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

Author:

Chui Kwok Tai1,Ordóñez de Pablos Patricia2,Lytras Miltiadis D.3,Liu Ryan Wen4ORCID,Shen Chien-wen5

Affiliation:

1. Hong Kong Metropolitan University, Hong Kong

2. The University of Oviedo, Spain

3. Deree College — The American College of Greece, Greece

4. Wuhan University of Technology, China

5. National Central University, Taiwan

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.

Publisher

IGI Global

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1. Circular LBP Prior-Based Enhanced GAN for Image Style Transfer;International Journal on Semantic Web and Information Systems;2022-12-16

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