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Scale out to speed up Mean Time to Detection and Mean Time to Respond

Scale out to speed up Mean Time to Detection and Mean Time to Respond

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Technology not only drives our world, but it increasingly becomes more vital to business success. As businesses turn more and more to new technologies to improve performance and give them an edge over their competition, they also increase their cyber attack surfaces and threat exposure. Mobile BYOD initiatives. Cloud expansion. The proliferation of IoT. The deployment of a never-ending assortment of emerging technologies. These combine to give security experts the near-impossible task of successfully monitoring for threats across all the varied and highly diverse aspects of their enterprise environments. 

That’s why you continue to see headline news of major data breaches like the September 26, 2017 Sears and Delta Airlines credit card data breach that went undiscovered for almost three weeks as the tally of affected customers grew to 100,000. Even worse was the Saks Fifth Avenue and Lord & Taylor breach where attackers started stealing customers’ credit card information on May 2017, but weren’t detected until March 2018. During that time attackers stole nearly 5 million credit card and debit card numbers, with at least 125,000 of those records going up for sale immediately on the dark web. Those are only a few examples, but 87% of the data compromises that occurred last year went undiscovered for months or more.1 Unfortunately, the damage and costs associated with such breaches continue to rise the longer they take to be discovered. 

Security Incident and Event Management (SIEM) systems have been crucial in giving security teams needed visibility and intelligence to speed up discovery, but as the mountain of data to be analyzed has continued to grow bigger and bigger, organizations have tried to keep up by simply throwing more SIEMs into the mix. But in doing so, they have not only complicated their security management efforts, but they’ve lost the benefit of centralizing event collection and correlation that SIEMs deliver. That’s a major reason why the hints and clues of suspicious activity get lost among all the data noise, enabling breaches to continue to go undiscovered for weeks, months, and even years. 

Making scalable real-time distributed event correlation a key part of your security strategy is the answer to speeding up threat detection and response—and keeping your name off the headlines. That’s what you get with ArcSight Enterprise Security Manager (ESM). With the ability to scale out and up as fast and big as you need, it uses proven cluster technology to deploy armies of data correlators and aggregators across multiple hosts, while bubbling up events of interest into a centralized single pane of glass. And it does it without the complexity and expense of other solutions. Plus, the real-time distributed correlation engine in ESM is the only solution capable of scaling up to 100,000 events per second. 

To learn more about how ESM 7.0 can modernize and reduce the complexity of your SIEM infrastructure, as well as improve your mean time to detection (MTD) and your mean time to response (MTR), please watch the following video on ArcSight Distributed Correlation in ESM.

See how ArcSight ESM 7.0 allows SOCs to gain the agility to expand their cyber security footprint and respond faster to evolving threats at massive scale—up to 100,000 correlated events per second, per cluster—as well as solve a wider set of security use cases. 

1 "2018 Data Breach Investigations Report." Verizon, April 2018. 

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