Harnessing Machine Learning, Data Analytics, and Computer-Aided Testing for Cyber Security Applications
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While media reports frequently highlight the exciting aspects of the cyber security field, many cyber security tasks are quite tedious and repetitive. At the same time, however, strong pattern recognition, deductive reasoning, and inference skills are required, as well as a high degree of situational awareness. As a direct consequence, the field of cyber security is replete with potential opportunities to apply data analytics, machine learning, computer aided testing, and other advanced approaches to reduce the frustration of cyber security operators by easing key challenges. In fact, given a typical range of cyber attack surfaces, leveraging these machine-enhanced analysis and decision approaches in conjunction with a robust defense-in-depth posture is a crucial step towards achieving sustained, predictable performance across typical cyber security tasks and promotes cyber resilience. This paper will both outline details for a near-term research effort and explore a variety of key opportunities to exploit these approaches with the objective of raising awareness, providing initial guidance to aid potential adopters, and developing effective strategies to incorporate them into existing cyber security constructs.
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