There is growing concern within companies and governments that we might be losing control over cybersecurity. The rapid changes in how we use technology to communicate and the increased number of connected devices mean that points of weakness are increasing. Because the pace of change has been so rapid, security hasn’t adapted fast enough and hackers are taking full advantage.
But while the rest of the industry gets up to speed, a number of forward thinking cybersecurity startups are harnessing the power of artificial intelligence to tackle this threat in a manner which promises to be quicker and more effective than traditional approaches. We decided to pick out 10 of the most exciting cyber security startups using artificial intelligence. You can see the profiles below.
You can also search for 100s of other Cyber Security innovators on our database.
Darktrace is inspired by the self-learning intelligence of the human immune system; it’s Enterprise Immune System technology iteratively learns a pattern of life for every network, device and individual user, correlating this information in order to spot subtle deviations that indicate in-progress threats. The system is powered by machine learning and mathematics developed at the University of Cambridge. Some of the world’s largest corporations rely on Darktrace’s self-learning appliance in sectors including energy and utilities, financial services, telecommunications, healthcare, manufacturing, retail and transportation.
Jask says that the tsunami of logs, SIEM events, and other indicators that security analysts face every day produces a never ending flood of unknowns which forces these analysts to spend their valuable time sorting through indicators in the endless hunt for real threats. Jask is aiming to solve this problem by developing a new artificial intelligence based approach that can highlight the real actual attacks.
Deep Instinct says it is the first company to apply deep learning to cybersecurity. Leveraging deep learning’s predictive capabilities, Deep Instinct’s on-device, proactive solution protects against zero-day threats and APT attacks with industry leading accuracy. Deep Instinct is designed to safeguards the enterprise’s endpoints and/or any mobile devices against any threat, on any infrastructure, whether or not connected to the network or to the Internet.
harvest.ai aims to replicate the processes of top security researchers: searching for changes in behavior of users, key business systems and applications caused by targeted cyber attacks. harvest.ai has applied AI-based algorithms to learn the business value of critical documents across an organization, and offer what is describes as an industry-first ability to detect and stop data breaches from targeted attacks and insider threat before data is stolen.
PatternEx’s Threat Prediction Platform is designed to create “virtual security analysts” that mimic the intuition of human security analysts in real time and at scale. The platform reportedly detects ten times more threats with five times fewer false positives compared with approaches based on Machine Learning-Anomaly Detection technology. Using a new technology called “Active Contextual ModelingTM” or ACM, the product synthesizes analyst intuition into predictive models. These models, when deployed across global customers, can reportedly learn from each other and achieve a network effect in detecting attack patterns.
Vectura Networks’ platform is designed to instantly identify cyber attacks while they are happening as well as what the attacker is doing. Vectra automatically prioritizes attacks that pose the greatest business risk, enabling organizations to quickly make decisions on where to focus their time and resources. The company says that platform uses next-generation compute architecture and combines data analytics and machine learning to detect attacks on every device, application and operating system. The platform is completely automated and is designed to empower IT organizations that have neither the budget nor the depth of security expertise.
StatusToday protects company’s from insider threat and data breaches using a patent pending Artificial Intelligence that understands Human Behavior. Using Machine Learning techniques and Organizational Human Behavior it detects possible malicious behavior, no matter how big or small. The system doesn’t intercept data or intrude in the network which might decrease the performance, but insead uses a passive monitoring approach that sits behind the scene. The company says its advanced Artificial Intelligence adapts to the organization’s behavior and self-learns to detect the slightest abnormality in activities, identifying suspicious activity right when it happens in real time.
Cyberlytic provides security intelligence software that prioritises the workload of security teams and reduces response times from cyber attacks to seconds. Cyberlytic was founded on the belief that security intelligence should enable security teams to be more efficient and reduce the demand on human operators. Through research originally completed for the UK Ministry of Defence, Cyberlytic is the originator and owner of intellectual property relating to real-time risk assessment and prioritisation of cyber-attacks. Its system enables businesses and government departments to focus their attention on responding to the most high-risk cyber attacks.
Leveraging Artificial Intelligence, Neokami’s CyberVault enables companies to discover, secure and govern sensitive data in the cloud, on premise, or across their physical assets. The company says its technology has already been used successfully across many Fortune 500 Enterprises.
Fortscale’s user behavior analytics (UEBA) solution combines expertise from the Israeli Defense Force’s elite security unit, big data analytics and advanced machine learning to deliver what the company describes as the holy grail of enterprise security: The ability to rapidly detect and eliminate insider threats. From rogue employees to hackers with stolen credentials, Fortscale is designed to automatically and dynamically identify anomalous behaviors and prioritizes the highest-risk activities within any application, anywhere in the enterprise network.