Android Malware Mitigation

As Android devices gain popularity and are increasingly used to perform sensitive tasks (e.g., online banking) they become an attractive target for cybercriminals. In this project we aim to better understanding the threat posed by Android malware, and to develop novel techniques to detect it and protect victim devices.


MaMaDroid: Detecting Android Malware by Building Markov Chains of Behavioral Models

Enrico Mariconti, Lucky Onwuzurike, Panagiotis Andriotis, Emiliano De Cristofaro, Gordon Ross, and Gianluca Stringhini.
NDSS, 2017.

A Family of Droids: Analyzing Behavioral Model based Android Malware Detection via Static and Dynamic Analysis

Lucky Onwuzurike, Mario Almeida, Enrico Mariconti, Jeremy Blackburn, Gianluca Stringhini, and Emiliano De Cristofaro.
PST, 2018.

AndrEnsemble: Leveraging API Ensembles to Characterize Android Malware Families

Omid Mirzaei, Guillermo Suarez-Tangil, Juan Maria De Fuentes, Juan Tapiador, and Gianluca Stringhini.
ASIACCS, 2019.

Eight Years of Rider Measurement in the Android Malware Ecosystem

Guillermo Suarez-Tangil and Gianluca Stringhini.
TDSC 2020.


MaMaDroid Source Code