Gurucul: Network Security Augmented With Predictive Analytics

The recent network intrusion attack on the large enterprise company, Sony, is proof that even with multiple levels of security; a network can still have vulnerabilities that can lead to breaches and attacks. To add to this, CIOs have to scrounge for resources and strain their budgets to get a cyber security system in place. Such systems may protect the network from external threats but when the threat is internal, finding the culprit can prove to be a challenge. Adding to these woes, CIOs lose network visibility when they migrate their network resources to the cloud. With loads of data to sift and secure, CIOs are hard pressed to find an effective security solution capable of handling such issues, prevent internal attacks, and deliver timely alerts.

“With our experience in enterprise-level cyber security, we know that internal threats can be managed by controlling user identity and access,” says Saryu Nayyar, CEO of Gurucul. Gurucul is disrupting the industry with its behavior based machine learning and predictive analytics. Using identity to monitor for threats, the firm provides Actionable Risk Intelligence to protect against targeted and under-the-radar attacks. “Our solutions are intelligent and have real-time threat-detection behavior that is programmed to flag risky and anomalous network activity,” says Saryu. This threat analysis system keeps track of over 250 attributes associated with user ID to narrow down potential threats to the network. The algorithm employed by the firm is augmented by the use of big data, is self-learning while it continuously monitors network activity and builds a behavior baseline to find anomalies— real-time. The predictive nature of the solution can alert organizations early for preventative damage control.