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Applications of Machine Learning in Cyber Security


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1 Department of Computer Science, RVCE, Bengaluru, India
     

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Machine learning techniques have been applied in many areas of science due to their unique properties like adaptability, scalability, and potential to rapidly adjust to new and unknown challenges. Cyber security is a fast-growing field demanding a great deal of attention because of remarkable progresses in social networks, cloud and web technologies, online banking, mobile environment, smart grid, etc. Diverse machine learning methods have been successfully deployed to address such wide-ranging problems in computer security. This paper discusses and highlights different applications of machine learning in cyber security. This study covers phishing detection, network intrusion detection, testing security properties of protocols, authentication with keystroke dynamics, cryptography, human interaction proofs, spam detection in social network, smart meter energy consumption profiling, and issues in security of machine learning techniques itself.


Keywords

Security, Machine Learning, Survey.
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  • Applications of Machine Learning in Cyber Security

Abstract Views: 199  |  PDF Views: 3

Authors

B. N. Deepak
Department of Computer Science, RVCE, Bengaluru, India
H. Pavithra
Department of Computer Science, RVCE, Bengaluru, India

Abstract


Machine learning techniques have been applied in many areas of science due to their unique properties like adaptability, scalability, and potential to rapidly adjust to new and unknown challenges. Cyber security is a fast-growing field demanding a great deal of attention because of remarkable progresses in social networks, cloud and web technologies, online banking, mobile environment, smart grid, etc. Diverse machine learning methods have been successfully deployed to address such wide-ranging problems in computer security. This paper discusses and highlights different applications of machine learning in cyber security. This study covers phishing detection, network intrusion detection, testing security properties of protocols, authentication with keystroke dynamics, cryptography, human interaction proofs, spam detection in social network, smart meter energy consumption profiling, and issues in security of machine learning techniques itself.


Keywords


Security, Machine Learning, Survey.

References