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Machine Learning in Cybersecurity: A Review - 2019

Machine Learning In Cybersecurity: A Review

Research Area:  Machine Learning

Abstract:

Machine learning technology has become mainstream in a large number of domains, and cybersecurity applications of machine learning techniques are plenty. Examples include malware analysis, especially for zero-day malware detection, threat analysis, anomaly based intrusion detection of prevalent attacks on critical infrastructures, and many others. Due to the ineffectiveness of signature-based methods in detecting zero day attacks or even slight variants of known attacks, machine learning-based detection is being used by researchers in many cybersecurity products. In this review, we discuss several areas of cybersecurity where machine learning is used as a tool. We also provide a few glimpses of adversarial attacks on machine learning algorithms to manipulate training and test data of classifiers, to render such tools ineffective.

Keywords:  

Author(s) Name:  Anand Handa,Ashu Sharma,Sandeep K. Shukla

Journal name:  WIREs Data Mining and Knowledge Discovery

Conferrence name:  

Publisher name:  Wiley

DOI:  10.1002/widm.1306

Volume Information:  Volume 9, Issue 4