Detection, Alert and Response to Malicious Behavior in Mobile Devices: Knowledge-Based Approach

  • Authors:

  • Asaf Shabtai;Uri Kanonov;Yuval Elovici

  • Affiliations:

  • Deutsche Telekom Laboratories at Ben-Gurion University and Department of Information Systems Engineering, Ben-Gurion University, Israel;Deutsche Telekom Laboratories at Ben-Gurion University and Department of Information Systems Engineering, Ben-Gurion University, Israel;Deutsche Telekom Laboratories at Ben-Gurion University and Department of Information Systems Engineering, Ben-Gurion University, Israel

  • Venue:
  • RAID '09 Proceedings of the 12th International Symposium on Recent Advances in Intrusion Detection
  • Year:
  • 2009

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Abstract

In this research, we evaluate a knowledge-based approach for detecting instances of known classes of mobile devices malware based on their temporal behavior. The framework relies on lightweight agent that continuously monitors time-stamped security data within the mobile device and then processes the data using a light version of the Knowledge-Based Temporal Abstraction (KBTA) methodology. The new approach was applied for detecting malware on Google Android powered-devices. Evaluation results demonstrated the effectiveness of the proposed approach.