8 citations · 13 across the 16 of their papers we have counts for
17 papers
Merging Cyber Threat Intelligence Through Retrieval-Augmented Generation and Small Language Models for Rich Threat Representation
Nicola Deidda, Leonardo Regano, Alessandro Sanna +2
Modern cybersecurity operations rely on CTI collected from heterogeneous sources, including semi-structured threat representations, IoCs, and narrative technical reports. However,…
SemVul: Semantic-Enhanced Graph Neural Networks for Code Property Graph-based Vulnerability Detection
Younas Affan, Leonardo Regano, Giorgio Giacinto
Vulnerabilities in source code are often the root cause of cyberattacks worldwide, as attackers exploit weaknesses in software to gain unauthorized access, steal data, or disrupt s…
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…
An Analysis of Modern Web Security Vulnerabilities Inside WebAssembly Applications
Lorenzo Corrias, Lorenzo Pisu, Davide Maiorca +1
The growth in the adoption of the WebAssembly (WASM) standard has given rise to a rapidly increasing landscape of binary applications that are natively ported to the environment of…
An Explainable Memory Forensics Approach for Malware Analysis
Silvia Lucia Sanna, Davide Maiorca, Giorgio Giacinto
Memory forensics is an effective methodology for analyzing living-off-the-land malware, including threats that employ evasion, obfuscation, anti-analysis, and steganographic techni…
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…
Improving Cybercrime Detection and Digital Forensics Investigations with Artificial Intelligence
Silvia Lucia Sanna, Leonardo Regano, Davide Maiorca +1
According to a recent EUROPOL report, cybercrime is still recurrent in Europe, and different activities and countermeasures must be taken to limit, prevent, detect, analyze, and fi…
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…
Exploring the Robustness of AI-Driven Tools in Digital Forensics: A Preliminary Study
Silvia Lucia Sanna, Leonardo Regano, Davide Maiorca +1
Nowadays, many tools are used to facilitate forensic tasks about data extraction and data analysis. In particular, some tools leverage Artificial Intelligence (AI) to automatically…
A Risk Estimation Study of Native Code Vulnerabilities in Android Applications
Silvia Lucia Sanna, Diego Soi, Davide Maiorca +2
Android is the most used Operating System worldwide for mobile devices, with hundreds of thousands of apps downloaded daily. Although these apps are primarily written in Java and K…
An Assessment of the Overlooked Dangers of Template Engines
Lorenzo Pisu, Davide Maiorca, Giorgio Giacinto
Template engines play a pivotal role in modern web application development by enabling the dynamic rendering of content, products, and user interfaces. Today, they are essential fo…
Can you See me? On the Visibility of NOPs against Android Malware Detectors
Diego Soi, Davide Maiorca, Giorgio Giacinto +1
Android malware still represents the most significant threat to mobile systems. While Machine Learning systems are increasingly used to identify these threats, past studies have re…