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A Survey of Data Mining and Machine Learning Methods for Cyber Security Intrusion Detection - 2015

A Survey Of Data Mining And Machine Learning Methods For Cyber Security Intrusion Detection

Research Area:  Internet of Things

Abstract:

This survey paper describes a focused literature survey of machine learning (ML) and data mining (DM) methods for cyber analytics in support of intrusion detection. Short tutorial descriptions of each ML/DM method are provided. Based on the number of citations or the relevance of an emerging method, papers representing each method were identified, read, and summarized. Because data are so important in ML/DM approaches, some well-known cyber data sets used in ML/DM are described. The complexity of ML/DM algorithms is addressed, discussion of challenges for using ML/DM for cyber security is presented, and some recommendations on when to use a given method are provided.

Keywords:  

Author(s) Name:  Anna L. Buczak; Erhan Guven

Journal name:   IEEE Communications Surveys & Tutorials

Conferrence name:  

Publisher name:  IEEE

DOI:  10.1109/COMST.2015.2494502

Volume Information:  Volume: 18, Issue: 2, Secondquarter 2016,Page(s): 1153 - 1176