Hewlett Packard Enterprise has acquired Niara, a startup that uses machine learning and big data analytics on enterprise packet streams and log streams to detect and protect customers from advanced cyberattacks that have penetrated perimeter defenses.
The financial terms of the deal were not disclosed.
Operating in the User and Entity Behavior Analytics (UEBA) market, Niara’s technology starts by automatically establishing baseline characteristics for all users and devices across the enterprise and then that may indicate a security threat, Keerti Melkote, senior vice president and general manager of HPE Aruba and cofounder of Aruba Networks, wrote in a blog post on Wednesday.
The time taken to investigate individual security incidents has been reduced from up to 25 hours using manual processes to less than a minute by using machine learning, Melkote added.
in May 2015, ahead of its corporate split into HPE, an enterprise-focused business and HP, a business focused on PCs and printers.
The strategy now is to integrate Niara’s behavioral analytics technology with Aruba’s , a role and device-based network access control platform, so as to to offer customers advanced threat detection and prevention for network security in wired and wireless environments, and internet of things (IoT) devices, Melkote wrote.
For Niara’s CEO Sriram Ramachandran and Vice President for Engineering Prasad Palkar and several other engineers it is a homecoming. They are part of the team that developed the core technologies in the ArubaOS operating system.
Niara technology addresses the need to monitor a device after it is on the internal network, following authentication by a network access control platform like ClearPass. Niara claims that it detects compromised users, systems or devices by aggregating and putting into context even subtle changes in typical IT access and usage.
Most networks today allow the traffic to flow freely between source and destination once devices are on the network, with internal controls, such as Access Control Lists, used to protect some types of traffic, while others flow freely, Melkote wrote.
“More importantly, none of this traffic is analyzed to detect advanced attacks that have penetrated perimeter security systems and actively seek out weaknesses to exploit on the interior network,” she added.