Advanced machine learning platform preemptively identifies attack pathways
At RSA Conference 2017, illusive networks announced the illusive Deception Management System (DMS), a machine learning platform that preemptively identifies attack pathways and autonomously creates best-fit deceptions based on continuous real-time environment analysis.
“Attack vectors change with lightning speed leaving little to no time to wait for human intervention,” said Ofer Israeli, CEO, illusive networks. “As cybercriminals launch increasingly sophisticated attacks, it’s more imperative than ever to continuously create and plant deceptions in real time that are impossible for attackers to discern from real network assets. Using advanced machine learning, illusive DMS takes deception cybersecurity to the next level by automatically customizing and continually adapting deceptions with zero disruption to business — but total disruption to cyber attackers.”
illusive DMS manages the creation, diversification, placement, and dynamic tailoring of deceptions, building and evolving a deceptive layer across every part of the network. By continually adapting and revising deceptions and ensuring that deceptions are always contextual to the location where they are planted, illusive DMS improves attack detection by creating a credible environment from the attackers’ perspective.
illusive DMS offers a plug-and-play solution with automatic network discovery, immediate network analysis, instant deception-creation, and one-click deployment.
- Automated discovery and analysis of attack vectors
- Visibility into key attack risk vectors
- Crafted tailored deceptions, that are best-fit for each environment
- “One-click” deception policy deployment
- Continuous monitoring with ever-changing adaptive protection.
- Identify and neutralize attack vectors
- Zero maintenance, plug & play automated solution reduces cost and overhead
- Agentless technology that is fast to deploy
- Scales to the largest and rapidly changing environments
- Increases attack detection probability with best-fit deception-deployment.