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​Deloitte, Cray launch supercomputer-driven threat analytics service

​Deloitte, Cray launch supercomputer-driven threat analytics service

Subscription-based service powered by the Cray Urika-GX system

Deloitte Advisory Cyber Risk Services and Cray have launched what they claim to be the first commercially available supercomputing threat analytics service.

Cyber Reconnaissance and Analytics is a subscription-based service powered by the Cray Urika-GX system, an analytics platform that combines supercomputing technologies with a software framework for big data analytics.

It’s designed to help companies discover, understand and take action against cyber adversaries, the companies said.

The US Department of Defense is using this service to provide remediation teams with intelligence reports that provide detailed, actionable information on potential threat vectors and identify specific flows, network locations, times and events.

Deborah Golden, federal cyber risk services leader for Deloitte Advisory, said instead of reviewing every component of an agency’s internal enterprise, the service is trying to show what the adversary sees in order to give an organisation a true risk profile.

“This includes the ability to effectively prioritise internal budgets and resources, and facilitate a realistic approach towards assessing network defence effectiveness.” Golden said.

By changing the perspective, increasing the volume of data, and applying advanced analytics, an organisation can have a clearer view of true risk, exposure, and malicious activity.

This vantage point provides potential weaknesses, vulnerabilities and threat vectors that may highlight risks involving anomalous activities, the companies said.

“Defending against sophisticated and evolving threats is an analytics problem squarely at the crossroads of big data and supercomputing," said Barry Bolding, chief strategy officer at Cray.

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Tags CraySupercomputerthreat managementDeloitte Advisory Cyber Risk ServicesCray Urika-GXCyber Reconnaissance and Analytics

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