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Leveraging self-learning analytics to thwart cyber threats: FICO

Nurdianah Md Nur | Feb. 27, 2015
By doing so, organisations will be able to identify threats in near real-time and receive less false-positive alerts.

In an effort to enable organisations to better combat fraud, FICO recently launched its Cyber Security Analytics solution. 

The solution leverages decades of research in streaming analytics technologies and new advances in self-learning models to detect emerging and evolving cyber threats in real time, said the predictive analytics and decision management software firm in a press release.

By utilising self-learning analytics and anomaly detection techniques that monitor activity across multiple network assets and real-time data streams, the solution is able to identify threats as they occur. This is in contrast to traditional signature-based threat detection solutions that take months to discover data theft threats, during which affected companies would have experienced significant data losses due to malware, botnets and other data theft attempts.

FICO added that the Cyber Security Analytics solution could also recognise new "normal" activities, thus minimising false-positive alerts.

"Current cyber security solutions leave a wide gap in coverage," said Doug Clare, vice president for cyber security solutions at FICO. "It's like having a burglar alarm that doesn't go off until after the burglar's done his work, left the premises and crossed the county line. FICO will fill that gap, using our arsenal of streaming analytic technologies to detect and stop malicious network activity right at the point of inception."

FICO Cyber Security Analytics can be used independently, or in conjunction with existing cyber security infrastructures, signature-based threat detection systems, and security information and event management(SIEM) tools.


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