Ransomware has had a major impact on how IT organizations think about protecting data. Now Druva, a provider of data protection and management software delivered as a service, wants to make it a lot simpler for IT organizations to identify data that is being targeted by ransomware before things completely spin out of their control. Today, Druva announced it is employing machine learning algorithms across its cloud service to continually assess the unique attributes of changes being made across various file types to make it easier to identify abnormal deletions, unusual modifications and updates, and an atypical number or large number of file creations. Druva CEO Jaspreet Singh says all these events are symptomatic of events associated with ransomware attacks. In the event of such an attack, Singh says, Druva can now also pinpoint the last safest snapshot for an organization to recover. Machine learning algorithms, Singh says, are only part of an overall approach to data protection that is rapidly evolving.

IBM Watson has a new job: Cybersecurity specialist. At the RSA Conference…IBM announced the availability of Watson for Cyber Security, with the aim of assisting cybersecurity professionals with threat assessment and mitigation…The company said it is the industry's first augmented intelligence technology with the ability to power cognitive security operations centers (SOCs). But what need does Watson fill here?

Today on In Case You Missed It: We get a much closer look at electrical discharge phenomena courtesy of a video filmed from the International Space Station. Called "Transient Luminous Events", the phenomena are notoriously hard to study as they occur 25-60 miles above thunderstorms. Even satellites have had little luck at capturing images of the upper-atmosphere lighting. However, viewing angles were less of a challenge for ESA astronaut Andreas Mogensen who was able to a highly-sensitive camera to snag video footage of 245 flashes of blue lightning while he was stationed on the ISS in 2015. Meanwhile, Agility Robotics introduced us to Cassie, a bipedal robot that can walk smoothly over pavement, grass and lose soil without issue. The three-month old bot walks much the same way as humans do, which makes it more adept at handling various types of terrain, and has a similar three-planed hip joint movement which makes it more steerable than earlier bipedal models.

Tysons Corner, Va.--February 14, 2017--BluVector, the leader in applying supervised machine learning to detect and respond to advanced security threats at digital speed, announced its expanded operations following the completion from the recent LLR acquisition. BluVector is now positioned for rapid growth powered by new executive hires, new product enhancements and expansion into key verticals such as financial, retail and healthcare. BluVector's supervised machine learning technology allows organizations to monitor high bandwidth, globally dispersed networks for advanced threats that are consistently evading traditional security infrastructures. The technology is based on over a decade of research that inspects millions of packets per second of North-South and East-West traffic to predict, in real-time, if software and application files pose a threat to an enterprise on-premise and in the cloud. Evaluating vast collections of both benign and malicious software and applying machine learning science, BluVector is uncovering the markers and mutations of today's modern threats.

Recent breakthroughs in machine learning and artificial intelligence mean AI-enabled technologies are gaining traction. The billion-dollar cybersecurity industry is no exception, as vendors begin to scale and automate their processes intelligently – all while locked into the early stages of a security arms race with professional hackers. A recent report from analyst firm ABI Research estimates that machine learning in cybersecurity will enormously bolster spending in big data, intelligence and analytics, reaching as much as $96 billion (£71.9 billion) by 2021. Vendors are likely to find buyers in large enterprises, and more than likely, across industries that are especially prone to attack: think government and defence, banking, and across the technology sector. At the moment, ABI's report says, User and Entity Behavioural Analytics – using machine learning for threat detection by analysing data at scale – is the driving force. "Using static machine learning models to detect previously unknown malware is the only use case I'm aware of that offers clear evidence of effective results," says cybersecurity analyst at 451 Research, Adrian Sanabria.

Recently, the Urban Institute called for the creation of "neighborhood-level early warning and response systems that can help city leaders and community advocates get ahead of (neighborhood) changes." Open data and open-source analytics allows community stakeholders to mine data for actionable intelligence like never before. The objective of this research is to take a first step in exploring the feasibility of forecasting neighborhood change using longitudinal census data in 29 Legacy Cities (Figure 2). The first section provides some motivation for the analysis. Section 3 provides results and the final section concludes with a discussion of community-oriented neighborhood change forecasting systems. Neighborhoods change because people and capital are mobile and when new neighborhood demand emerges, incumbent residents rightfully worry about displacement.

If humankind wants to survive the rise of artificial intelligence, we need to embrace the machines and become a melded cyborg organism, projected Elon Musk, CEO of SpaceX and Tesla, on Monday. Enhancing our minds is Musk's answer to finding the meaning of life. Musk has been a proponent of the human-A.I. mind-meld for a while: He's floated the idea of neural lace, a hypothetical computer processing net that can be injected into your brain to enhance intelligence. He seems pretty serious about enhancing humans to survive an A.I. takeover. "When I was a kid, I was wondering, 'What's the meaning of life -- you know, why are we here, what's it all about?' And I came to the conclusion that what really matters is trying to understand the right questions to ask. And the more that we can increase the scope and scale of human consciousness, the better we are able to ask these questions."

While there has been plenty of conversation over the possibility that robots will replace humans in the work force, Tesla and SpaceX CEO Elon Musk believes the threat is existential for people. The billionaire warned humans will soon have to learn to communicate with artificial intelligence or face becoming obsolete. "Over time I think we will probably see a closer merger of biological intelligence and digital intelligence," Musk said while speaking at the World Government Summit in Dubai, according to a report from CNBC. Musk, who was at the event to announce the launch of Tesla in the United Arab Emirates, suggested that a merger between humans and machines will be necessary for the species going forward, lest it find itself made irrelevant. The founder and CEO of Tesla and SpaceX pointed to the processing power of a computer compared to that of a person's brain, explaining that computers can communicate at "a trillion bits per second" while humans do so at about 10 bits per second.

Two senators said Monday that they're launching a bipartisan effort to help to speed up the deployment of self-driving cars on the nation's roads. It's the first major congressional attempt to address the advent of the vehicles. Sens. John Thune (R-S.D.), the chairman of the Senate Commerce, Science and Transportation Committee, and Gary Peters (D-Mich.) said they're exploring legislation that "clears hurdles and advances innovation in self-driving vehicle technology." The senators' counterparts in the House are also gearing up to address the new technology, with a hearing scheduled for Tuesday. Automakers cite federal requirements that all vehicles must have steering wheels and brake pedals as examples of regulations that presume there will be a human driver and might inhibit the introduction of self-driving cars.

Signature and behavioural based anti-malware are no match for next generation adversaries who use mutating hashes, sophisticated obfuscation mechanisms, self-propagating malware and intelligent malware components, according to the findings of a new report. The report, published by the Institute for Critical Infrastructure Technology (ICIT), said that it is "no longer enough" to detect and respond to cyber-attacks and that artificial intelligence (AI) is necessary to offer the predictive quality that can give organisations a "much-needed edge on their more sophisticated, less burdened, and more evasive adversaries". The research paper, titled Signature Based Malware Detection is Dead, said that the average data breach costs $158 per stolen record, and is often undetected for 229 days. In some organisations, especially ones containing critical infrastructure, feature layers of incompatible technologies are "Frankensteined" together in a haphazard attempt at nominally meeting security standards. "Any unused technology in every layer exponentially increases cyber-security noise and could result in exploitable security vulnerabilities. Meanwhile, C-level executives suffer from security solution fatigue as the result of incessant product evaluations, investments, and failures," the paper said.