The Era of Advanced Machine Learning and Deep Learning Algorithms for Malware Detection

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Author(s): Kwok Tai Chui (Hong Kong Metropolitan University, Hong Kong), Patricia Ordóñez de Pablos (The University of Oviedo, Spain), Miltiadis D. Lytras (Deree College — The American College of Greece, Greece), Ryan Wen Liu (Wuhan University of Technology, China)and Chien-wen Shen (National Central University, Taiwan)
Copyright: 2022
Pages: 15
Source title: Advances in Malware and Data-Driven Network Security
Source Author(s)/Editor(s): Brij B. Gupta (National Institute of Technology, Kurukshetra, India)
DOI: 10.4018/978-1-7998-7789-9.ch004

Keywords: Cyber and Network Security / Information Science Reference / Information Security & Privacy / Security & Forensics

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Abstract

Software has been the essential element to computers in today's digital era. Unfortunately, it has experienced challenges from various types of malware, which are designed for sabotage, criminal money-making, and information theft. To protect the gadgets from malware, numerous malware detection algorithms have been proposed. In the olden days there were shallow learning algorithms, and in recent years there are deep learning algorithms. With the availability of big data for training of model and affordable and high-performance computing services, deep learning has demonstrated its superiority in many smart city applications, in terms of accuracy, error rate, etc. This chapter intends to conduct a systematic review on the latest development of deep learning algorithms for malware detection. Some future research directions are suggested for further exploration.

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The Era of Advanced Machine Learning and Deep Learning Algorithms for Malware Detection

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