AdDetect: Automated detection of Android ad libraries using semantic analysis

IEEE ISSNIP 2014 - 2014 IEEE 9th International Conference on Intelligent Sensors, Sensor Networks and Information Processing, Conference Proceedings

Volumn , Issue , 2014, Pages

  Narayanan, Annamalai ^a   Chen, Lihui ^a   Chan, Chee Keong ^a  

^a NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; DATA PROCESSING; INTELLIGENT CONTROL; LIBRARIES; MALWARE; SEMANTICS; SENSOR NETWORKS; SMART SENSORS; VIRUSES;

AUTOMATED DETECTION; DECOUPLING TECHNIQUE; DETECTION MECHANISM; HIER-ARCHICAL CLUSTERING; MOBILE OPERATING SYSTEMS; RECENT RESEARCHES; SEMANTIC ANALYSIS; UNSOLVED PROBLEMS;

ANDROID (OPERATING SYSTEM);

EID: 84903745241     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ISSNIP.2014.6827639     Document Type: Conference Paper

References (17)

1. Google Play. Dec. 2013. URL: https://play.google.com/store
2. Grace, M. C., Zhou, W., Jiang, X., & Sadeghi, A. R. (2012, April). Unsafe exposure analysis of mobile in-app advertisements. In Proceedings of the fifth ACM conference on Security and Privacy in Wireless and Mobile Networks (pp. 101-112). ACM.
3. Stevens, R., Gibler, C., Crussell, J., Erickson, J., & Chen, H. (2012, May). Investigating user privacy in android ad libraries. In Workshop on Mobile Security Technologies (MoST).
4. Book, T., Pridgen, A., & Wallach, D. S. (2013). Longitudinal Analysis of Android Ad Library Permissions. In IEEE Mobile Security Technologies (MoST).
5. Pearce, P., Felt, A. P., Nunez, G., & Wagner, D. (2012, May). Addroid: Privilege separation for applications and advertisers in android. In Proceedings of the 7th ACM Symposium on Information, Computer and Communications Security (pp. 71-72). ACM.
6. Tongaonkar, A., Dai, S., Nucci, A., & Song, D. (2013, January). Understanding mobile app usage patterns using in-app advertisements. In Passive and Active Measurement (pp. 63-72). Springer Berlin Heidelberg.
7. Book, T., & Wallach, D. S. (2013, November). A case of collusion: a study of the interface between ad libraries and their apps. In Proceedings of the Third ACM workshop on Security and privacy in smartphones & mobile devices (pp. 79-86). ACM.
8. Gibler, C., Stevens, R., Crussell, J., Chen, H., Zang, H., & Choi, H. (2013). AdRob: Examining the Landscape and Impact of Android Application Plagiarism. In Proceedings of 11th International Conference on Mobile Systems, Applications and Services.
9. apktool. Dec. 2013. URL: https://code.google.com/p/android-apktool
10. baksmali disassembler. Dec. 2013. URL: https://code.google.com/p/smali
11. Androguard. Dec. 2013. URL: https://code.google.com/p/androguard
12. Zhou, W., Zhou, Y., Grace, M., Jiang, X., & Zou, S. (2013, February). Fast, scalable detection of Piggybacked mobile applications. In Proceedings of the third ACM conference on Data and application security and privacy (pp. 185-196). ACM.
13. Kaufman, L., & Rousseeuw, P. J. (2009). Finding groups in data: an introduction to cluster analysis (Vol. 344). Wiley.com.
14. Au, K. W. Y., Zhou, Y. F., Huang, Z., & Lie, D. (2012, October). Pscout: analyzing the android permission specification. In Proceedings of the 2012 ACM conference on Computer and communications security (pp. 217-228). ACM.
15. Hall, M., Frank, E., Holmes, G., Pfahringer, B., Reutemann, P., and Witten, I. H. (2009). The WEKA data mining software: an update. ACM SIGKDD Explorations Newsletter 11, No 1, pp. 10-18.
16. N. V. Chawla, K. W. Bowyer, L. O. Hall, and W. P. Kegelmeyer. (2002). SMOTE: Synthetic Minority Over-sampling Technique. Journal of Artificial Intelligence Research, 16: 321-357.
17. Apperhand ad library threat. Dec. 2013. URL: urlhttp:// www.symantec.com/security response/writeup.jsp?docid=2012-012709-4046- 99&tabid=2