Abstract
Rewarded advertisements are popularly used in the mobile advertising industry. In this paper, we analyze several rewarded advertisement applications to discover security weaknesses, which allow malicious users to automatically generate in-app activities for earning cash rewards on advertisement networks; we call this attack automated cash mining. To show the risk of this attack, we implemented automated cashing attacks on four popularly used Android applications (Cash Slide, Fronto, Honey Screen and Screen Stash) with rewarded advertisements through reverse engineering and demonstrated that all the tested reward apps are vulnerable to our attack implementation.
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References
Fiddler Extension (Requset to Code). http://www.chadsowald.com/software/fiddler-extension-request-to-code. Accessed 28 Feb 2019
Cho, G., Cho, J., Song, Y., Choi, D., Kim, H.: Combating online fraud attacks in mobile-based advertising. EURASIP J. Inf. Secur. 2016(1), 2 (2016)
Crussell, J., Stevens, R., Chen, H.: Madfraud: investigating ad fraud in android applications. In: Proceedings of the 12th Annual International Conference on Mobile Systems, Applications, and Services (2014)
Enck, W., Octeau, D., McDaniel, P., Chaudhuri, S.: A study of android application security. In: Proceedings of the 20th USENIX Security Symposium (2011)
Evans, C., Palmer, C.: Certificate pinning extension for HSTS (2011). https://tools.ietf.org/html/draft-evans-palmer-hsts-pinning-00
Immorlica, N., Jain, K., Mahdian, M., Talwar, K.: Click fraud resistant methods for learning click-through rates. In: Deng, X., Ye, Y. (eds.) WINE 2005. LNCS, vol. 3828, pp. 34–45. Springer, Heidelberg (2005). https://doi.org/10.1007/11600930_5
Acknowledgments
This work was supported in part by NRF of Korea (NRF-2017K1A3A1A17092614) and the ICT Consilience Creative support program (IITP-2019-2015-0-00742).
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Ji, W., Kim, T., Kim, K., Kim, H. (2019). Automated Cash Mining Attacks on Mobile Advertising Networks. In: Jang-Jaccard, J., Guo, F. (eds) Information Security and Privacy. ACISP 2019. Lecture Notes in Computer Science(), vol 11547. Springer, Cham. https://doi.org/10.1007/978-3-030-21548-4_40
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DOI: https://doi.org/10.1007/978-3-030-21548-4_40
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