Название: The Android Malware Handbook: Detection and Analysis by Human and Machine
Автор: Qian Han, Salvador Mandujano, Sebastian Porst, V.S. Subrahmanian
Издательство: No Starch Press
Год: 2024
Страниц: 446
Язык: английский
Формат: epub
Размер: 25.6 MB

This groundbreaking guide to Android malware distills years of research by Machine Learning experts in academia and members of Meta and Google’s Android Security teams into a comprehensive introduction to detecting common threats facing the Android eco-system today.

Explore the history of Android malware in the wild since the operating system first launched and then practice static and dynamic approaches to analyzing real malware specimens. Next, examine Machine Learning techniques that can be used to detect malicious apps, the types of classification models that defenders can implement to achieve these detections, and the various malware features that can be used as input to these models. Adapt these machine learning strategies to the identification of malware categories like banking trojans, ransomware, and SMS fraud.

Running on over three billion devices worldwide, Android operates a significant portion of the Internet of Things and is the most popular operating system in history. This reach also makes it one of the most attractive targets for cybercriminals; indeed, as I write this, Android and its devices, stores, apps, and users face constant attacks from a wide range of actors, including well-resourced criminal and state-sponsored organizations.

This threat profile demands a commensurate defense, and Android’s anti-malware program represents one of the most significant engineering investments in the history of cybersecurity. In the early days of Android, many believed the platform’s open source nature would hinder its ability to provide safe experiences for users. But after many years of hard work by academics, security companies, device and microprocessor manufacturers, the Linux community, and others, it is now more costly to develop exploits for Android than for all other consumer mobile operating systems. Android’s success in both popularity and safety is a testament to the transcendence of openness over walled gardens.
I am honored to introduce this comprehensive guide to modern Android malware detection, as it is yet another example of the transparency of the Android security community. The book covers a wide range of topics, from the basics of Android security and the types of malware present in the wild to the latest developments in the field of machine learning for malware identification and classification.

The authors delve into the technical details of manual program analysis and machine learning algorithms, highlighting the importance of using cutting-edge technology to detect and prevent malware when attackers are working hard to evade detection. They also describe specific types of malware, including rooting malware, spyware, banking trojans, ransomware, and toll fraud. Finally, they conclude with a look at the future of Android malware and the challenges that lie ahead. With its breadth of coverage, this book will remain an invaluable resource for security professionals and researchers, as well as those who simply want to stay informed about the state of Android security.

You’ll:

Dive deep into the source code of real malware
Explore the static, dynamic, and complex features you can extract from malware for analysis
Master the Machine Learning algorithms useful for malware detection
Survey the efficacy of Machine Learning techniques at detecting common Android malware categories

The Android Malware Handbook’s team of expert authors will guide you through the Android threat landscape and prepare you for the next wave of malware to come.




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