Biometrics: Authentication Silver Bullet or Skeleton Key?
"We do need to understand how we're going to use them and what the problems are," he says. "We need to mitigate against those problems, the same as we'd do with any other system." Biometric systems become stronger in context, and that's where big data can help. Location data or knowing a pattern of when someone uses biometric authentication can help the systems make a better judgment on whether to open access. "You need to make sure the biometric system you are using isn't a single factor because it's essentially useless," Jamieson says. "It needs to be coupled with something else." That risk can be judged according to the situation. In some cases, a partial fingerprint alone may be fine. But for other transactions with higher risks, the authentication can be escalated, requiring or calling on other information.
A Roadmap to the Programmable World
Today's development methods, languages, and tools-or at least those that are in widespread use-are poorly suited to the emergence of millions of programmable things in our surroundings. We highlight issues and technical challenges that deserve deeper study beyond those IoT topics that receive the most attention today. Because this article is forwardlooking, our roadmap is somewhat subjective. Our viewpoints stem from our own projects and collaborations in the IoT domain2-5, as well as from our experience predicting and partaking in mobile and web computing's evolution over the past 20 years. For instance, the emergence of virtual machines in mobile phones in the late 1990s wasn't a dramatic technical achievement per se. However, it opened up mobile phones for the vast masses of developers, creating today's multibillion-dollar mobile-app industry.
How Women Will Disrupt Cybersecurity
The element of emotional connection in facilitating a strong security culture will be key going forward as organizations shift their focus from technologies to internal employees in an effort to combat the massive amounts of breaches taking place on a daily basis. And as highlighted in the Harvard Business Review, “the higher up you go in an organization, the less important your technical skills become and the more your interpersonal skills matter”. So what is the solution for creating the norm of emotional connectedness in the workplace and enhancing the security culture? ... With the research clearly demonstrating that emotional connection is essential in fostering a strong security culture, and women outperforming men in the measurement of emotional intelligence, we can conclude that the creation of more strategic security communication roles in leadership positions will enhance organizational security culture, create a platform for women to excel in the space
We Still Know Very Little About How AI Thinks
It is important to understand how these systems work, as they are already being applied to industries including medicine, cars, finance, and recruitment: areas that have fundamental impacts on our lives. To give this massive power to something we don’t understand could be a foolhardy exercise in trust. This is, of course, providing that the AI is honest, and does not suffer from the lapses in truth and perception that humans do. At the heart of the problem with trying to understand the machines is a tension. If we could predict them perfectly, it would rob AI of the autonomous intelligence that characterizes it. We must remember that we don’t know how humans make these decisions either; consciousness remains a mystery, and the world remains an interesting place because of it.
How chatbots can settle an insurance claim in 3 seconds
As chatbots become more commonplace, they are making their way into behind-the-scenes claims processes as well. Tableau’s prototype chat software, Eviza, has a voice interface so users can drill into its signature data visualizations simply by asking questions out loud. Clara Analytics offers askClara, a chatbot the company bills as a “24/7 personal assistant to the claims handler.” Like customer-facing chatbots, it can answer routine questions about a given set of claims. Insurance companies are sitting on a trove of the one thing AI requires to be successful — data. And AI technologies like machine learning have the ability to make that data actionable. Machine learning can look at data in a number of different ways. It can rank information, putting what it thinks you are looking for at the top of a list; classify information like images; make recommendations; and associate something with a numerical value.
Are data lakes the answer to privacy regulations, competition in healthcare?
“Arguably, for the first time, we finally have the deep, rich, clinical data that we’ve needed to do analytics with, [and] big data processing power, the Internet of Things and all of the rich sources of new data that we can learn new things about how to treat patients better. And then the final component is … the financial incentives are finally aligned,” Cramer stated. What he finds most exciting about all the changes is by having the ability to analyze data it enables organizations and practitioners to measure the quality and outcomes of their work by removing inefficiencies that were prevalent in the past and providing value. With all the conversations over the years on theCUBE, when it comes to digital transformation there is a pattern emerging, according to Furrier: how to run an organization, how to take care of the users and giving the customer or patient a great experience.
Information Architecture. Basics for Designers.
Information architecture aims at organizing content so that users would easily adjust to the functionality of the product and could find everything they need without big effort. The content structure depends on various factors. First of all, IA experts consider the specifics of the target audience needs because IA puts user satisfaction as a priority. Also, the structure depends on the type of the product and the offers companies have. For example, if we compare a retail website and a blog, we’ll see two absolutely different structures both efficient for accomplishing certain objectives. Information architecture has become the fundamental study in many spheres including design and software development.
Five DevOps principles to apply to enterprise architecture
At the most basic level, DevOps means that software developers and IT operations engineers (also known as system administrators) work together on software production. By facilitating collaboration between the programmers who write software and the administrators who manage it in production, implementing strong DevOps principles eliminates communication barriers that could lead to software design mishaps, bugs going unnoticed until they are too costly to fix and other software delivery issues. An important practice that DevOps promotes is continuous delivery of software. Under the continuous delivery model, small changes to a software program are designed, written, tested and placed into production at a constant pace. For continuous delivery to work, however, all members of the organization who play a role in software production need to be in constant communication.
MeitY Requires Government Departments to Have a CISO
Some security experts, however, say there aren't enough qualified officials to take over the role of CISO in each department. "A senior person in government doesn't necessarily guarantee the right skills required for a CISO," says J Prasanna, director at the Cyber Security & Privacy Foundation Pte Ltd. "At the senior level, you may have someone who commands respect, but he should also understand security process." Given the criticality of the role, government departments should consider hiring outside experts to serve as CISO, rather than selecting someone already on the staff, as MeitY is requiring, says Sivakumar Krishnan, former head of IT at M Power Microfinance. Shashidhar adds that each department "should appoint industry experts and empower them as CISOs in the short term. ..."
Introducing Socks Shop: A Cloud Native Reference Application
This project began as a small demo application for DockerCon to show off some new services developed by Weave Works. As a company which focuses on building products and tooling for microservice and container based applications, they needed an actual application on which to demo their services. In two weeks, we built an “aggressively microserviced” application, throwing in a variety of technologies, programming languages, and datastores. After its initial run, we saw benefits in keeping the project alive. It turned out to be quite useful, both as a testbed for container and microservice focused tools, as well as reference application for what a Cloud Native system should look like. Over the course of the next few months, we worked to convert this demo application to be production ready.
Quote for the day:
"The minute you settle for less than you deserve, you get even less than you settled for." -- Maureen Dowd
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