MOBDroid2: An Improved Feature Selection Method for Detecting Malicious Applications in a Mobile Cloud Computing Environment
Author:
Affiliation:
1. Auckland University of Technology,School of Engineering, Computer and Mathematical Sciences,Auckland,New Zealand
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9798893/9798894/09799201.pdf?arnumber=9799201
Reference21 articles.
1. MADAM: Effective and Efficient Behavior-based Android Malware Detection and Prevention
2. Significant Permission Identification for Machine-Learning-Based Android Malware Detection
3. A novel Android malware detection system: adaption of filter-based feature selection methods;?ahin;J Ambient Intelligence and Humanized Computing,2021
4. “Andromaly”: a behavioral malware detection framework for android devices
5. Automated Malware Detection in Mobile App Stores Based on Robust Feature Generation
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