Armorblox's co-founder and head of engineering, Arjun Sambamoorthy, explains that Google is a ripe target for exploitation due to the free and democratized nature of many of its services. Adopted by so many legitimate users, Google's open APIs, extensible integrations, and developer-friendly tools have also been co-opted by cybercriminals looking to defraud organizations and individuals. Specifically, attackers are using Google's own services to sneak past binary security filters that look for traffic based on keywords or URLs. ... cybercriminals spoof an organization's security administration team with an email telling the recipient that they've failed to receive some vital messages because of a storage quota issue. A link in the email asks the user to verify their information in order to resume email delivery. The link in the email leads to a phony login page hosted on Firebase, Google's mobile platform for creating apps, hosting files and images, and serving up user-generated content. This link goes through one redirection before landing on the Firebase page, confusing any security product that tries to follow the URL to its final location. As it's hosted by Google, the parent URL of the page will escape the notice of most security filters.
Next-gen analytics have helped to shift perception and enable the business to accelerate the use of data, according to panelist Barb Latulippe, Sr. Director Enterprise Data at Edward Life Sciences, who emphasized the trend toward self-service in enterprise data management. The days of the business going to IT are gone—a data marketplace provides a better user experience. Coupled with an effort to increase data literacy throughout the enterprise, such data democratization empowers users to access the data they need themselves, thanks to a common data language. This trend was echoed by panelist Katie Meyers, senior vice president at Charles Schwab responsible for data sales and service technologies. A data leader for 25 years, Katie focused on the role cloud plays in enabling new data-driven capabilities. Katie emphasized that we’re living in a world where data grows faster than our ability to manage the infrastructure. By activating data science and artificial intelligence (AI), Charles Schwab can leverage automation and machine learning to enable both the technical and business sides of the organization to more effectively access and use data.
Code that provides the structure and resources to allow a developer to meet their objectives with a high degree of comfort and efficiency is indicative of a good developer experience. Code that is hard to understand, hard to use, fails to meet expectations and creates frustration for the developer is typical of a bad developer experience. Technology that offers a good developer experience allows a programmer to get up and running quickly with minimal frustration. A bad developer experience—one that is a neverending battle trying to figure out what the code is supposed to do and then actually getting it to work—costs time, money, and, in some cases, can increase developer turnover. When working with a company’s code is torturous enough, a talented developer who has the skills to work anywhere will do take one of their many other opportunities and leave. There is only so much friction users will tolerate. While providing a good developer experience is known to be essential as one gets closer to the user of a given software, many times, it gets overlooked at the architectural design level. However, this oversight is changing. Given the enormous demand for more software at faster rates of delivery, architects are paying attention.
"The typical Internet service provider is primarily focused on delivering reliable, predictable bandwidth to their customers," Crisler says. "They value connectivity and reliability above everything else. As such, if they need to make a trade-off decision between security and uptime, they will focus on uptime." To be fair, demand for speed and reliable connections was crushing many home ISPs in the early days of the pandemic. For some, it remains a serious strain. "In the early weeks of the pandemic, when people started using their residential connections at once, ISPs were faced with major outages as bandwidth oversubscription and increased botnet traffic created serious bottlenecks for people working at home," says Bogdan Botezatu, director of threat research and reporting at Bitdefender. ISPs' often aging and inadequately protected home hardware presents many security vulnerabilities as well. "Many home users rent network hardware from their ISP. These devices are exposed directly to the Internet but often lack basic security controls. For example, they rarely if ever receive updates and often leave services like Telnet open," says Art Sturdevant, VP of technical operations at Internet device search engine Censys. "And on devices that can be configured using a Web page, we often see self-signed certificates, a lack of TLS for login pages, and default credentials in use."
Data as a service (DaaS), a scalable model where many analysts can access a shared data resource, is commonplace. However, privacy assurance about that data has not kept pace. Data breaches occur by the thousands each year, and insider threats to privacy are commonplace. De-identification of data can often be reversed and has little in the way of a principled security model. Data synthesis techniques can only model correlations across data attributes for unrealistically low-dimensional schemas. What is required to address the unique data privacy challenges that government agencies face is a privacy-focused service that protects data while retaining its utility to analysts: private data as a service (PDaaS). PDaaS can sit atop DaaS to protect subject privacy while retaining data utility to analysts. Some of the most compelling work to advance PDaaS can be found with projects funded by the Defense Advanced Research Projects Agency’s Brandeis Program, ... According to DARPA, “[t]he vision of the Brandeis program is to break the tension between: (a) maintaining privacy and (b) being able to tap into the huge value of data. Rather than having to balance between them, Brandeis aims to build a third option – enabling safe and predictable sharing of data in which privacy is preserved.”
