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Machine Learning in Cybersecurity

Machine Learning in Cybersecurity

by Igor Mikhaylov2017-06-19

Cybersecurity industry has always been under constant strain from malicious programs and cyber-criminals. With increasing integration of software services and hardware, into every aspect of our lives, the task of keeping data secure has now become more tedious. The arsenal of tools that cyber criminals today have at their disposal has raised several concerns for security companies.

Modern threats that profit from organizations often shy away from traditional security mechanisms, but the use of machine learning algorithms is activated in order to fill the gap between proactivity and detection. Machine learning algorithms are better at applying models on large data without tiring or complaining of repetitive tasks. At the same time, the human component is responsible for the accuracy of the machine learning model. Machine learning algorithms range from genetic algorithms to neural networks, but their ultimate goal is to adapt to variations of baseline behavior.
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