13 papers
MoLIFE: Methodology, Technologies, and Challenges for Mobile Live Intelligent Forensics Examination
Silvia Lucia Sanna, Cristina Alcaraz, Alessandro Sanna +2
Nowadays, mobile forensics is less explored in Digital Forensics case analysis due to the increase in data protection mechanisms implemented by tech companies (i.e., Google for And…
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…
The Sound of Malware: A Memory Forensics Approach for Android Malware Analysis via Audio Signals
Silvia Lucia Sanna, Massimo Palozzi, Leonardo Regano +2
Android malware analysis is currently facing increasing challenges in achieving robust classification and detecting stealth attacks. Modern threats employ advanced evasion strategi…
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…
Obfuscating Code Vulnerabilities against Static Analysis in JavaScript Code
Francesco Pagano, Lorenzo Pisu, Leonardo Regano +3
Code obfuscation is widely adopted in modern software development to protect intellectual property and hinder reverse engineering, but it also provides attackers with a powerful me…
Label-efficient Training Updates for Malware Detection over Time
Luca Minnei, Cristian Manca, Giorgio Piras +6
Machine Learning (ML)-based detectors are becoming essential to counter the proliferation of malware. However, common ML algorithms are not designed to cope with the dynamic nature…