Daily Tech Digest - October 27, 2020

How realistic is the promise of low-code?

“Grady Booch, one of the fathers of modern computer science, said the whole history of computer scientists layering is adding new layers of abstraction. On top of existing technology, low-code is simply a layer of abstraction that makes the process of defining logic, far more accessible for the most people. “Even children are being taught the code programming through languages such as MIT‘s scratch, a visual programming language. Just like humans communicate through both words and pictures with a picture, being worth roughly 1000 words. So, developers can develop using both code, and low-code or visual programming languages. “Visual language is much more accessible for many people, as well, much safer. So many business users who are great subject matter experts can make small dips into defining logic or user interfaces, through low-code systems, without necessarily having to commit hours and days to developing a feature through more sophisticated methods.” ...  Tools that use a visual node editor to create code paths are impressive but the code still exists as a base layer for advanced control. I once built a complete mobile video game using these visual editors. Once workflows get slightly more complex it’s helpful to be able to edit the code these tools generate.


“The Surgical Team” in XXI Century

In the surgical team of XXI century, every artifact shall have a designated owner. With ownership comes responsibility for quality of the artifact which is assessed by people who consume it (for example, consumers of designs are developers, and consumers of code are other developers who need to review it or interface with it). Common ownership as advocated by Extreme Programming can only emerge as the highest form of individual ownership in highly stable teams of competent people who additionally developed interpersonal relationships (a.k.a. friendship), and feel obligated to support one another. In other situations, collective ownership will end up with tragedy of commons caused by social loathing. Each team member will complete his assignments with least possible effort pushing consequences of low quality on others (quality of product artifacts becomes "the commons"). This is also the reason why software development outsourcing is not capable of producing quality solutions. The last pillar is respect. It is important for architect and administrator not to treat developers, testers and automation engineers as replaceable grunts (a.k.a. resources). An architect being the front-man of the team needs to be knowledgeable and experienced but it doesn’t mean that developers or testers aren’t. 


The great rebalancing: working from home fuels rise of the 'secondary city'

There are already signs of emerging disparity. Weekday footfall in big urban centres, which plummeted during lockdown, has not bounced back – the latest figures suggest less than one-fifth of UK workers have returned to their physical workplaces – which has led to reductions in public transport. This disadvantages low-income workers and people of colour, and has led to job losses at global chains such as Pret a Manger and major coffee franchises. Meanwhile, house prices in the Hamptons have reached record highs as wealthy New Yorkers have opted to weather the pandemic at the beach. Companies have also started capitalising on reduced occupancy costs – potentially passing them on to workers. The US outdoors retailer REI plans to sell its brand-new Seattle campus, two years in the making, in favour of smaller satellite sites. In the UK, government contractor Capita is to close more than a third of its 250 offices after concluding its 45,000 staff work just as efficiently at home. Not every community will be able to take advantage of the remote working boom, agrees Serafinelli. Those best placed to do so already have – or are prepared to invest in – good-quality schools, healthcare and transport links.


Deno Introduction with Practical Examples

Deno was originally announced in 2018 and reached 1.0 in 2020, created by the original Node.js founder Ryan Dahl and other mindful contributors. The name DE-NO may seem odd until you realize that it is simply the interchange of NO-DE. The Deno runtime: Adopts security by default. Unless explicitly allowed, Deno disallows file, network, or environment access; Includes TypeScript support out-of-the-box; Supports top-level await; Includes built-in unit testing and code formatting (deno fmt); Is compatible with browser JavaScript APIs: Programs authored in JavaScript without the Deno namespace and its internal features should work in all modern browsers; Provides a one-file executable bundler through deno bundle command which lets you share your code for others to run without installing Deno. ... Putting simplicity and security into consideration, Deno ships with some browser-related APIs which allows you to create a web server with little or no difference from a client-side JavaScript application, with APIs including fetch(), Web Worker and WebAssembly. You can create a web server in Deno by importing the http module from the official repo. Although there are already many libraries out there, the Deno system has also provided a straightforward way to accomplish this.


How to Successfully Integrate Security and DevOps

As digitalization transforms industries and business models, organizations increasingly are adopting modern software engineering practices such as DevOps and agile to become competitive in the modern marketplace. DevOps enables organizations to release new products and features faster, but this pace and frequency of application releases can conflict with established practices of handling security and compliance. This leads to the enterprise paradox to go faster and innovate but stay secure by avoiding compromises on controls. However, integrating security into DevOps efforts (DevSecOps) across the whole product life cycle rather than being handled independently or left until the end of the development process after a product is released can help organizations significantly reduce their risk posture, making them more agile and their products more secure and reliable. When properly implemented, DevSecOps offers immense benefits such as easy remediation of vulnerabilities and a tool to mitigate against cost overruns due to delays. It also enables developers to tackle security issues more quickly and effectively.


Forrester: CIOs must prepare for Brexit data transfer

According to the Information Commissioner’s Office (ICO), while the government has said that transfers of data from the UK to the European Economic Area (EEA) will not be restricted, from the end of the transition period, unless the EC makes an adequacy decision, GDPR transfer rules will apply to any data coming from the EEA into the UK. The ICO website recommended that businesses consider what GDPR safeguards they can put in place to ensure that data can continue to flow into the UK. Forrester also highlighted the lack of an adequacy decision, which it said would impact the supply chain of all businesses that rely on technology infrastructure in the UK when dealing with European citizens’ personal data. The analyst firm predicted that cloud providers will start to provide a way for their customers to make this transition. The authors of the report recommended that companies should focus on assessing compliance with UK data protection requirements, including the UK’s GDPR, and determine how lack of an adequacy decision will impact data transfers and work on a transition strategy. While the ICO is the UK’s supervisory authority (SA) for the GDPR, in July the European Data Protection Board (EDPB) stated that it will no longer qualify as a competent SA under the GDPR at the end of the transition period.


Ransomware vs WFH: How remote working is making cyberattacks easier to pull off

"You have a much bigger attack surface; not necessarily because you have more employees, but because they're all in different locations, operating from different networks, not working with the organisation's perimeter network on multiple types of devices. The complexity of the attack surface grows dramatically," says Shimon Oren, VP of research and deep learning at security company Deep Instinct. For many employees, the pandemic could have been the first time that they've ever worked remotely. And being isolated from the corporate environment – a place where they might see or hear warnings over cybersecurity and staying safe online on a daily basis, as well as being able to directly ask for advice in person, makes it harder to make good decisions about security. "That background noise of security is kind of gone and that makes it a lot harder and security teams have to do a lot more on messaging now. People working at home are more insular, they can't lean over and ask 'did you get a weird link?' – you don't have anyone do to that with, and you're making choices yourself," says Sherrod DeGrippo, senior director of threat research at Proofpoint. "And the threat actors know it and love it. We've created a better environment for them," she adds.


Machine learning in network management has promise, challenges

It’s difficult to say how rapidly enterprises are buying AI and ML systems, but analysts say adoption is in the early stages. One sticking point is confusion about what, exactly, AI and ML mean. Those imagining AI as being able to effortlessly identify attempted intruders, and to analyze and optimize traffic flows will be disappointed. The use of the term AI to describe what’s really happening with new network management tools is something of an overstatement, according to Mark Leary, research director at IDC. “Vendors, when they talk about their AI/ML capabilities, if you get an honest read from them, they’re talking about machine learning, not AI,” he said. There isn’t a hard-and-fast definitional split between the two terms. Broadly, they both describe the same concept—algorithms that can read data from multiple sources and adjust their outputs accordingly. AI is most accurately applied to more robust expressions of that idea than to a system that can identify the source of a specific problem in an enterprise computing network, according to experts. “We’re probably overusing the term AI, because some of these things, like predictive maintenance, have been in the field for a while now,” said Jagjeet Gill, a principal in Deloitte’s strategy practice.


