Think about a world where retail banks could send cross-border payments directly to a counterparty without navigating through intermediaries. Instead, you could use a service dedicated to carrying out “Know Your Customer” processes on behalf of the financial services community. The same principle could apply for other transactions. Maybe a single, global fund transfer network is in our future, where any kind of transaction could flow autonomously while sharing only the minimum information necessary, maintaining the privacy of all other personal financial data. ... The technology now exists to massively increase computational power for a range of specific problems, such as simulation and machine learning, by trying all possibilities at once and linking events together. It’s more like the physical phenomena of nature versus the on-or-off switches of ordinary computer calculations. As a result, for instance, an investment bank may no longer have to choose between accuracy and speed when deciding how to allocate collateral across multiple trading desks. It could also give banks a more accurate way to determine how much capital to keep on hand to meet regulations.
Clearly some adjustment is needed on an unknown number of Windows machines. And therein lies the big problem with the Windows ecosystem: Even though we have had Windows for years, it’s still a very vast and messy ecosystem of hardware vendors, multiple drivers, and software vendors that often build their solutions on something undocumented. Microsoft over the years has clamped down on this “wild west” approach and mandated certain developer requirements. It’s one of the main reasons I strongly recommend that if you want to be in the Insider program or install feature releases on the very first day they are released, that you use Windows Defender as your antivirus, and not something from a third party. While Microsoft will often follow up with a fix for a patch problem, typically — unlike this issue — it is not released in the same fashion as the original update. Case in point: in November, Microsoft released an update that impacted Kerberos authentication and ticket renewal issues. Later last month, on Nov. 19, it released an out-of-band update for the issue. The update was not released to the Windows update release channel, nor on the Windows Software Update Servicing release channel; instead IT administrators had to manually seek it out and download it or insert it into their WSUS servers.
Compliance and auditing: Auditors need the data in a meaningful and contextual manner from their perspective. DB audit logs are suitable for DBA teams but not for auditors. The ability to generate critical alerts in case of a security breach are basic requirements of any large scale software. Audit logs can be used for this purpose. You must be able to answer a variety of questions such as who accessed the data, what was the earlier state of the data, what was modified when it was updated, and are the internal users abusing their privileges, etc. It’s important to note that since audit trails help identify infiltrators, they promote deterrence among "insiders." People who know their actions are scrutinized are less likely to access unauthorized databases or tamper with specific data. All kinds of industries - from finance and energy to foodservice and public works - need to analyze data access and produce detailed reports regularly to various government agencies. Consider the Health Insurance Portability and Accountability Act (HIPAA) regulations. HIPAA requires that healthcare providers deliver audit trails about anyone and everyone who touches any data in their records.
Skillate can work as both as a standalone ATS that takes care of the end-to-end recruitment needs of your organization or as an intelligent system that integrates with your existing ATS to make your recruitment easy, fast, and transparent. And how it does this is by banking on cutting-edge technology and the power of AI to integrate with the existing platforms such as traditional ATSs like Workday, SuccessFactors, etc. to solve some real pain points of the industry. However, for AI to work in a complex industry like recruitment, we need to consider the human element involved. Take for instance the words Skillate and Skillate.com — both these words refer to the same company but will be treated as different words by a machine. Moreover, every day new companies and institute names come up, and thus it is almost impossible to keep the software’s vocabulary updated. To illustrate further, consider the following two statements: 'Currently working as a Data Scientist at <Amazon>’ and, ‘Worked on a project for the client Amazon.’ In the first statement, “Amazon” will be tagged as a company as the statement is about working in the organization. But in the latter “Amazon” should be considered as a normal word and not as a company. Hence the same word can have different meanings based on its usage.
The first step to achieving cyber resilience is to start with a fundamental paradigm shift: Expect to be breached, and expect it to happen sooner than later. You are not "too small to be of interest," what you do is not "irrelevant for an attacker," it doesn't matter that there is a "bigger fish in the pond to go after." Your business is interconnected to all the others; it will happen to you. Embrace the shift. Step away from a one-size-fits-all cybersecurity approach. Ask yourself: What parts of the business and which processes are generating substantial value? Which must continue working, even when suffering an attack, to stay in business? Make plans to provide adequate protection — but also for how to stay operational if the digital assets in your critical processes become unavailable. Know your most important assets, and share this information among stakeholders. If your security admin discovers a vulnerability on a server with IP address 18.104.22.168 but doesn't know the value of that asset within your business processes, how can IT security properly communicate the threat? Would a department head fully understand the implications of a remote code execution (RCE) attack on that system?
