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The Scientific World Journal
Volume 2014, Article ID 101986, 11 pages
Research Article

SmartMal: A Service-Oriented Behavioral Malware Detection Framework for Mobile Devices

1Department of Computer Science, University of Science and Technology of China, Hefei 230027, China
2School of Software Engineering, University of Science and Technology of China, Suzhou 215123, China
3Faculty of Business and Information Technology, University of Ontario Institute of Technology, Oshawa, ON, Canada

Received 14 March 2014; Accepted 2 June 2014; Published 5 August 2014

Academic Editor: Fei Yu

Copyright © 2014 Chao Wang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


This paper presents SmartMal—a novel service-oriented behavioral malware detection framework for vehicular and mobile devices. The highlight of SmartMal is to introduce service-oriented architecture (SOA) concepts and behavior analysis into the malware detection paradigms. The proposed framework relies on client-server architecture, the client continuously extracts various features and transfers them to the server, and the server’s main task is to detect anomalies using state-of-art detection algorithms. Multiple distributed servers simultaneously analyze the feature vector using various detectors and information fusion is used to concatenate the results of detectors. We also propose a cycle-based statistical approach for mobile device anomaly detection. We accomplish this by analyzing the users’ regular usage patterns. Empirical results suggest that the proposed framework and novel anomaly detection algorithm are highly effective in detecting malware on Android devices.