Today’s high-growth, high-scale organizations must have well-rounded tech teams in place -- teams that are engineered for success and longevity. However, the process of hiring for, training and building those teams requires careful planning. Tech leaders must ask themselves a series of questions throughout the process: Are we solving the right problem? Do we have the right people to solve these problems? Are we coaching and empowering our people to solve all aspects of the problem? Are we solving the problem the right way? Are we rewarding excellence? Is 1+1 at least adding up to 2 if not 3? ... When thinking of problems to solve for the customers -- don’t constrain yourself by the current resources. A poor path is to first think of solutions based on resource limitations and then find the problems that fit those solutions. An even worse path is to lose track of the problems and simply start implementing solutions because “someone” asked for it. Instead, insist on understanding the actual problems/pain points. Development teams who understand the problems often come back with alternate, and better, solutions than the initial proposed ones.
“Apstra wants organizations to reliably deploy and operate SONiC with simplicity, which is achieved through validated automation...Apstra wants to abstract the switch OS complexity to present a consistent operational model across all switch OS options, including SONiC,” Zilakakis said. “Apstra wants to provide organizations with another enterprise switching solution to enable flexibility when making architecture and procurement decisions.” The company’s core Apstra Operating System (AOS), which supports SONIC-based network environments, was built from the ground up to support IBN. Once running it keeps a real-time repository of configuration, telemetry and validation information to constantly ensure the network is doing what the customer wants it to do. AOS includes automation features to provide consistent network and security policies for workloads across physical and virtual infrastructures. It also includes intent-based analytics to perform regular network checks to safeguard configurations. AOS is hardware agnostic and integrated to work with products from Cisco, Arista, Dell, Juniper, Microsoft and Nvidia/Cumulus.
As the European Union finalises new digital-era laws, its legacy of world-leading privacy and data protection is at stake. Starting next week, the European Commission will kick off the introduction of landmark legislative proposals on data governance, digital market competition, and artificial intelligence. The discussions happening now and over the next few months have implications for the future of the General Data Protection Regulation and the rights this flagship law protects. With Google already (predictably) meddling in the debate, it is imperative that regulators understand what the pitfalls are and how to avoid them. ... The first new legislation out of the gate will be the Data Governance Act, which the European Commission is set to publish on November 24. According to Commissioner Thierry Breton, the new Data Strategy aims to ensure the EU “wins the battle of non-personal data” after losing the “race on personal data”. We strongly object to that narrative. While countries like the US have fostered the growth of privacy-invasive data harvesting business models that have led to repeated data breaches and scandals such as Cambridge Analytica, the EU stood against the tide, adopting strong data protection rules that put people before profits.
We want everything to be faster, and that’s what this Data Fabric approach gets for you. In the past, we’ve seen edge solutions deployed, but you weren’t processing a whole lot at the edge. You were pushing along all the data back to a central, core location -- and then doing something with that data. But we don’t have the time to do that anymore. Unless you can change the laws of physics -- last time I checked, they haven’t done that yet -- we’re bound by the speed of light for these networks. And so we need to keep as much data and systems as we can out locally at the edge. Yet we need to still take some of that information back to one central location so we can understand what’s happening across all the different locations. We still want to make the rearview reporting better globally for our business, as well as allow for more global model management. ... Typically, we see a lot of data silos still out there today with customers – and they’re getting worse. By worse, I mean they’re now all over the place between multiple cloud providers. I may use some of these cloud storage bucket systems from cloud vendor A, but I may use somebody else’s SQL databases from cloud vendor B, and those may end up having their own access methodologies and their own software development kits (SDKs).
"Most of the world's knowledge is imperfect in some way or another. But there's an enormous amount of knowledge that, say, a bright 10-year-old can just pick up for free, and we should have RDF be able to do that. Some examples are, first of all, Wikipedia, which says so much about how the world works. And if you have the kind of brain that a human does, you can read it and learn a lot from it. If you're a deep learning system, you can't get anything out of that at all, or hardly anything. Wikipedia is the stuff that's on the front of the house. On the back of the house are things like the semantic web that label web pages for other machines to use. There's all kinds of knowledge there, too. It's also being left on the floor by current approaches. The kinds of computers that we are dreaming of that can help us to, for example, put together medical literature or develop new technologies are going to have to be able to read that stuff. We're going to have to get to AI systems that can use the collective human knowledge that's expressed in language form and not just as a spreadsheet in order to really advance, in order to make the most sophisticated systems."
Quote for the day:
"To have long term success as a coach or in any position of leadership, you have to be obsessed in some way." -- Pat Riley