The foundation of Zoracles Protocol that differentiates the project from other decentralized finance projects is its use of cutting-edge privacy technologies centered around zero-knowledge proofs. Those familiar with these privacy-preserving techniques were most likely introduced to these concepts by the team at Electric Coin Company who are responsible for the zero-knowledge proofs developed for the privacy cryptocurrency Zcash. Zoracles will build Zk-Snarks that are activated when pulling consumer credit scores yet hiding their values as they are brought onto the blockchain. This is accomplished with a verification proof derived from the ZoKrates toolbox. Keeping the data confidential is critical to ensure confidence from users to have their data available on-chain. It can be compared to using https (SSL) to transmit credit card data that allowed eCommerce to flourish.A very interesting long-term goal of Zora.cc is to eventually use credit score verification to prove identity. The implications are enormous for the usefulness of their protocol if it can become the market leader in decentralized identity. The team is focused on building the underlying API infrastructure as well as a front-end user experience. If executed successfully, it is very similar to the product offering of Twilio. The “Platform as a Service” could go well with Zoracles “Snarks as a Service.” One should watch this project closely.
One of the more puzzling misconceptions that I hear pertains to the topic of refactoring. I consult on a lot of legacy rescue efforts that will need to involve refactoring, and people in and around those efforts tend to think of “refactor” as “massive cleanup effort.” I suspect this is one of those conflations that happens subconsciously. If you actually asked some of these folks whether “refactor” and “massive cleanup effort” were synonyms, they would say no, but they never conceive of the terms in any other way during their day to day activities. Let’s be clear. Here is the actual definition of refactoring, per wikipedia. Code refactoring is the process of restructuring existing computer code – changing the factoring – without changing its external behavior. Significantly, this definition mentions nothing about the scope of the effort. Refactoring is changing the code without changing the application’s behavior. This means the following would be examples of refactoring, provided they changed nothing about the way the system interacted with external forces: Renaming variables in a single method; Adding whitespace to a class for readability; Eliminating dead code; Deleting code that has been commented out; and Breaking a large method apart into a few smaller ones.
"Autonomous robots took on more expansive roles in stores and warehouses during the pandemic," says Rowland, "which is expected to gain momentum in 2021. Data-collecting robots shared real-time inventory updates and accurate product location data with mobile shopping apps, online order pickers and curbside pickup services along with in-store shoppers and employees." That's especially key in large retail environments, with hundreds of thousands of items, where the ability to pinpoint products is a major productivity booster. Walmart recently cut its contract with robotic shelf scanning company Bossa Nova, but Rowland believes the future is bright for the technology category. Heretofore, automation solutions have largely been task-specific. That could be a thing of the past, according to Rowland. "Autonomous robots can easily handle different duties, often referred to as 'payloads,' which are programmed to address varying requirements, including but not limited to, inventory management, hazard detection, security checks, surface disinfectants, etc. In the future, retailers will have increased options for mixing/matching automated workflows to meet specific operational needs." Remember running out of toilet paper? So do retailers and manufacturers, and it was a major wake up call.
When we are in a coding competition where the clock is ticking, all we care about is efficiency. We will be using variable names such as a, b, c, or index names such as j, k, l. Putting less attention to naming can save us a lot of time, and we will probably throw the code right after the upload passed all the test sets. These are called the “throw-away code”. These codes are short and as the name suggests — they won’t be kept for too long. In a real-life software engineering project, however, our code will likely be reused and modified, and that person may be someone other than ourselves, or ourselves but after 6 months of working on a different module. ... Readability is so important that sometimes we even sacrifice efficiency for it. We will probably choose the less readable but extremely efficient lines of code when working on projects that aim to be optimized within several CPU cycles and limited memory space, such as the control system running on a microprocessor. However, in many of the real-life scenarios we care much less about that millisecond difference on a modern computer. But writing more readable code will cause much less trouble for our teammates.
Quote for the day:
"Leadership does not always wear the harness of compromise." -- Woodrow Wilson