The Past and Future of In-Memory Computing

“With the explosion in the adoption of IoT (which is soon to be catalyzed by 5G wireless networking), countless data sources in our daily life now generate continuous streams of data that need to be mined to save lives, improve efficiency, avoid problems and enhance experiences,” Bain says in an email to Datanami. “Now we can track vehicles in real-time to keep drivers safe, ensure the safe and rapid delivery of needed goods, and avoid unexpected mechanical failures. Health-tracking devices can generate telemetry that enables diagnostic algorithms to spot emerging issues, such as heart irregularities, before it becomes urgent. Web sites can track e-commerce shoppers to assist them in finding the best products that meet their needs.” IMDGs aren’t ideal for all streaming or IoT use cases. But when the use case is critical and time is of the essence, IMDGs will be have a role in orchestrating the data and providing fast response times. “The combination of memory-based storage, transparent scalability, high availability, and integrated computing offered by IMDGs ensures the most effective use of computing resources and leads to the fastest possible responses,” Bain writes. “Powerful but simple APIs enable application developers to maintain a simplified view of their data and quickly analyze it without bottlenecks. IMDGs offer the combination of power and ease of use that applications managing live data need more than ever before.”


Work from home strategies leave many companies in regulatory limbo

A solution for this crucial predicament is a potential temporary regulatory grace period. Regulatory bodies or lawmakers could establish a window of opportunity for organizations to self-identify the type and duration of their non-compliance, what investigations were done to determine that no harm came to pass, and what steps were, or will be, taken to address the issue. Currently, the concept of a regulatory grace period is slowly gaining traction in Washington, but time is of the essence. Middle market companies are quickly approaching the time when they will have to determine just what to disclose during these upcoming attestation periods. Companies understand that mistakes were made, but those issues would not have arisen under normal circumstances. The COVID-19 pandemic is an unprecedented event that companies could have never planned for. Business operations and personal safety initially consumed management’s thought processes as companies scrambled to keep the lights on. Ultimately, many companies made the right decisions from a business perspective to keep people working and avoid suffering a data breach, even in a heightened environment of data security risks. Any grace period would not absolve the organization of responsibility for any regulatory exposures.



Quote for the day:

"Our expectation in ourselves must be higher than our expectation in others." -- Victor Manuel Rivera

Daily Tech Digest - October 26, 2020

How to hold Three Amigos meetings in Agile development

Three Amigos meetings remove uncertainty from development projects, as they provide a specified time for everyone to get on the same page about what to -- or not to -- build. "The meeting exposes any potential assumptions and forces explicit answers," said Jeff Sing, lead software QA engineer at Optimizely, a digital experience optimization platform. "Everyone walks away with crystal-clear guidelines on what will be delivered and gets ahead of any potential scope creep." For example, a new feature entails new business requirements, engineering changes, UX flow and design. Each team faces its own challenges and requirements. The business requirements focus on a broad problem space, and how to monetize the product. The engineering requirements center on the technical solution and hurdles. The UX requirements define product usability. The design requirements ensure the product looks finished. All of these requirements might align -- or they might not. "This is why a formalized meeting needs to occur to hash out how to achieve everyone's goals, or which requirements will not be met and need to be dropped in order to build the right product on the right time schedule," Sing said.


Key success factors behind intelligent automation

For an intelligent automation programme to really deliver, a strategy and purpose is needed. This could be improving data quality, operational efficiency, process quality and employee empowerment, or enhancing stakeholder experiences by providing quicker, more accurate responses. Whatever the rationale, an intelligent automation strategy must be aligned to the wider needs of the business. Ideally, key stakeholders should be involved in creating the vision; if they haven’t, engage them now. If they see intelligent automation as a strategic business project, they’ll support it and provide the necessary financial and human resources too. Although intelligent automation is usually managed by a business team, it will still be governed by the IT team using existing practices, so they must also be involved at the beginning. IT will support intelligent automation on many critical fronts, such as compliance with IT security, auditability, the supporting infrastructure, its configuration and scalability. So intelligent automation can scale as demand increases, plan where it sits within the business. A centralised approach encompasses the entire organisation, so it may be beneficial to embed this into a ‘centre of excellence’ (CoE) or start moving towards creating this operating environment.,/div.


Why Most Organizations’ Investments in AI Fall Flat

A common mistake companies make is creating and deploying AI models using Agile approaches fit for software development, like Scrum or DevOps. These frameworks traditionally require breaking down a large project into small components so that they can be tackled quickly and independently, culminating in iterative yet stable releases, like constructing a building floor by floor. However, AI is more like a science experiment than a building. It is experiment-driven, where the whole model development life cycle needs to be iterated—from data processing to model development and eventually monitoring—and not just built from independent components. These processes feed back into one another; therefore, a model is never quite “done.” ... We know AI requires specialized skill sets—data scientists remain highly sought-after hires in any enterprise. But it’s not just the data scientists who build the models and product owners who manage the functional requirements who are necessary in order for AI to work. The emerging role of machine-learning engineer is required to help scale AI into reusable and stable processes that your business can depend on. Professionals in model operations (model ops) are specialized technicians who manage post-deployment model performance and are ultimately responsible for ongoing stability and continuity of operations.


Cybersecurity as a public good

The necessity to privately provision cyber security has resulted in a significant gap between the demand for cyber security professionals and the supply of professionals with appropriate skills. Multiple studies have identified cyber security as the domain with one of the highest skills gap. When a significant skills gap occurs in the market, it results in two things. The remuneration demanded by the professionals will sky rocket since there are many chasing the scarce resources. Professionals who are not so skilled will also survive — rather thrive — since lack of alternatives means they will continue to be in demand. ...  Security as a public good involves trade-offs with privacy. Whether it is police patrols, or CCTV cameras — a trade-off with privacy is imperative to make security a public good. The privacy trade-off risks will be higher in the cyber world because technology would provide the capability to conduct surveillance at larger scale and also larger depth. It is crucial , delicate — and hence difficult — to strike the right balance between security and privacy such that the extent of privacy sacrificed meets the test of proportionality. However, the complexity of the task, or the associated risks with it, should not prevent us from getting out of the path down a rabbit hole.


The Art and Science of Architecting Continuous Intelligence

Loosely defined, machine data is generated by computers rather than individuals. IoT equipment sensors, cloud infrastructure, security firewalls and websites all throw off a blizzard of machine data that measures machine status, performance and usage. In many cases the same math can analyze machine data for distinct domains, identifying patterns, outliers, etc. Enterprises have well-established processes such as security information and event management (SIEM), and IT operations (ITOps), that process machine data. Security administrators, IT managers and other functional specialists use mature SIEM and ITOps processes on a daily basis. Generally, these architectures perform similar functions as in the first approach, although streaming is a more recent addition. Another difference is that many machine-data architectures have more mature search and index capabilities, as well as tighter integration with business tasks and workflow. Data teams typically need to add the same two functions to complete the CI picture. First, they need to integrate doses of contextual data to achieve similar advantages as those outlined above. Second, they need to trigger business processes, which in this case might mean hooking into robotic process automation tools.


