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MAMADROID: Detecting Android Malware by Building Markov Chains of Behavioral Models (2017)
Presentation / Conference
Mariconti, E., Onwuzurike, L., Andriotis, P., De Cristofaro, E., Ross, G., & Stringhini, G. (2017, February). MAMADROID: Detecting Android Malware by Building Markov Chains of Behavioral Models. Paper presented at NDSS Symposium 2017, San Diego, USA

The rise in popularity of the Android platform has resulted in an explosion of malware threats targeting it. As both Android malware and the operating system itself constantly evolve, it is very challenging to design robust malware mitigation techniq... Read More about MAMADROID: Detecting Android Malware by Building Markov Chains of Behavioral Models.

Permissions snapshots: Assessing users' adaptation to the Android runtime permission model (2017)
Conference Proceeding
Andriotis, P., Sasse, M. A., & Stringhini, G. (2017). Permissions snapshots: Assessing users' adaptation to the Android runtime permission model. . https://doi.org/10.1109/WIFS.2016.7823922

© 2016 IEEE. The Android operating system changed its security-and privacy-related permission model recently, offering its users the ability to control resources that applications are allowed to access on their devices. This major change to the tradi... Read More about Permissions snapshots: Assessing users' adaptation to the Android runtime permission model.

Privacy decision-making in the digital era: A game theoretic review (2017)
Journal Article
Anastasopoulou, K., Kokolakis, S., & Andriotis, P. (2017). Privacy decision-making in the digital era: A game theoretic review. Lecture Notes in Artificial Intelligence, 10292 LNCS, 589-603. https://doi.org/10.1007/978-3-319-58460-7_41

© Springer International Publishing AG 2017. Information privacy is constantly negotiated when people interact with enterprises and government agencies via the Internet. In this context, all relevant stakeholders take privacy-related decisions. Indiv... Read More about Privacy decision-making in the digital era: A game theoretic review.

A comparative study of android users’ privacy preferences under the runtime permission model (2017)
Journal Article
Andriotis, P., Li, S., Spyridopoulos, T., & Stringhini, G. (2017). A comparative study of android users’ privacy preferences under the runtime permission model. Lecture Notes in Artificial Intelligence, 10292 LNCS, 604-622. https://doi.org/10.1007/978-3-319-58460-7_42

© Springer International Publishing AG 2017. Android users recently were given the ability to selectively grant access to sensitive resources of their mobile devices when apps request them at runtime. The Android fine-grained runtime permission model... Read More about A comparative study of android users’ privacy preferences under the runtime permission model.