Network Threat Protection Powered by Deep LearningBlue Hexagon has built the industry’s FIRST real-time deep learning platform for network threat protection. Built by a team with decades of machine learning and deep learning expertise, the Blue Hexagon proprietary neural network architecture is designed for speed and efficacy. Blue Hexagon detects known and unknown threats in less than a second at nearly 100% efficacy and 10G wire speed performance. The platform works out-of-the- box and requires no baselining. Near real-time prevention can be enabled via orchestrated enforcement to endpoints, firewalls and web proxies, to block malicious traffic at the network or application.
A New Approach to Cybersecurity
- Threat detection must be at the speed malware is unleashed – in subseconds, not days, hours or minutes.
- Harnessing deep learning will deliver the speed and efficacy needed. Deep learning is the most advanced subfield of machine learning and AI, where artificial neural networks learn from large amounts of data. Neural networks trained with the massive threat data that exists today, can intelligently learn and make decisions on whether traffic is malicious.
- The best place to do this is closest to the source of attack – the network – to stop the threat as soon as possible and to prevent lateral movement deeper in the network.
Blue Hexagon Case StudyThe Blue Hexagon deep learning models inspect the complete network flow—payloads, headers, malicious URLs, and C2 communications—and is able to deliver threat inference in less than a second. Threat prevention can then be enabled on firewalls, endpoint devices, and network proxies. Case Study
Real-time Deep Learning for Network Threat Protection
Your existing security solutions will benefit from Blue Hexagons' real-time deep learning platform.