Fintech Startups Broke Apart Financial Services. Now The Sector Is Rebundling

When fintech companies began unbundling, the tools got better but consumers ended up with 15 personal finance apps on their phones. Now, a lot of new fintechs are looking at their offerings and figuring out how to manage all of a person’s personal finances so that other products can be enhanced, said Barnes. “We are not trying to be a bunch of products, but more about how each product helps the other,” Barnes said. “If we offer a checking account, we can see income coming in and be able to give you better access to borrowing. That is the rebuild—how does fintech serve all of the needs, and how do we leverage it for others?” Traditional banking revolves around relationships for which banks can sell many products to maximize lifetime value, said Chris Rothstein, co-founder and CEO of San Francisco-based sales engagement platform Groove, in an interview. Rebundling will become a core part of workflow and a way for fintechs to leverage those relationships to then be able to refer them to other products, he said. “It makes sense long-term,” Rothstein said in an interview. “In financial services, many people don’t want all of these organizations to have their sensitive data. Rebundling will also force incumbents to get better.”


Microsoft Glazes 5G Operator Strategy

Microsoft’s 5G strategy links the private Azure Edge Zones service it announced earlier this year, Azure IoT Central, virtualized evolved packet core (vEPC) software it gained by acquiring Affirmed Networks, and cloud-native network functions it brought onboard when it acquired Metaswitch Networks. Combining those services under a broader portfolio allows Microsoft to “deliver virtualized and/or containerized network functions as a service on top of a cloud platform that meets the operators where they are, in a model that is accretive to their business,” Hakl said.  “We want to harness the power of the Azure ecosystem, which means the developer ecosystem, to help [operators] monetize network slicing, IoT, network APIs … [and] use the power of the cloud” to create the same type of elastic and scalable architecture that many enterprises rely on today, he explained. That vision is split into two parts: the Azure Edge Zones, which effectively extends the cloud to a private edge environment, and the various pieces of software that Microsoft has assembled for network operators. On the latter, Hakl said Microsoft “could have gone out and had our customers teach us that over time. Instead, we acquired two companies that brought in hundreds of engineers that have telco DNA and understand the space.”


Artificial intelligence for brain diseases: A systematic review

Among the various ML solutions, Deep Neural Networks (DNNs) are nowadays considered as the state-of-the-art solution for many problems, including tasks on brain images. Such human brain-inspired algorithms have been proven to be capable of extracting highly meaningful statistical patterns from large-scale and high-dimensional datasets. A DNN is a DL algorithm aiming to approximate some function f ∗. For example, a classifier can be seen as a function y = f * ( x , θ ) mapping a given input x to a category labeled as y. θ is the vector of parameters that the model learns in order to make the best approximation of f ∗. Artificial Neural Networks (ANNs) are built out of a densely interconnected set of simple units, where each unit takes a number of real-valued inputs (possibly the outputs of other units) and produces a single real-valued output (which may become the input to many other units). DNNs are called networks because they are typically represented by composing together many functions. The overall length of the chain gives the depth of the model; from this terminology, the name “deep learning” arises. 


Things to Consider about Brain-Computer Interface Tech

A BCI is a system that provides a direct connection between your brain and an electronic device. Since your brain runs on electrical signals like a computer, it could control electronics if you could connect the two. BCIs attempt to give you that connection. There are two main types of BCI — invasive and non-invasive. Invasive devices, like the Neuarlink chip, require surgery to implant them into your brain. Non-invasive BCIs, as you might’ve guessed, use external gear you wear on your head instead. ... A recent study suggested that brain-computer interface technology and NeuraTech in general could measure worker comfort levels in response to their environment. They could then automatically adjust the lights and temperature to make workers more comfortable and minimize distractions. Since distractions take up an average of 2.1 hours a day, these BCIs could mean considerable productivity boosts. The Department of Defense is developing BCIs for soldiers in the field. They hope these devices could let troops communicate silently or control drones with their minds. As promising as BCIs may be, there are still some lingering concerns with the technology. While the Neuralink chip may be physically safe, it raised a lot of questions about digital security. 


Microsoft did some research. Now it's angry about what it found

A fundamental problem, said Brill is the lack of trust in society today. In bold letters, she declared: "The United States has fallen far behind the rest of the world in privacy protection." I can't imagine it's fallen behind Russia, but how poetic if that was true. Still, Brill really isn't happy with our government: "In total, over 130 countries and jurisdictions have enacted privacy laws. Yet, one country has not done so yet: the United States." Brill worries our isolation isn't too splendid. She mused: "In contrast to the role our country has traditionally played on global issues, the US is not leading, or even participating in, the discussion over common privacy norms." That's like Microsoft not participating in the creation of excellent smartphones. It's not too smart. Brill fears other parts of the world will continue to lead in privacy, while the US continues to lead in inaction and chaos. It sounds like the whole company is mad as hell and isn't going to take it anymore. Yet it's not as if Microsoft has truly spent the last 20 years championing privacy much more than most other big tech companies. In common with its west coast brethren, it's been too busy making money.



Quote for the day:

"Leadership is about carrying on when everyone else has given up" -- Gordon Tredgold

Daily Tech Digest - October 25, 2020

Meet modern compliance: Using AI and data to manage business risk better

Strong, tech-enabled, third-party risk management capabilities can strengthen corporate governance, which will in turn enhance reputation and build trust. In essence, compliance should no longer be seen simply as a backroom cost center. Rather, it is a means of strengthening the business brand, increasing productivity, and driving growth of market share, with relevance at the C suite and at the board level. ... “By engaging early in the sales contract life cycle and providing compliance oversight and ongoing risk education, we [at Microsoft] have been able to realize better, more compliant deal construction. This is critical at quarter-end when deal volumes spike. Sellers internalize the risk guidance and proactively ensure their contract meets the company’s compliance standards — often reducing monetary concessions that improve margin and profitability.” Four years ago, PwC and Microsoft worked closely together to further develop a tech-enabled compliance analytics suite of tools called Risk Command. “We started the journey to respond to internal and external pressures to embrace a ‘data-driven’ approach,” Gibson recalled. “But it appears to be what regulators are now expecting and serves as a benchmark for what others may want to do.”


Is The Cybersecurity Industry Selling Lemons? Apparently Lots Of Important CISOs Think it Is

If it’s true that poor products have contributed to the success of cyberattacks then something must be wrong, but what? The report’s thesis – which borrows its title from economist George Akerlof’s Nobel Prize winning 1970 paper on the same topic – doesn’t sugar coat it: cybersecurity has become an industry that keeps churning out lemons that not enough people complain about. Searing tech skepticism is nothing new of course – Clifford Stoll’s Silicon Snake Oil or Michael Lewis’s satirical The New New Thing come to mind – but those were about issues (the Internet will go wrong, dotcom excess), people have already processed. Cybersecurity, by contrast, is all that stands between us and a world where criminality contorts the system in ways that cost livelihoods and whole economies. Bad cybersecurity isn’t just inconvenient, it’s dangerous and somebody needs to say this now. The authors believe the underlying problem is economic rather than technical. Technology doesn’t work as claimed because the market relationship between customers and the vendors has broken down. This manifests as an ‘information asymmetry’ where vendors know how good their product is, but their customers not only don’t know but don’t have time to find out.


