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IoT Data Security: SAS Integrates with McAfee Security Innovation Alliance

By Ken Briodagh October 19, 2017

According to a recent announcement, SAS has achieved technical integration of its SAS Cybersecurity analytics solution with the McAfee Data Exchange Layer (DXL), which extends to McAfee ePolicy Orchestrator (McAfee ePO) database and McAfee's partner ecosystem.

Through the McAfee DXL, SAS Cybersecurity delivers continuously updated risk scores for every network-connected asset. The solution derives risk from extensive composite scoring against multiple behavioral measures and the behavior of an asset's peer group.

“Given seemingly exponential increases in IoT devices, virtual machines and cloud services inside most enterprise networks, security organizations often lack the network knowledge and context necessary to prioritize risks and jump-start investigations,” said Stu Bradley, VP, Cybersecurity Solutions, SAS. “This integration not only provides much-needed network behavior context at scale; it also automates the triangulation of risk across end point, identity and threats using DXL data. The result is significant efficiency gains, enhancing detection while eliminating the need for extensive manual data manipulation.”

As an input to risk scoring, SAS Cybersecurity is designed to enrich data to enhance behavioral records across data dimensions. Customers with McAfee DXL-compatible solutions can opt to have the composite risk scores, enriched records and underlying contextual data published to their systems.

“The SAS Cybersecurity-McAfee DXL integration empowers security teams with an analytics-based view of their security risks, enabling them to efficiently prioritize efforts and resources, and accelerate incident investigation,” said DJ Long, head of the McAfee Security Innovation Alliance. “Organizations will benefit from the rich context the solution provides to help them improve their network defenses.”

This integration is a first step in SAS and McAfee's collaboration to deliver an enhanced, analytically driven approach to security operations that enables customers to move beyond indicators of compromise  to predictively identify and address indicators of attack.


Ken Briodagh is a writer and editor with more than a decade of experience under his belt. He is in love with technology and if he had his druthers would beta test everything from shoe phones to flying cars.

Edited by Ken Briodagh

Editorial Director

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