Hewlett Packard Enterprise has expanded its security-first, AI-powered networking portfolio with the introduction of behavioural analytics-based network detection and response (NDR) capabilities, delivered by HPE Aruba Networking Central.
What’s new
The new NDR solution leverages telemetry from HPE Aruba Networking Central’s data lake to train and deploy AI models to monitor and detect unusual activity in vulnerable IoT devices that play an increasingly important role in supporting mission-critical business processes.
As the opportunity grows for IoT to provide organisations with data to train and activate Generative AI models, so too does the critical need to detect changes in network traffic patterns, connection status or dynamic device attributes that are indicative of a successful compromise.
“Enterprises are increasingly realising that unsecured IoT devices in the network present an observability blind spot in their security solutions. Those devices can be exploited for initiating larger network attacks, and thus are also one of the largest contributors to a growing attack surface,” said Jon Green, chief technology and security officer for HPE Aruba Networking.
He opines that as security teams increasingly rely on the network to deliver zero trust security solutions, HPE Aruba Networking will provide the ability to leverage a single access control policy for application resources, on-prem or off-prem, that customers can adopt to reduce overlapping and potentially confusing controls.
Securing IoT
“The proliferation of IoT devices is presenting enterprises with significant security challenges that are complex and costly to tackle while posing major risks to business operations. The new network and detection response capabilities are part of HPE Aruba Networking’s commitment to delivering a security-first, AI-powered networking approach to our customers, enabling them to critically strengthen IoT security in their network,” said Nick Harders, APJ SASE Director, HPE Aruba Networking.
“Companies need AI-powered behavioural network detection and response, universal security policies, and edge-to-cloud enforcement to protect users, devices, and applications at scale – a key consideration as AI assets throughout the enterprise increasingly become attack targets,” said Maribel Lopez, founder and industry analyst at Lopez Research.