How advanced AI language tools could change the workplace

Within the last decade, some of the most notable breakthroughs in artificial intelligence (AI) have come in the form of computer vision. Essentially giving robotics systems ‘eyesight’, in the ability to identify and classify objects using image or video recognition, the technology has been put to use in anything from facial recognition systems and quality control in manufacturing to anomalies in MRI scans and self-driving vehicle systems. And while computer vision applications are still comparatively nascent, the ‘breakthrough’ AI applications of the decade ahead might well come in the form of advances in language-based applications. AI research and deployment company OpenAI developed the largest language model ever created this year, GPT-3. The software can generate human-like text on demand and is set to be turned into a commercial product later this year, as a paid-for subscription via the cloud for businesses. It represents a leap forward from previous language processing models that used hand-coded rules, statistical techniques, and increasingly artificial neural networks — which can learn from raw data, with less reliance on data labelling — to perform language processing.


Open-source software detects potential collisions in radiotherapy plans

The RadCollision software needs to be embedded into each TPS database and a folder (STL files) with the 3D models of the machines prepared. RadCollision is currently limited to use with the RayStation TPS, but versions for use with other commercial TPS are planned, says first author Fernando Hueso-González. The researchers quantitatively evaluated their software using the RayStation TPS with four patient treatment plans that were found infeasible during previous collision checks by therapists. The software reported collisions with the couch at similar angles to those reported experimentally. The team also tested the software with a model of a proton treatment room and a robotic patient positioning system. “In one case, we tested in the RadCollision software a beam where the dosimetrist doubted that there was enough clearance with the toe of a patient’s foot. RadCollision predicted that clearance would be very tight, but the irradiation-optimized TPS was feasible,” comments Remillard. “When we performed a dry run, there was no collision.” The team note that the reliability of the collision assessment depends upon the accuracy of the input data.


Technology is about to destroy millions of jobs. But, if we're lucky, it will create even more

CIOs are effectively banking on AI systems and machines to carry out tasks that would have previously been taken on manually. For example, the WEF predicts that in 2025, machines will be performing up to 65% of information and data processing and retrieval, leaving only 35% of the job to humans. This means that some roles are set to become increasingly redundant in the next few years. Data entry clerks, accountants and auditors, and factory workers are among the jobs that the WEF expects to be particularly displaced by automation. At the same time, growth in so-called "jobs of tomorrow" will offset the lack of demand for workers in jobs that can be filled by machines. Leading the polls for positions in growing demand are roles linked to the green economy, data, AI, and cloud computing. Think data analysts, machine-learning specialists, robotics engineers or software developers. Jumping from a redundant job to one in high demand is no easy challenge. The "jobs of tomorrow" will require new skills; in fact, the vast majority of employers (94%) surveyed by the WEF said that they expected employees to pick up new skills on the job. The past few months have seen employees and employers alike getting started with tackling the issue. 


How Artificial Intelligence is Transforming the Insurance Space

Although insurance CEOs are conscious of the herald of digital disruption breaking through the industry, it will be a whole new challenge to keep up with these revolutionary changes and to see it beyond the plain integration of modern technology. Intelligent solutions must be innovative enough to foster better customer relationship and deliver customer experience in a way that inspires much-needed poise between incipient market expectations and cost optimization. Apart from these, another pressure point is coming from emerging InsurTech entrants who are giving rise to tough competition by creating affordable solutions to reach and serve customers. What is relaxing is that to surpass this challenge, industry leaders are prepared to embrace new innovative possibilities and appreciate the role of creativity in evolving the processes and becoming a beloved brand in the financial marketplace. Over the last two years, we have seen the widespread advent and adoption of AI across multiple industries (be it hospitality or be it healthcare). The idea of digital technologies ruling the financial market isn’t exactly new since Nasdaq in its early days established a secure connected network of trading desks for integrated customer data records.


Voice Payment in Banking: The New Revolution in Fintech

Voice recognition methods use biometrics data to identify who’s speaking with virtual assistants. The robotic assistants have gone through so much changes and updating that you won’t be able to differentiate whether it’s a human or AI is talking to you. However there are a lot of privacy concerns around smart speakers. 33% of U.S. surveyed adults said they had security concerns which restrain them from purchasing the devices. Estimated that in January 2019 26% of people showed a strong concern about speaker’s privacy risk. The number jumped to 30% in January 2020. The reason is exposure to recorded conversations. All of the world’s biggest voice assistant providers Amazon, Google, Apple, Microsoft, Facebook are listening to some utterances because machine learning won’t be efficient if there would be no improvements in conversations between humans and devices. However, some situations were real leakage of consumer secret information which caused many doubts and indicated privacy as key risk in voice assistant technology.AI updates will facilitate the ability to understand accents, dialects, intonations and more. Fingertips is unique biometrics data which is an important secure measure. 48% of people have used biometrics to make payment.


How blockchain is used to transform the lives of people in marginalised communities

A key aim of the Building Blocks project is to provide people in refugee camps with the means of buying food and necessities quickly and securely using direct cash transfers. Another objective is to ensure they no longer have to worry about food vouchers being lost or stolen or about third party organisations, such as banks, having access to their personal data. Direct cash transfers, according to WFP research, are often the most effective and efficient way to distribute humanitarian assistance as well as support local economies. But being able to distribute it relies on the support of local financial institutions, which are not always in a position to do so, not least because many refugees face restrictions in opening bank accounts. To try and address the situation, in early 2017 the WFP introduced a proof-of-concept blockchain-based system to register and authenticate transactions in Sindh province, Pakistan, which did not require a bank to act as an intermediary to connect both parties. The system is now being used to support 106,000 Syrian refugees in the Azraq and Zaatari camps in Jordan and 500,000 Rohingyas in the Cox's Bazar camp in Bangladesh.


Chip industry is going to need a lot more software to catch Nvidia’s lead in AI

"Software is the hardest word," quipped Gwennap, referring to the struggles of competitors. He noted how companies either don't support some aspects of popular AI frameworks, such as TensorFlow, or how some AI applications for competing chips may not even compile properly. "To compete against deep software stacks from companies such as Nvidia and Intel, these vendors must support a broad range of frameworks and development environments with drivers, compilers, and debug tools that deliver full acceleration and optimal performance for a variety of customer workloads." ... The use of AI is spreading from cloud computing data centers where it has traditionally been developed to embedded devices in automobiles and infrastructure. Vendors such as the UK's Imagination and Think Silicon, a division of chip equipment giant Applied Materials, are pushing the boundaries in low-power designs that can go into power-constrained devices, such as battery-powered, microcontroller gadgets.  The stakes seem suddenly higher since Nvidia announced last month that it intends to buy Arm Plc for $40 billion. Arm makes the intellectual property at the heart of all the chips made by all the challengers in the chip industry. Hence, Nvidia's software is poised to gain even greater sway.


JP Morgan Veteran Daniel Masters Explains How Blockchain Will End Commercial Banks

The most interesting aspect of CBDCs is the impact they will have on commercial banks and the financial system as a whole. Today, central banks issue currency to a slew of commercial banks like Chase and Bank of America. These banks do two things—create products and services such as mortgages, and deal with the end users. I think we are going into a new paradigm where central banks issue CBDCs, commercial banks cease to exist and the service layer is filled by crazy new emerging companies like Compound Finance, Uniswap, SushiSwap, and people that are really getting distributed, decentralized finance done today. Then the final interesting layer is who actually faces the consumer. You can already see that there are multiple choices. Coinbase would like to get to all the users, as would Binance though probably not in America. You’ve got wallet infrastructures like Blockchain.com that already have 50 million outstanding wallets. That said, you could get incumbents as well. Samsung is putting chips into phones now, making them essentially hardware wallets. Amazon could come out with a digital wallet. Whoever owns that level at the bottom is critical.



