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. © 2009 Springer Berlin Heidelberg.
CITATION STYLE
Shabtai, A., Kanonov, U., & Elovici, Y. (2009). Detection, alert and response to malicious behavior in mobile devices: Knowledge-based approach. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5758 LNCS, pp. 357–358). https://doi.org/10.1007/978-3-642-04342-0_23
Mendeley helps you to discover research relevant for your work.