Adversarial ModSecurity: Countering Adversarial SQL Injections with Robust Machine Learning

no code implementations • 9 Aug 2023 • Biagio Montaruli, Luca Demetrio, Andrea Valenza, Luca Compagna, Davide Ariu, Luca Piras, Davide Balzarotti, Battista Biggio

To overcome these issues, we design a robust machine learning model, named AdvModSec, which uses the CRS rules as input features, and it is trained to detect adversarial SQLi attacks.

Adversarial Robustness

Is Data Clustering in Adversarial Settings Secure?

no code implementations • 25 Nov 2018 • Battista Biggio, Ignazio Pillai, Samuel Rota Bulò, Davide Ariu, Marcello Pelillo, Fabio Roli

In this work we propose a general framework that allows one to identify potential attacks against clustering algorithms, and to evaluate their impact, by making specific assumptions on the adversary's goal, knowledge of the attacked system, and capabilities of manipulating the input data.

Clustering

Poisoning Behavioral Malware Clustering

no code implementations • 25 Nov 2018 • Battista Biggio, Konrad Rieck, Davide Ariu, Christian Wressnegger, Igino Corona, Giorgio Giacinto, Fabio Roli

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 antivirus systems.

Clustering Computer Security +1