Quote for the day:

"We are drowning in information, but starved for knowledge." -- John Naisbitt

Daily Tech Digest - October 24, 2020

How will self-driving cars affect public health?

The researchers created a conceptual model to systematically identify the pathways through which AVs can affect public health. The proposed model summarizes the potential changes in transportation after AV implementation into seven points of impact: transportation infrastructure; land use and the built environment; traffic flow; transportation mode choice; transportation equity; and jobs related to transportation and traffic safety. The changes in transportation are then attributed to potential health impacts. In optimistic views, AVs are expected to prevent 94% of traffic crashes by eliminating driver error, but AVs’ operation introduces new safety issues such as the potential of malfunctioning sensors in detecting objects, misinterpretation of data, and poorly executed responses, which can jeopardize the reliability of AVs and cause serious safety consequences in an automated environment. Another possible safety consideration is the riskier behavior of users because of their overreliance on AVs—for example, neglecting the use of seatbelts due to an increased false sense of safety. AVs have the potential to shift people from public transportation and active transportation such as walking and biking to private vehicles in urban areas, which can result in more air pollution and greenhouse gas emissions and create the potential loss of driving jobs for those in the public transit or freight transport industries.


Now’s The Time For Long-Term Thinking

For most financial institutions, the strategic planning process for 2021 is far different than any in the past. As opposed to an iterative adjustment to plans from the previous year, this year’s planning must take into account a level of change in technology, competition, consumer behaviors, society and many other areas that is far less defined than before. The uncertainty about the future requires a combination of a solid strategic foundation with sensing capabilities and the ability to respond to threats and opportunities as quickly as possible. For many banks and credit unions, this will require organizational restructuring, the reallocation of resources, revamping processes, finding new outside partners and a culture that will support flexibility in plans that never was required before. There is also the need to build a marketplace sensing capability across the entire organization and from a broader array of sources. This includes customers, internal staff (especially customer-facing employees), suppliers, strategic partners, research organizations, boards of directors and even competition. Gathering the insights is only half the battle. There must also be a centralized location to gather and analyze the insights collected.


Rapid Threat Evolution Spurs Crucial Healthcare Cybersecurity Needs

Cybercriminals have been actively taking advantage of the global pandemic, with an increase in cyberattacks, phishing, spear-phishing, and business email compromise (BEC) attempts. And on the healthcare side of things, NSCA Executive Director, Kelvin Coleman, said it’s not a huge surprise.  Even in the early 1900s during the Spanish flu pandemic, folks would put articles in newspapers to take advantage of the crisis with hoaxes and scams, Coleman explained. “Bad actors take advantage of crises,” he said. “Hackers are being aggressive, leveraging targeted emails and phishing attempts. Josh Corman, cofounder of IAmTheCalvary.org and DHS CISA Visiting Researcher, stressed that when a provider is forced into EHR downtime and to divert patient care, it’s even more nightmarish during a pandemic. In Germany, a patient died earlier this month after a ransomware attack shut down operations at a hospital, and she was diverted to another hospital. These are criminals without scruples, Corman explained. The attacks were happening before the pandemic, but there’s been no cease- fire amid the crisis. In healthcare, hackers continue to rely on previously successful attack methods – especially phishing. It continues to be a successful attack method. 


FBI, CISA: Russian hackers breached US government networks, exfiltrated data

US officials identified the Russian hacker group as Energetic Bear, a codename used by the cybersecurity industry. Other names for the same group also include TEMP.Isotope, Berserk Bear, TeamSpy, Dragonfly, Havex, Crouching Yeti, and Koala. Officials said the group has been targeting dozens of US state, local, territorial, and tribal (SLTT) government networks since at least February 2020. Companies in the aviation industry were also targeted, CISA and FBI said. The two agencies said Energetic Bear "successfully compromised network infrastructure, and as of October 1, 2020, exfiltrated data from at least two victim servers." The intrusions detailed in today's CISA and FBI advisory are a continuation of attacks detailed in a previous CISA and FBI joint alert, dated October 9. The previous advisory described how hackers had breached US government networks by combining VPN appliances and Windows bugs. Today's advisory attributes those intrusions to the Russian hacker group but also provides additional details about Energetic Bear's tactics. According to the technical advisory, Russian hackers used publicly known vulnerabilities to breach networking gear, pivot to internal networks, elevate privileges, and steal sensitive data.


Secure NTP with NTS

NTP can be secured well with symmetric keys. Unfortunately, the server has to have a different key for each client and the keys have to be securely distributed. That might be practical with a private server on a local network, but it does not scale to a public server with millions of clients. NTS includes a Key Establishment (NTS-KE) protocol that automatically creates the encryption keys used between the server and its clients. It uses Transport Layer Security (TLS) on TCP port 4460. It is designed to scale to very large numbers of clients with a minimal impact on accuracy. The server does not need to keep any client-specific state. It provides clients with cookies, which are encrypted and contain the keys needed to authenticate the NTP packets. Privacy is one of the goals of NTS. The client gets a new cookie with each server response, so it doesn’t have to reuse cookies. This prevents passive observers from tracking clients migrating between networks. The default NTP client in Fedora is chrony. Chrony added NTS support in version 4.0. The default configuration hasn’t changed. Chrony still uses public servers from the pool.ntp.org project and NTS is not enabled by default. Currently, there are very few public NTP servers that support NTS. The two major providers are Cloudflare and Netnod.


Non-Intimidating Ways To Introduce AI/ML To Children

The brainchild of IBM, Machine Learning for Kids is a free, web-based tool to introduce children to machine learning systems and applications of AI in the real world. Machine Learning for Kids is built by Dale Lane using APIs from IBM Watson. It provides hands-on experiments to train ML systems that recognise texts, images, sounds, and numbers. It leverages platforms such as Scratch and App Inventor to create interesting projects and games. It is also being used in schools as a significant resource to teach AI and ML to students. Teachers can also form their own admin page to manage their access to students. A product from the MIT Media Lab, Cognimates is an open-source AI learning platform for young children starting from age 7. Children can learn how to build games, robots, and train their own AI modes. Like Machine Learning for Kids, Cognimates is also based on Scratch programming language. It provides a library of tools and activities for learning AI. This platform even allows children to program intelligent devices such as Alexa. Another offering from Google in order to make learning AI fun and engaging is AIY. The name is an intelligent wordplay with AI and do-it-yourself (DIY).


How RPA differs from conversational AI, and the benefits of both

Enterprises are working to digitally transform core business processes to enable greater automation of backend processes and to encourage more seamless customer experiences and self-service at the frontend. We are seeing banks, insurers, retailers, energy providers and telcos working to develop their own digital assistants with a growing number of skills, while still providing a consistent brand experience. Developing bots doesn’t have to be complex. It is more important to carefully identify the right use cases where these technologies will deliver clear ROI with the least amount of effort. Whether an enterprise is applying RPA or conversational AI, or both, it’s important to first understand the business problem that needs to be solved, and then identify where bots will make an immediate difference. Then consider the investment required, barriers to successful implementation, and the expected business outcomes. It’s better to start small with a narrowly focused use case and achievable KPIs, rather than trying to do too much at once. Conversational AI and RPA are very powerful automation technologies. When designed well, a chatbot can automate up to 80% of routine queries that come into a customer service centre or IT helpdesk, saving an organisation time and money and enabling it to scale its operations.


