3 papers
cs.CR2026
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…
cs.CR2026
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…
cs.CR2025
Are Trees Really Green? A Detection Approach of IoT Malware Attacks
Silvia Lucia Sanna, Diego Soi, Davide Maiorca +1
Nowadays, the Internet of Things (IoT) is widely employed, and its usage is growing exponentially because it facilitates remote monitoring, predictive maintenance, and data-driven…