Malware and Anomaly Detection Using Machine Learning and Deep Learning Methods

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Author(s): Valliammal Narayan (Avinashilingam Institute for Home Science and Higher Education for Women, India)and Barani Shaju (Avinashilingam Institute for Home Science and Higher Education for Women, India)
Copyright: 2022
Pages: 28
Source title: Research Anthology on Machine Learning Techniques, Methods, and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-6684-6291-1.ch010

Keywords: Artificial Intelligence / Engineering Science Reference / Knowledge Management and Library Science / Machine Learning

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Abstract

This chapter aims to discuss applications of machine learning in cyber security and explore how machine learning algorithms help to fight cyber-attacks. Cyber-attacks are wide and varied in multiple forms. The key benefit of machine learning algorithms is that it can deep dive and analyze system behavior and identify anomalies which do not correlate with expected behavior. Algorithms can be trained to observe multiple data sets and strategize payload beforehand in detection of malware analysis.

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Malware and Anomaly Detection Using Machine Learning and Deep Learning Methods

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