£123.11

Springer Android Malware Detection Machine Learning Book

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£128.11 £122.41 £123.66 £124.90 £126.14 £127.38 £128.63 11 March 2026 20 March 2026 30 March 2026 09 April 2026 19 April 2026

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Description

Protect mobile ecosystems with advanced technical insights from Springer. This book provides a comprehensive framework for Android malware detection and family attribution using machine learning. It addresses the growing need for data-driven fingerprinting to identify threats within large-scale app markets. The text focuses on building systems that remain effective against common obfuscation techniques. By studying the underlying static structure of Android applications, readers can understand how to implement approximate fingerprinting for bulk and offline detection. This approach is designed for high scalability and portability across different platforms and architectures. Whether you are researching cybersecurity or developing mobile security tools, this volume offers a deep look into modern threat intelligence. It bridges the gap between theoretical machine learning and practical application in the context of mobile security and large malware corpora.

Key Features

Develops a specialized malware fingerprinting framework for accurate Android detection and family attribution.

Provides methods for scalable analysis when working over a large malware corpus.

Offers techniques designed to remain resilient against common software obfuscation methods.

Ensures portability of detection methods across various platforms and different architectures.

Proposes an approximate fingerprinting technique to capture the static structure of Android applications.

Supports bulk and offline detection capabilities suitable for app-market level monitoring.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
12 July 2022
Listed Since
15 June 2022

Barcode

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