Things to consider when running visual tests in CI/CD pipelines: Getting Started

Testing – it’s an important part of a developer’s day-to-day, but it’s also crucial to the operations engineer. In a world where DevOps is more than just a buzzword, where it’s become accepted as a mindset shift and culture change, we all need to consider running quality tests. Traditional testing may include UI testing, integration testing, code coverage checks, and so forth, but at some point, we still need eyeballs on a physical page. How many times have we seen a funny looking page because of CSS errors? Or worse yet, an important button like say, “Buy now” “missing” because someone changed the CSS and now the button blends in with the background? Logically, the page still works, and even from a traditional test perspective, the button can be clicked, and the DOM (used in UI Test verification) is perfect. Visually, however, the page is broken; this is where visual testing comes into play. Visual testing allows us to use automated UI testing with the power of AI to help us determine if a page “looks right” aside from just “functions right.” Earlier this year, I partnered with Angie Jones from Applitools in a joint webinar where we talked about best practices as it pertains to both Visual Testing and also CI/CD. This blog post is a summary of that webinar and how to handle visual testing in CI/CD.


Design patterns – for faster, more reliable programming

Every design has a pattern and everything has a template, whether it be a cup, house, or dress. No one would consider attaching a cup’s handle to the inside – apart from novelty item manufacturers. It has simply been proven that these components should be attached to the outside for practical purposes. If you are taking a pottery class and want to make a pot with handles, you already know what the basic shape should be. It is stored in your head as a design pattern, in a manner of speaking. The same general idea applies to computer programming. Certain procedures are repeated frequently, so it was no great leap to think of creating something like pattern templates. In our guide, we will show you how these design patterns can simplify programming. The term “design pattern” was originally coined by the American architect Christopher Alexander who created a collection of reusable patterns. His plan was to involve future users of the structures in the design process. This idea was then adopted by a number of computer scientists. Erich Gamma, Richard Helm, Ralph Johnson, and John Vlissides (sometimes referred to as the Gang of Four or GoF) helped software patterns break through and gain acceptance with their book “Design Patterns – Elements of Reusable Object-Oriented Software” in 1994.


Public and Private Blockchain: How to Differentiate Them and Their Use Cases

Public blockchain is the model of Bitcoin, Ethereum, and Litecoin and is essentially considered to be the original distributed ledger structure. This type of blockchain is completely open and anyone can join and participate in the network. It can receive and send transactions from anybody in the world, and can also be audited by anyone who is in the system. Each node (a computer connected to the network) has as much transmission and power as any other, making public blockchains not only decentralized, but fully distributed, as well. ... Private blockchains, on the other hand, are essentially forks of the originator but are deployed in what is called a permissioned manner. In order to gain access to a private blockchain network, one must be invited and then validated by either the network starter or by specific rules that were put into place by the network starter. Once the invitation is accepted, the new entity can contribute to the maintenance of the blockchain in the customary manner. Due to the fact that the blockchain is on a closed network, it offers the benefits of the technology but not necessarily the distributed characteristics of the public blockchain.



Quote for the day:

"Every moment is a golden one for those who have the vision to recognize it as such." -- Henry Miller

Daily Tech Digest - October 23, 2020

Enterprise Architecture and Tech Debt

Architects must assess the changed needs of the business, – customers, staff, supply chain and identify efficient technology to support those new requirements. There is opportunity to walk away from legacy technology containing Unplanned Tech Debt that has never been corrected, the result of poor practices or poorly communicated requirements. The move to remote workspace may present the option to discontinue the use of equipment or applications that have become instances of Creeping Tech Debt where features become obsolete, replaced by the better, faster more capable upgrades. Or, the applications and operating systems are no longer supported, causing security vulnerabilities. Changes in market dynamics as the customer base struggles to understand their new needs, constraints and opportunities invite architects and product developers to consider incurring Intentional Tech Debt. By releasing prototypes and minimal viable products (MVPs) customers become partners in product development, helping to build the plane even as it reaches cruising altitude. Architects know this will entail false starts as perceived requirements morph or fade away and require rework as the product matures.


Understanding GraphQL engine implementations

Generic and flexible are the key words here and it’s important to realize that it’s hard to keep generic APIs performant. Performance is the number one reason that someone would write a highly customized endpoint in REST (e.g. to join specific data together) and that is exactly what GraphQL tries to eliminate. In other words, it’s a tradeoff, which typically means we can’t have the cake and eat it too. However, is that true? Can’t we get both the generality of GraphQL and the performance of custom endpoints? It depends! Let me first explain what GraphQL is, and what it does really well. Then I’ll discuss how this awesomeness moves problems toward the back-end implementation. Finally, we’ll zoom into different solutions that boost the performance while keeping the generality, and how that compares to what we at Fauna call “native” GraphQL, a solution that offers an out-of-the-box GraphQL layer on top of a database while keeping the performance and advantages of the underlying database. Before we can explain what makes a GraphQL API “native,” we need to explain GraphQL. After all, GraphQL is a multi-headed beast in the sense that it can be used for many different things. First things first: GraphQL is, in essence, a specification that defines three things: schema syntax, query syntax, and a query execution reference.


Digital transformation starts with software development

Software development is another key requirement for businesses that are pursuing digital transformation quests. Leveraging technology and ensuring it is able to offer reliable and high quality results is a key focus for the majority of companies. At this stage, it is important for businesses to acknowledge what its strategic goals are and implement software that is going to help it reach those ambitions and achieve tangible results. Businesses should also ensure the technology it selects is equipped with sustainable software that is going to withstand time, inevitable digital advances and deliver the requirements of the new normal. In addition, today’s current climate has emphasised the importance of providing teams with reliable software that enables them to work remotely and complete projects without any constraints. In the midst of the pandemic, 60% of the UK’s adult population were working remotely. Unfortunately, many businesses did not have the technology in place to cope with this immediate change. Therefore, IT decision makers and leaders had to undergo a rapid shift to remain agile and maintain continuity during this unprecedented time. By keeping software up to date and regularly enhancing tools, employees can remain productive and maintain a high level of communication with colleagues.


We need to be more imaginative about cybersecurity than we are right now

“Trying to achieve security is something of a design attitude—where at every level in your system design, you are thinking about the possible things that can go wrong, the ways the system can be influenced, and what circuit-breakers you might have in place in case something unforeseen happens,” said Mickens. “That seems like a vague answer because it is: There isn’t a magic way to do it.” Designers, Mickens continued, might even need to consider the political or ethical mindset of the people using their system. “There’s no simple way to figure out if our system is going to be used ethically or not, because ethics itself is very poorly defined. And when we think about security, we need to have a similarly broad attitude, saying that there are fundamental questions which are ambiguous, and which have no clean answer—‘What is security and how do I make my product secure?’ As a result, we need to be more imaginative than we are right now.” Thus, suggested Zittrain, the question has moved to the supply side: Consumers want safe products, and the onus is on designers to provide them. This, he said, opens an even thornier question: Does there need to be a regulatory board for people producing code, and if not, “What would incent the suppliers to worry about systematic risks that might not even be traced back to them?”


How to Make DevOps Work with SAFe and On-Premise Software

The main issues we dealt with in speeding up our delivery from a DevOps perspective were: testing (unit and integration), pipeline security check, licensing (open source and other), builds, static code analysis, and deployment of the current release version. For some of these problems we had the tools, for some, we didn’t and we had to integrate new tools. Another issue was the lack of general visibility into the pipeline. We were unable to get a glimpse of what our DevOps status was, at any given moment. This was because we were using many tools for different purposes and there was no consolidated place where someone could take a look and see the complete status for a particular component or the broader project. Having distributed teams is always challenging getting them to come to the same understanding and visibility for the development status. We implemented a tool to enable a standard visibility into how each team was doing and how the SAFe train(s) were doing in general. This tool provided us with a good overview of the pipeline health. The QA department has been working as the key-holder of the releases. Its responsibility is to check the releases against all bugs and not allow the version to be released if there are critical bugs.


