{"id":1476,"date":"2018-04-26T08:45:34","date_gmt":"2018-04-26T12:45:34","guid":{"rendered":"https:\/\/solutionsreview.com\/security-information-event-management\/?p=1476"},"modified":"2018-04-26T09:09:35","modified_gmt":"2018-04-26T13:09:35","slug":"big-data-security-analytics-differ","status":"publish","type":"post","link":"https:\/\/solutionsreview.com\/security-information-event-management\/big-data-security-analytics-differ\/","title":{"rendered":"What are Big Data Security Analytics? How Do They Differ?"},"content":{"rendered":"

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In 2012, the <\/span>SANS Institute<\/span><\/a> issued a survey which found that 58% of enterprises were using some kind of log management solution and 37% were using SIEM. While seeming a positive discovery, the problem they found was that the solutions these respondents deployed were considerably \u201clast-gen.\u201d<\/span><\/p>\n
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In fact, they were so last gen they couldn\u2019t possibly keep up with the deluge of data coming into and leaving their enterprise every day. Enterprise networks, customer and vendor interactions, and applications can generate terabytes of data a month\u2014which can overwhelm information security systems. According to BI Survey, 62% of enterprises say that digital security threats have increased in the past year. Even with the assistance of human knowledge and intervention, traditional solutions may not be able to handle the sheer volume of cyber threats attacking your enterprise on a daily basis. <\/span><\/p>\n

The SANS Institute\u2019s suggested answer to this conundrum? Deploy a big data security analytics<\/a> solution. <\/span><\/p>\n

Much like traditional security analytics<\/a>, big data security analytics monitors and analyzes incoming and outgoing data for indicators of a potential security incident. It also collects, analyzes, and stores huge data caches in real time, allowing for data correlation from across all of your enterprise\u2019s endpoints (including the IoT). <\/span><\/p>\n

Going Into Depth with Big Data Security Analytics<\/b><\/h3>\n

You can think of big data security analytics solutions as a branch off of SIEM\u2019s tree. It incorporates many of the same tools that make up the heart of SIEM\u2014log and event management, behavioral analysis, and data correlation\u2014while adding some new capabilities such as operations management. \u00a0<\/span><\/p>\n

Yet big data security analytics is more than just the sum of its parts. It also offers powerful compliance reporting capabilities, including visualization options to help IT security professionals understand and respond to possible security incidents faster. Big data security analytics allows for greater scalability than traditional security analytics, as it can adapt to an ever-changing and ever-growing IT environment much more smoothly. <\/span><\/p>\n

These security analytics solutions also enhance the detection capabilities of your enterprise\u2019s cybersecurity platform. And this is more critical than you might think: prevention is a critical aspect of cybersecurity, but it can\u2019t extend infinitely nor can it catch every threat. Your best chance to mitigate the full blow of a data breach is to catch threats after they have infiltrated your network as quickly as possible. \u00a0\u00a0\u00a0<\/span><\/p>\n

What\u2019s Stopping Big Data Security Analytics Adoption?<\/b><\/h3>\n

In 2015, The SANS Institute conducted another study of big data security analytics, and found some surprising figures: <\/span><\/p>\n