Security remains a top news item this year. We see increased activities to address security in enterprises and the product marketplace in 2015. I offer my predictions on the top trends in security analytics for 2016. They are:
#1 Data science as a de-facto tool for cyber security
Cyber security traditionally has been relying on signature-based and rule-based approaches to detect bad activities. The use of data science has emerged only in recent years. This technology trend parallels that of fraud detection in credit or banking industry. Starting from rule- and signature-based systems, the financial industry moved to risk-based systems using analytics to catch evermore sophisticated fraud activities. The cyber security domain is no different. In 2015 we’ve seen increased activities in data scientist hiring and a broader interest in the use of machine learning and data analytics among enterprises security offices.
#2 Increased Marketing Noise in Security Analytics
In 2015, new and old security product vendors are marketing data analytics. But this also creates confusion in the market as there is neither a standard for data analytics tools, nor benchmark data sets to compare analytics procedures. If you are in the marketplace, do your due diligence in understanding the security products under the hood.
#3 Spark!
In its very short history, the open-source Apache Spark has become mainstream, especially with Databricks, IBM, and Cloudera supporting it in 2015. Its ability to stream and analyze data in close to real time will drive adoption in many verticals and applications. Security analytics will be no exception. However, Spark is not a panacea to all security data analytics, as not all problems can be addressed by data parallelization. Security systems that are designed to leverage stateless data parallelization and to accommodate stateful event tracking will enjoy an advantage.
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