889 citations · 898 across the 4 of their papers we have counts for
4 papers · 1 filter
Evasion Attacks against Machine Learning at Test Time
Battista Biggio, Igino Corona, Davide Maiorca +5
In security-sensitive applications, the success of machine learning depends on a thorough vetting of their resistance to adversarial data. In one pertinent, well-motivated attack s…
DeltaPhish: Detecting Phishing Webpages in Compromised Websites
Igino Corona, Battista Biggio, Matteo Contini +6
The large-scale deployment of modern phishing attacks relies on the automatic exploitation of vulnerable websites in the wild, to maximize profit while hindering attack traceabilit…
Yes, Machine Learning Can Be More Secure! A Case Study on Android Malware Detection
Ambra Demontis, Marco Melis, Battista Biggio +6
To cope with the increasing variability and sophistication of modern attacks, machine learning has been widely adopted as a statistically-sound tool for malware detection. However,…
AdversariaLib: An Open-source Library for the Security Evaluation of Machine Learning Algorithms Under Attack
Igino Corona, Battista Biggio, Davide Maiorca
We present AdversariaLib, an open-source python library for the security evaluation of machine learning (ML) against carefully-targeted attacks. It supports the implementation of s…