The popularity of Android mobile phones has attracted cybercriminals to create malware applications that carry out various malicious activities. The attacks escalated much more after the COVID-19 pandemic. In this scenario, it is very important to protect our Android mobile devices from malware attacks. This book will teach how to develop intelligent Android malware detection mechanisms using various graph and stochastic models. The book begins with an introduction of the Android operating system accompanied by the limitations of the state of the art static malware detection mechanisms and a detailed presentation of a hybrid malware detection mechanism. The book then presents four different system call based dynamic Android malware detection mechanisms using graph centrality measures, graph signal processing and graph convolutional networks. Further it is showed that most of the Android malware could be detected by checking the presence of a unique subsequence of system calls in its system call sequence. All the malware detection mechanisms presented in the book are based on the recent research works of the authors. The experiments are conducted with the latest Android malware samples and also the malware samples collected from public repositories. The source codes are also provided for easy implementation of the mechanisms. This book will be highly useful for Android malware researchers, developers, students and cyber security professionals to explore and build defense mechanisms against the ever-evolving Android malware.

Book Information
ISBN 9780367638719
Author Tony Thomas
Format Hardback
Page Count 200
Imprint CRC Press
Publisher Taylor & Francis Ltd
Weight(grams) 156g