The android malware handbook : manual analysis and ML-based detection
By: Han, Qian.
Contributor(s): Mandujano, Salvador | Porst, Sebastian | Subrahmanian, V. S | Tetali, Sai Deep | Xiong, Yanhai.
Material type:
BookPublisher: San Francisco : No starch Press, 2023Description: xxvi, 298 p. ; ill. (some b & w), 24 cm.ISBN: 9781718503304.Subject(s): Android | XGBoost | Wireshark | Uses-permission | Two-factor authentication | Spyware | Rooting malware | Reverse engineers | Ransomware | Privilege escalation | Manifest file | JSON | JavaScript | Decision tree | Command-and-control server | Click fraud | API package | Malware | Security measureDDC classification: 005.88 Summary: Explores the history of Android attacks and covers static and dynamic approaches to analyzing real malware specimens, machine-learning techniques to detect malicious apps, and how to identify banking trojans, ransomware, and SMS fraud.
| Item type | Current location | Call number | Status | Date due | Barcode |
|---|---|---|---|---|---|
| Books | 005.88 HAN (Browse shelf) | Available | 034808 |
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| 005.86 HAR Oracle Database 10g RMAN backup & recovery | 005.86 PRE Backup and recovery | 005.87 CHA Practical IoT hacking : the definitive guide to attacking the internet of things | 005.88 HAN The android malware handbook : manual analysis and ML-based detection | 005.88 SAX Malware data science : attack detection and attribution | 006.312 PEA Exploratory data analysis using R | 006.312 SKI Understanding high-dimensional spaces |
Includes index.
Explores the history of Android attacks and covers static and dynamic approaches to analyzing real malware specimens, machine-learning techniques to detect malicious apps, and how to identify banking trojans, ransomware, and SMS fraud.
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