889 citations · 1.7k across the 36 of their papers we have counts for
8 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…
Is Data Clustering in Adversarial Settings Secure?
Battista Biggio, Ignazio Pillai, Samuel Rota Bulò +3
Clustering algorithms have been increasingly adopted in security applications to spot dangerous or illicit activities. However, they have not been originally devised to deal with d…
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…
Why Do Adversarial Attacks Transfer? Explaining Transferability of Evasion and Poisoning Attacks
Ambra Demontis, Marco Melis, Maura Pintor +5
Transferability captures the ability of an attack against a machine-learning model to be effective against a different, potentially unknown, model. Empirical evidence for transfera…
Towards Adversarial Configurations for Software Product Lines
Paul Temple, Mathieu Acher, Battista Biggio +2
Ensuring that all supposedly valid configurations of a software product line (SPL) lead to well-formed and acceptable products is challenging since it is most of the time impractic…
Is feature selection secure against training data poisoning?
Huang Xiao, Battista Biggio, Gavin Brown +3
Learning in adversarial settings is becoming an important task for application domains where attackers may inject malicious data into the training set to subvert normal operation o…