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Classifying Anomalous Mobile Applications Based on Data Flows

Authors:
Chia-Mei Chen
Gu-Hsin Lai
Yu-Hsuan Tsai
Sheng-Tzong Cheng

Keywords: mobile security; malware detection; static analysis.

Abstract:
Mobile security becomes more important as users increasingly rely on the portable network devices. The security consultant firms indicate that the amount of mobile malware increases every year at a fast speed. Therefore, fast detecting mobile malware becomes an important issue. By applying reverse engineering techniques, a source code extraction module produces data flow information from the mobile application executable. The proposed static analysis-based detection system analyzes the data flow of the target software and it identifies if a data flow might leak sensitive data. The experimental results show that the proposed detection system can identify mobile malware efficiently.

Pages: 147 to 150

Copyright: Copyright (c) IARIA, 2015

Publication date: April 19, 2015

Published in: conference

ISSN: 2308-4413

ISBN: 978-1-61208-398-8

Location: Barcelona, Spain

Dates: from April 19, 2015 to April 24, 2015