The Two Sides of AI in the Modern Digital Age

We will now discuss some of its more sinister aspects. As we’ve already mentioned, as the digital landscape welcomes an increasing number of technological advancements, so does the threat landscape. With rapid progress in the cybersecurity arena, cybercriminals have turned to AI to amp up on their sophistication. One such way through which hackers leverage the potential of artificial intelligence is by using AI to hide malicious codes in otherwise trustworthy applications. The hackers program the code in such a way that it executes after a certain period has elapsed, which makes detection even more difficult. In some cases, cybercriminals programmed the code to activate after a particular number of individuals have downloaded the application, which maximizes the attack’s attack’s impact. Furthermore, hackers can manipulate the power offered by artificial intelligence, and use the AI’s ability to adapt to changes in the environment for their gain. Typically, hackers employ AI-powered systems adaptability to execute stealth attacks and formulate intelligent malware programs. These malware programs can collect information on why previous attacks weren’t successful during attacks and act accordingly.


A Pause to Address 'Ethical Debt' of Facial Recognition

This pause is needed. All too often, ethics lags technology. With all apologies to Jeff Goldblum, there's no need to be hunted by intelligent dinosaurs to realize that we often do things because "we can rather than that we should." This ACM's call for restraint is appropriate, although a few issues remain. What about the facial data that already exists from currently deployed systems? This is not unique to facial recognition, but rather one that is well known from GDPR compliance and other use cases. The stoppage is intended for private and public entities, but personal cameras — and an opening for facial recognition — are rapidly becoming ubiquitous. Log in to your neighborhood watch program for a close-to-home example. (What street doesn't have a doorbell camera?) Public life is being monitored and passive data on our habits and lives is continually collected; any place that there is a camera, facial recognition technology is in play. The call by the ACM could be stronger. They urge the immediate suspension of use of facial recognition technology anywhere that is "known or reasonably foreseeable to be prejudicial to established human and legal rights." What is considered reasonable here? Is good intent enough to absolve misuse of these systems from blame, for instance?


DevOps best practices Q&A: Automated deployments at GitHub

Ultimately, we push code to production on our own GitHub cloud platform, on our data centers, utilizing features provided by the GitHub UI and API along the way. The deployment process can be initiated with ChatOps, a series of Hubot commands. They enable us to automate all sorts of workflows and have a pretty simple interface for people to engage with in order to roll out their changes. When folks have a change that they’d like to ship or deploy to github.com, they just need to run .deploy with a link to their pull request and the system will automatically deconstruct what’s within that link, using GitHub’s API for understanding important details such as the required CI checks, authorization, and authentication. Once the deployment has progressed through a series of stages—which we will talk about in more detail later—you’re able to merge your pull request in GitHub, and from there you can continue on with your day, continue making improvements, and shipping features. The system will know exactly how to deploy it, which servers are involved, and what systems to run. The person running the command has no need to know that it’s all happening. Before any changes are made, we run a series of authentication processes to ensure a user even has the right access to run these commands.


Exploring the prolific threats influencing the cyber landscape

Ransomware has quickly become a more lucrative business model in the past year, with cybercriminals taking online extortion to a new level by threatening to publicly release stolen data or sell it and name and shame victims on dedicated websites. The criminals behind the Maze, Sodinokibi (also known as REvil) and DoppelPaymer ransomware strains are the pioneers of this growing tactic, which is delivering bigger profits and resulting in a wave of copycat actors and new ransomware peddlers. Additionally, the infamous LockBit ransomware emerged earlier this year, which — in addition to copying the extortion tactic — has gained attention due to its self-spreading feature that quickly infects other computers on a corporate network. The motivations behind LockBit appear to be financial, too. CTI analysts have tracked cybercriminals behind it on Dark Web forums, where they are found to advertise regular updates and improvements to the ransomware, and actively recruit new members promising a portion of the ransom money. The success of these hack-and-leak extortion methods, especially against larger organizations, means they will likely proliferate for the remainder of 2020 and could foreshadow future hacking trends in 2021.


Unsecured Voice Transcripts Expose Health Data - Again

In a report issued Tuesday, security researchers at vpnMentor write that they discovered the exposed voice transcript records in early July and contacted Pfizer about the problem three times before the pharmaceutical company finally responded on Sept. 22 and fixed the issue on Sept. 23. Contained in the exposed records were personally identifiable information, including customers' full names, home addresses, email addresses, phone numbers and partial details of health and medical status, the report says. ...  However, upon further investigation, we found files and entries connected to various brands owned by Pfizer," including Lyrica, Chantix, Viagra and cancer treatments Ibrance and Aromasin, the report says. Eventually, the vpnMentor team concluded the exposed bucket most likely belonged to the company's U.S. Drug Safety Unit. "Once we had concluded our investigation, we reached out to Pfizer to present our findings. It took two months, but eventually, we received a reply from the company." In a statement provided to Information Security Media Group, the pharmaceutical company says: "Pfizer is aware that a small number of non-HIPAA data records on a vendor-operated system used for feedback on existing medicines were inadvertently publicly available. ..."



Quote for the day:

"A leader or a man of action in a crisis almost always acts subconsciously and then thinks of the reasons for his action." -- Jawaharlal Nehru

Daily Tech Digest - October 22, 2020

Cisco reports highlight widespread desire for data privacy and fears over remote work security

Cisco has released two studies examining how workers feel about the current state of play when it comes to remote work security and data privacy, finding that thousands around the world are increasingly concerned about how their employers are handling the massive societal changes that have occurred over the last six months. The "Consumer Privacy" report includes findings from a study of responses from more than 2,600 adults in 12 countries across Europe, Asia, and the Americas. The "Global Future of Secure Remote Work" report has insights gleaned from over 3,000 IT decision makers in the Americas, Japan, China, and Europe.  Both reports indicate that remote work is now a permanent part of the new normal, with 62% of respondents telling researchers that more than half of their workplace is working remotely since the onset of the coronavirus pandemic. Despite the massive shift to telecommuting, the vast majority of people who responded to the survey said they did not trust the digital tools they used for work.  Workers and consumers are particularly concerned about the privacy protections built into the tools they use for work and nearly half of all respondents said they do not feel that most businesses can effectively protect their data today.


How To Protect Yourself From Unexpectedly High AWS Bills

Set up billing alerts. If you are using AWS, even for a small task, please please please set up billing alerts. They are not required during setup, but if you are a non-enterprise user, I would consider this step mandatory as AWS will not alert you to dramatic increases in charges unless they bypass 15K which is already an incredible amount of money. Read the pricing table…carefully. If you are installing a new service, make sure to carefully read the pricing table. Amazon will sometimes set ridiculous defaults for container size which you might not see until the bill comes in. Do understand however that this might not be good enough, as bugs, loose API keys, and improper installations can do crazy things. Consider using another service. If you are a non-business individual user or small-business user, you might want to consider using another service. AWS is built for enterprise customers, and as such an enterprise wallet. Yes, it can be very cheap, but consider this: after my little mix up, I could have payed $150 a month over all of the years I used AWS and still come out ahead. Yes, AWS might be cheap at first, but one mistake can make it very expensive.


