Android Malware


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The Android Malware Handbook


The Android Malware Handbook

Author: Qian Han

language: en

Publisher: No Starch Press

Release Date: 2023-11-07


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Written by machine-learning researchers and members of the Android Security team, this all-star guide tackles the analysis and detection of malware that targets the Android operating system. 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 identifica-tion of malware categories like banking trojans, ransomware, and SMS fraud. 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.

Malware Analysis Using Artificial Intelligence and Deep Learning


Malware Analysis Using Artificial Intelligence and Deep Learning

Author: Mark Stamp

language: en

Publisher: Springer Nature

Release Date: 2020-12-20


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​This book is focused on the use of deep learning (DL) and artificial intelligence (AI) as tools to advance the fields of malware detection and analysis. The individual chapters of the book deal with a wide variety of state-of-the-art AI and DL techniques, which are applied to a number of challenging malware-related problems. DL and AI based approaches to malware detection and analysis are largely data driven and hence minimal expert domain knowledge of malware is needed. This book fills a gap between the emerging fields of DL/AI and malware analysis. It covers a broad range of modern and practical DL and AI techniques, including frameworks and development tools enabling the audience to innovate with cutting-edge research advancements in a multitude of malware (and closely related) use cases.

Research in Attacks, Intrusions, and Defenses


Research in Attacks, Intrusions, and Defenses

Author: Marc Dacier

language: en

Publisher: Springer

Release Date: 2017-10-10


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This book constitutes the refereed conference proceedings of the 20th International Symposium on Research in Attacks, Intrusions, and Defenses, RAID 2017, held in Atlanta, GA, USA, in September 2017. The 21 revised full papers were selected from 105 submissions. They are organized in the following topics: software security, intrusion detection, systems security, android security, cybercrime, cloud security, network security.