Machine Learning in Cyber Security

In recent years, attackers have been developing more sophisticated ways to attack systems. Thus, recognizing these attacks is getting more complicated in time. Most of the time, network administrators were not capable of recognizing these attacks effectively or response quickly.
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Therefore, there is a lot of software has been developed to support the human race in order to be able to manage and protect their systems effectively. Initially, these software has been developed to handle some operations like mathematical calculations which seem very complex for the human being. And then we need more. Next step was extending the ability of software using artificial intelligence and machine learning techniques. As technology advances, a huge amount of data is being produced to be processed every day and every hour. Finally, the concept of “Big Data” was born and people began to need a more intelligent system for processing and getting make sense of these data. For this purpose, there are a lot of algorithms have been developed until today. These algorithms are used for many research area such as; image processing, speech recognition, biomedical area, and of course cyber security domain.

Besides all of these, basically, the main purpose of Machine Learning techniques is providing decision mechanism to software as people do. Cybersecurity domain is one of the most important research area worked on. The Centre for Strategic and International Studies in 2014 estimated annual costs to the global economy caused by cyber crimes was between $375 billion and $575 billion. Although sources differ, the average cost of a data breach incident to large companies is over $3 million. Researchers have developed some intelligent systems for cyber security domain with the purpose of reducing this cost.