8 citations · 8 across the 6 of their papers we have counts for
3 papers · 1 filter
DroidBreaker: Practical and Functional Problem-Space Attacks on Machine-Learning Android Malware Detectors
Christian Scano, Diego Soi, Angelo Sotgiu +5
Adversarial APKs are Android applications modified in the problem space to evade machine-learning malware detectors. In this work, we first show that, despite claims, existing prob…
Don't Trust Us: A privacy-by-design android malware detection pipeline
Emmanuele Massidda, Diego Soi, Giorgio Giacinto
Android malware detection increasingly relies on collecting and processing sensitive user data, including device identifiers, network artifacts, and runtime traces, while privacy i…
AndroWasm: an Empirical Study on Android Malware Obfuscation through WebAssembly
Diego Soi, Silvia Lucia Sanna, Lorenzo Pisu +2
In recent years, stealthy Android malware has increasingly adopted sophisticated techniques to bypass automatic detection mechanisms and harden manual analysis. Adversaries typical…