889 citations · 1.1k across the 14 of their papers we have counts for
6 papers · 1 filter
Poisoning Behavioral Malware Clustering
Battista Biggio, Konrad Rieck, Davide Ariu +4
Clustering algorithms have become a popular tool in computer security to analyze the behavior of malware variants, identify novel malware families, and generate signatures for anti…
Towards Adversarial Malware Detection: Lessons Learned from PDF-based Attacks
Davide Maiorca, Battista Biggio, Giorgio Giacinto
Malware still constitutes a major threat in the cybersecurity landscape, also due to the widespread use of infection vectors such as documents. These infection vectors hide embedde…
On the Effectiveness of System API-Related Information for Android Ransomware Detection
Michele Scalas, Davide Maiorca, Francesco Mercaldo +3
Ransomware constitutes a significant threat to the Android operating system. It can either lock or encrypt the target devices, and victims are forced to pay ransoms to restore thei…
Adversarial Malware Binaries: Evading Deep Learning for Malware Detection in Executables
Bojan Kolosnjaji, Ambra Demontis, Battista Biggio +4
Machine-learning methods have already been exploited as useful tools for detecting malicious executable files. They leverage data retrieved from malware samples, such as header fie…
Explaining Black-box Android Malware Detection
Marco Melis, Davide Maiorca, Battista Biggio +2
Machine-learning models have been recently used for detecting malicious Android applications, reporting impressive performances on benchmark datasets, even when trained only on fea…
IntelliAV: Building an Effective On-Device Android Malware Detector
Mansour Ahmadi, Angelo Sotgiu, Giorgio Giacinto
The importance of employing machine learning for malware detection has become explicit to the security community. Several anti-malware vendors have claimed and advertised the appli…