In this episode of the ARCHITECHT AI and Robot Show, Demisto co-founder Rishi Bhargava explains how the company's technology works by learning how its customers resolve problems, and then helping automate remediation when similar problems arise in the future. Among other things, Bhargava talks about why the company takes a simple approach to machine learning; the value of looking at security as a human-centric problem; how bots not only automate actions, but aggregate immense amounts of activity data; and why the biggest things companies can do today is bring order to their security operations, automate what can be automated, and prioritize what's truly important to protect. Keep reading for highlights from the podcast interviews with Bhargava, and scroll to the bottom (or click here) for links to listen to the podcast pretty much everywhere else you might want to. But you'll want to listen to the whole thing to get a better sense of how Demisto's platform works and where we can take some simple steps that could have outsized benefits for enterprise security, as well as Bhargava's thoughts on issues such as consumer products and cybersecurity insurance.
Most security professionals spend a lot more time looking for the source of problem than they do fixing it. To cut down on that time, Demisto this week added a Demisto Insights module to a Demisto Enterprise security operations platform that provides access to machine learning algorithms that can now suggest the best method available for resolving a security issue. Demisto Insights is not only designed to make it possible for IT security professionals to spend less time diagnosing problems; Bhargava says it provides the added side benefit of making less experienced security personnel staffing a security operations center (SOC) become more effective sooner. As IT security technologies become imbued with advanced analytics and automation technologies based on machine learning algorithms, it's not clear how much longer a chronic shortage of IT security staff will persist.
With the help of the Kaggle data science community, the Department of Homeland Security (DHS) is hosting an online competition to build machine learning-powered tools that can augment agents, ideally making the entire system simultaneously more accurate and efficient. Kaggle, acquired by Google earlier this year, regularly hosts online competitions where data scientists compete for money by developing novel approaches to complex machine learning problems. The TSA is making its data set of images available to competitors so they can train on images of people carrying weapons. To mitigate this, the TSA put special effort into creating the data set of images that will ultimately be used to train the detectors.
Newswire) Research and Markets has announced the addition of the "Innovations in IoT-, Machine Learning-, and Artificial Intelligence-based Security Solutions" report to their offering. This edition of Network Security TOE provides a snapshot of the emerging security solutions based on artificial intelligence, machine learning, and other new technologies that help companies mitigate threats and defend against modern attacks. TechVision Information & Communication Technology cluster provides global industry analysis, technology competitive analysis, and insights into game-changing technologies in the wireless communication and computing space. These innovations have profound impact on a range of business functions for computing, communications, business intelligence, data processing, information security, workflow automation, quality of service (QoS) measurements, simulations, customer relationship management, knowledge management functions and many more.
With the help of the Kaggle data science community, the Department of Homeland Security (DHS) is hosting an online competition to build machine learning-powered tools that can augment agents, ideally making the entire system simultaneously more accurate and efficient. Kaggle, acquired by Google earlier this year, regularly hosts online competitions where data scientists compete for money by developing novel approaches to complex machine learning problems. The TSA is making its data set of images available to competitors so they can train on images of people carrying weapons. Thankfully, Google, Facebook and others are heavily investing in lighter versions of machine learning frameworks, optimized to run locally, at the edge (without internet).
Softbank has upped its investment in security firm Cybereason, as the focus on artificial intelligence (AI) continues, writes Banking Technology's sister publication Telecoms.com. The additional $100 million investment from Softbank now makes the firm the largest investor, with CRV, Spark Capital, and Lockheed Martin also involved. An AI-driven security solution can work continuously and more efficiently than a human, but also use machine learning to access content on the internet to learn about potential attacks it could face. This isn't about replacing humans because an AI is cheaper, it is a job which simply cannot be done by the security team; with the number of access points, the task is too much to ask for.
Anusha is a software engineer on the WSO2 real-time analytics team, where he researches and analyzes various methods of video processing to support solutions, such as surveillance and monitoring. With traffic monitoring, video processing can be used to detect vehicles, monitor vehicle density, and track vehicles by reading their license plates. Common applications are to use video feeds from traffic cameras to identify speeding vehicles or to observe the traffic flow speed on highways to, for example, predict travel time or dynamically calculate toll values. The sources may include video streaming devices, such as CCTV cameras, traffic cameras, online video feeds, or any other video source.
Recent weeks have brought controversy over electronic billboards in restaurants and shopping precincts that utilize advanced facial recognition techniques to not only provide personalized advertisements but also measure and record the consumer and their response, ostensibly to enable retailers to provide more targeted marketing and services. They believe this will have "big implications for our projects in retail and security, including allowing CCTV cameras to detect potential criminals and fugitives by marking them as suspicious if they express emotions like fear, hatred, or nervousness." While the increasing use of facial recognition in crime prevention and detection in public spaces is controversial, its' good arguably outweighs the lack of privacy. Yet facial recognition tech for marketing and retail purposes is less compelling, especially as we don't know how advanced the AI could get in the future.
According to their website: "We leverage the incredible progress recently made in computer vision thanks to a type of AI known as deep learning…Our AI Surveillance (AIS) platform can spot weapons, people concealing their identity, fire, and intruders after-hours, all at a fraction of the cost of a human-only monitoring solution." Up until now, Deep Science AI was only offering their security monitoring service in the United States to a small set of customers. In addition to providing businesses with an affordable solution to monitor their company's premises for real-time threats, Deep Science AI also has a team of analysts who monitor their customers' security camera feeds 24 hours a day, 7 days a week. By keeping their security solution affordable and flexible (there's no hardware purchase required; just the monthly camera monitoring fee), Deep Science AI is showing that a big field like deep learning has the potential to bring about big changes to the small business landscape.
If RoboCop has a gun in his thigh, this robotic security car from Singapore has a drone that it can send after intruders. It has 3D LIDAR sensors and GPS, along with other instruments that it uses to spot unattended bags and to differentiate between employees and intruders. It can differentiate the people security personnel mark as employees from unknown individuals. O-R3, he says, can complement human security personnel hired for jobs that require a higher level of skills.