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Big Data and Security: Analytics as a Way to Improve IT Security
On a near daily basis we learn of data breaches where sensitive data has been compromised. “We are being overwhelmed by all the opportunities for attack,” says Art Coviello, Executive Chairman of RSA. Existing intrusion protection tools have been found to have limitations. But one technique that’s increasingly being suggested as a means for combatting attacks and to better securing on-line information is Big Data analytics.
A report from Cloud Security Alliance (CSA) Big Data Working Group describes the evolution of intrusion-detection security tools through three generations:
1st Generation: Intrusion Detection Systems – This generation of tools provided a second layer of defense once a server had been breached. This is a reactive approach that grew out of the belief that a 100 percent protective defense that could stop all intruders was not possible.
2nd Generation: Security information and event management (SIEM) – These tools aggregate all alert and alarm information collected from all systems in an enterprise and presented as actionable information to security analysts.
3rd Generation: Big Data analytics – While we’re not there yet, the idea is that Big Data can be used to sift through all data access and security event information and more accurately identify problems. Long-term historical data could also be used forensic analysis.
Dan Mitchell, product manager of data sciences for RSA The Security Division of EMC, said that “in the past, it’s always been us who’s been behind the game, trying to catch up with the attackers’ techniques. I think data science gives us the opportunity to get ahead of the attackers and have them be behind for a change.”