Learn from the hype surrounding kale – don’t rush Kubernetes

It requires more than just Kubernetes to achieve business outcomes, and hype surrounds the technology and term Kubernetes. A lot of false expectations exist too. Some companies may have heard on the IT grapevine that Google, AWS, Netflix, and Microsoft bet on Docker as a container format and Kubernetes as the orchestration engine – that the technology can scale and provide infrastructure at the same level as the big players. Simultaneously they may not be aware that the whole business model of such companies focuses on making infrastructure fluid and immediately available. Regular customers have a very different business model, with solutions based on trusted platforms by trusted partners that have solved virtualisation in the past, and those partners now have solutions to achieve the same outcomes with containerisation. Of course, Kubernetes technology also has its benefits. Businesses can become more efficient in their use of IT and achieve better results, faster, from development life cycles. They’ll produce better software via more automation and standardisation. Organisations can then use software to explore new business opportunities, experiment with the best ways to profit from ideas, and evolve accordingly.


Ubiq Rolls Out Encryption-as-a-Service Platform Aimed at Developers

Encryption has always been a fundamental part of computing — many of the early uses of computers were for cracking codes — and the technology has always been difficult to implement correctly. Despite the fact that there are many open source encryption efforts, adoption has remained low until the data-security capabilities could be integrated into technology. Even companies immersed in security and technology have had poor adoption rates. Google, for example, only had encryption implemented in half of its products in 2014, although the company claims that share is 95% today. On the development side, encryption errors continue to be prevalent among applications, irrespective of the programming language. Cryptographic errors are the second most common software vulnerability, occurring in 62% of applications, just behind information leakage, which occurs in 64%, according to application security firm Veracode. Encryption failures are also a significant factor in the severity of many data breaches. From the theft of unencrypted e-mails from Stratfor in 2012 to the failure to encrypt data in publicly accessible databases and Amazon S3 buckets, the failure of developers and operations workers to lock down every step in the data life cycle has led to reoccurring breaches.


Researchers open the door to new distribution methods for secret cryptographic keys

The researchers suggest a simple do-it-yourself lesson to help us better understand framed knots, those three-dimensional objects that can also be described as a surface. “Take a narrow strip of a paper and try to make a knot,” said first author Hugo Larocque, uOttawa alumnus and current PhD student at MIT. “The resulting object is referred to as a framed knot and has very interesting and important mathematical features.” The group tried to achieve the same result but within an optical beam, which presents a higher level of difficulty. After a few tries (and knots that looked more like knotted strings), the group came up with what they were looking for: a knotted ribbon structure that is quintessential to framed knots. “In order to add this ribbon, our group relied on beam-shaping techniques manipulating the vectorial nature of light,” explained Hugo Larocque. “By modifying the oscillation direction of the light field along an “unframed” optical knot, we were able to assign a frame to the latter by “gluing” together the lines traced out by these oscillating fields.” According to the researchers, structured light beams are being widely exploited for encoding and distributing information.


Learn what to test in a mobile application

Mobile devices present different issues than desktop computers and laptops. For example, tilting a mobile device could cause the app to render in landscape form and look odd -- this won't happen on a laptop. A user can lose network connection briefly, which causes state problems. And, in some cases, notifications from other applications can interrupt the system. Anyone on a mobile device could experience these issues during everyday use. These problems might be impossible to simulate with a test automation tool. Automated mobile test scripts don't offer enough value to justify the time necessary to write them for every possible condition. Testers can be more successful if they follow the 80/20 rule: Assume 80% of failed tests stem from 20% of test cases. When these test scripts break, something is likely broken with the application. Check for these kinds of issues when the team rewrites the UI, or brings in a new GUI library or component. Test the software as a system when it first comes together, and before major releases under challenging conditions. The first few times QA professionals field test an app -- i.e., take a mobile device on a long car ride, or swap between cellular data and Wi-Fi -- it might take a few days.


Translating lost languages using machine learning

Spearheaded by MIT Professor Regina Barzilay, the system relies on several principles grounded in insights from historical linguistics, such as the fact that languages generally only evolve in certain predictable ways. For instance, while a given language rarely adds or deletes an entire sound, certain sound substitutions are likely to occur. A word with a “p” in the parent language may change into a “b” in the descendant language, but changing to a “k” is less likely due to the significant pronunciation gap. By incorporating these and other linguistic constraints, Barzilay and MIT PhD student Jiaming Luo developed a decipherment algorithm that can handle the vast space of possible transformations and the scarcity of a guiding signal in the input. The algorithm learns to embed language sounds into a multidimensional space where differences in pronunciation are reflected in the distance between corresponding vectors. This design enables them to capture pertinent patterns of language change and express them as computational constraints. The resulting model can segment words in an ancient language and map them to counterparts in a related language. 


On the trail of the XMRig miner

Alongside well-known groups that make money from data theft and ransomware (for example, Maze, which is suspected of the recent attacks on SK Hynix and LG Electronics), many would-be attackers are attracted by the high-profile successes of cybercrime. In terms of technical capabilities, such amateurs lag far behind organized groups and therefore use publicly available ransomware, targeting ordinary users instead of the corporate sector. The outlays on such attacks are often quite small, so the miscreants have to resort to various stratagems to maximize the payout from each infected machine. For example, in August of this year, we noticed a rather curious infection method: on the victim’s machine, a Trojan (a common one detected by our solutions as Trojan.Win32.Generic) was run, which installed administration programs, added a new user, and opened RDP access to the computer. Next, the ransomware Trojan-Ransom.Win32.Crusis started on the same machine, followed by the loader of the XMRig miner, which then set about mining Monero cryptocurrency. As a result, the computer would already start earning money for the cybercriminals just as the user saw the ransom note.


5 steps to learn any programming language

Some people love learning new programming languages. Other people can't imagine having to learn even one. In this article, I'm going to show you how to think like a coder so that you can confidently learn any programming language you want. The truth is, once you've learned how to program, the language you use becomes less of a hurdle and more of a formality. In fact, that's just one of the many reasons educators say to teach kids to code early. Regardless of how simple their introductory language may be, the logic remains the same across everything else children (or adult learners) are likely to encounter later. With just a little programming experience, which you can gain from any one of several introductory articles here on Opensource.com, you can go on to learn any programming language in just a few days (sometimes less). Now, this isn't magic, and you do have to put some effort into it. And admittedly, it takes a lot longer than just a few days to learn every library available to a language or to learn the nuances of packaging your code for delivery. But getting started is easier than you might think, and the rest comes naturally with practice.


Articulating Leadership through Nemawashi and Collaborative Boards

Many meetings are just conversations with no conclusion and it seems that we cannot get over that. The point is that we need both: meetings and conversations, but we shouldn’t mix them. Nemawashi puts order here, separating conversations and meetings, similar to what Scrum does with the different events, where each one has a clear purpose. Meetings are formal, concrete, to the point; and there should be no surprises. It is the official acknowledgement of everything previously discussed and we just get together to have everyone on the same page. It is the formal moment when decisions are communicated and officially agreed on. Conversations instead take place ad-hoc, as often and as long as needed, involving only the necessary (and engaged) participants. This is where focused discussions take place. ... People are deciding on things anyway all the time, but on the wrong things. One clear symptom is too much effort on details and important points being missed or late, while everyone is "busy". Collaborative Boards is where teams and leaders meet. They articulate top-down challenges through bottom-up proposals, keeping them aligned towards the vision and focusing on what really matters.



Quote for the day:

"Failures only triumph if we don't have the courage to try again. -- Gordon Tredgold