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2018-02-21
Tien, C. W., Huang, T. Y., Huang, T. C., Chung, W. H., Kuo, S. Y..  2017.  MAS: Mobile-Apps Assessment and Analysis System. 2017 47th Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops (DSN-W). :145–148.

Mobile apps are widely adopted in daily life, and contain increasing security flaws. Many regulatory agencies and organizations have announced security guidelines for app development. However, most security guidelines involving technicality and compliance with this requirement is not easily feasible. Thus, we propose Mobile Apps Assessment and Analysis System (MAS), an automatic security validation system to improve guideline compliance. MAS combines static and dynamic analysis techniques, which can be used to verify whether android apps meet the security guideline requirements. We implemented MAS in practice and verified 143 real-world apps produced by the Taiwan government. Besides, we also validated 15,000 popular apps collected from Google Play Store produced in three countries. We found that most apps contain at least three security issues. Finally, we summarize the results and list the most common security flaws for consideration in further app development.

2019-09-26
Pfeffer, T., Herber, P., Druschke, L., Glesner, S..  2018.  Efficient and Safe Control Flow Recovery Using a Restricted Intermediate Language. 2018 IEEE 27th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE). :235-240.

Approaches for the automatic analysis of security policies on source code level cannot trivially be applied to binaries. This is due to the lacking high-level semantics of low-level object code, and the fundamental problem that control-flow recovery from binaries is difficult. We present a novel approach to recover the control-flow of binaries that is both safe and efficient. The key idea of our approach is to use the information contained in security mechanisms to approximate the targets of computed branches. To achieve this, we first define a restricted control transition intermediate language (RCTIL), which restricts the number of possible targets for each branch to a finite number of given targets. Based on this intermediate language, we demonstrate how a safe model of the control flow can be recovered without data-flow analyses. Our evaluation shows that that makes our solution more efficient than existing solutions.