What Deep Learning Means for CyberSecurity


Danelle is CMO at Blue Hexagon. She has more than 15 years of experience bringing new technologies to market. Prior to Blue Hexagon, Danelle was VP Marketing at SafeBreach where she built the marketing team and defined the Breach and Attack Simulation category. Previously, she led strategy and marketing at Adallom, a cloud security company acquired by Microsoft. She was also Director, Security Solutions at Palo Alto Networks, driving growth in critical IT initiatives like virtualization, network segmentation and mobility.

Will Smith Was Wrong About the Robots


I, Robot was first released to theaters back in 2004. In it, the movie's filmmakers paint a fictional future (2035) where humanoid robots serve humanities needs. Our beloved Fresh Prince of Bel Air superstar is cast as a Chicago police detective named Del Spooner. Del hates robots with a deep skepticism after his experience with one that was unable to navigate a moral conundrum. Throughout the film, he condescends to these mechanical stewards for being unable to empathize and emote the way he believes only humans can.

You Can't Improve Cybersecurity By Throwing People At The Problem


It may seem counter-intuitive, but the answer probably isn't a surge in employee training or hiring of cybersecurity talent. That's because humans will always make errors, and humans can't cope with the scale and stealth of today's cyberattacks. To best protect information systems, including data, applications, networks, and mobile devices, look to more automation and artificial intelligence-based software to give the defense-in-depth required to reduce risk and stop attacks. That's one of the key conclusions of a new report conducted by Oracle, "Security in the Age of AI," released in May. The report draws on a survey of 775 respondents based in the US, including 341 CISOs, CSOs, and other CXOs at firms with at least $100 million in annual revenue; 110 federal or state government policy influencers; and 324 technology-engaged workers in non-managerial roles.

Artificial Intelligence & Cybersecurity


Both AI and cybersecurity are broad and poorly understood fields. This book helps give you an overview of the various technologies that make up AI, where they have come from, and what AI has evolved into today. Cybersecurity is another field that has evolved over the last few decades. Dive into the world of cybersecurity and then learn how AI is being applied to the battle. When you're done reading this book, you will be spouting terms like cognitive computing, machine learning, and deep learning, and know how they apply to the cybersecurity space.

Emerj Report - Artificial Intelligence in Banking: Compliance, Fraud and Cybersecurity Lead in Investment and Current Traction


Risk-related AI applications (risk management, lending, compliance, fraud and cybersecurity) account for 72% of the total $2.8 billion in funds raised for AI vendor companies in banking, according to the latest report by Emerj Artificial Intelligence Research. Compliance and fraud-related applications make up 32% of the total AI vendor landscape in banking, but banks report these applications as a mere 19% of their current AI initiatives. Bankers today see AI as a risk-reduction technology. Their AI initiatives are likely to yield negative ROI in part because they hold naive views about AI's integration and data requirements. Banks are eager to automate compliance specifically, especially given recent data privacy laws such as GDPR.

Home » Security Boulevard (Original) » News » Vectra Raises $100M More for Cybersecurity AI Vectra Raises $100M More for Cybersecurity AI – Tech Check News


Home » Security Boulevard (Original) » News » Vectra Raises $100M More for Cybersecurity AI Vectra has garnered another $100 million in funding to accelerate development of a threat detection and response system running in the cloud that makes extensive use of artificial intelligence (AI). This latest round of funding brings the total investment in Vectra to $200 million. Company CEO Hitesh Sheth said Vectra's Cognito platform applies machine learning algorithms to network metadata captured across the extended enterprise.

Deep Reinforcement Learning for Cyber Security Artificial Intelligence

The scale of Internet-connected systems has increased considerably, and these systems are being exposed to cyber attacks more than ever. The complexity and dynamics of cyber attacks require protecting mechanisms to be responsive, adaptive, and large-scale. Machine learning, or more specifically deep reinforcement learning (DRL), methods have been proposed widely to address these issues. By incorporating deep learning into traditional RL, DRL is highly capable of solving complex, dynamic, and especially high-dimensional cyber defense problems. This paper presents a survey of DRL approaches developed for cyber security. We touch on different vital aspects, including DRL-based security methods for cyber-physical systems, autonomous intrusion detection techniques, and multi-agent DRL-based game theory simulations for defense strategies against cyber attacks. Extensive discussions and future research directions on DRL-based cyber security are also given. We expect that this comprehensive review provides the foundations for and facilitates future studies on exploring the potential of emerging DRL to cope with increasingly complex cyber security problems.

How Machine Learning Helps Improve Cybersecurity


Cyberattacks have increased on an unprecedented scale. The main reason obviously is our increasing dependence on computing devices (computers, smartphones etc) and the internet for our day-to-day needs. The technology that we depend on today has interconnectedness as one of its salient features. This, plus our habit of using unsecured networks and devices (like, for example, public Wi-Fi) for convenience's sake, too has proven to be the cause for an unprecedented increase in cyberattacks. Of the various technologies that we use today to prevent cyberattacks and to ensure cybersecurity, machine learning deserves special mention.

Is AI fundamental to the future of cybersecurity?


Every time you connect to the internet from a computer, tablet or smartphone, there is a growing risk of cyberattack. If the threat is aimed at your workplace, then the entire organization around you could be vulnerable as well and, too often, the result is a major data breach. A well-run company, regardless of its size or global reach, must eventually acknowledge that cybersecurity requires a significant investment. But what tools and processes return the most bang for your buck? A growing number of experts believe that new technology based on machine learning and artificial intelligence are where the smart money lies when it comes to computer, network and data security.

How Could Artificial Intelligence Be Essential To Cybersecurity? - The Organization for World Peace


According to a survey conducted by Senseon as part of a research project on Small and Medium-sized Enterprises (SMEs), 81 percent of participants believe that AI would improve the future of cybersecurity while only 3 percent disagree. The remaining 16 percent stated that they were uncertain. Due to how innovative AI has become over the past few years, it is reasonable that the survey generated such a result. The question is, how does the aspect of machine intelligence provide benefits to the company and what objectives and initiatives must the developer, analyst and decision maker establish to enable those types of AI to benefit the security of the cyber age? The Microsoft Vice-President of Cybersecurity Solutions Group, Ann Johnson, told the RTE News during a meeting in Dublin that she sees about six and a half trillion cyber threats that Microsoft receive every day.