30 citations · 55 across the 5 of their papers we have counts for
5 papers
ROSpace: Intrusion Detection Dataset for a ROS2-Based Cyber-Physical System
Tommaso Puccetti, Simone Nardi, Cosimo Cinquilli +2
Most of the intrusion detection datasets to research machine learning-based intrusion detection systems (IDSs) are devoted to cyber-only systems, and they typically collect data fr…
Ensembling Uncertainty Measures to Improve Safety of Black-Box Classifiers
Tommaso Zoppi, Andrea Ceccarelli, Andrea Bondavalli
Machine Learning (ML) algorithms that perform classification may predict the wrong class, experiencing misclassifications. It is well-known that misclassifications may have cascadi…
On the Efficacy of Metrics to Describe Adversarial Attacks
Tommaso Puccetti, Tommaso Zoppi, Andrea Ceccarelli
Adversarial defenses are naturally evaluated on their ability to tolerate adversarial attacks. To test defenses, diverse adversarial attacks are crafted, that are usually described…
Prepare for Trouble and Make it Double. Supervised and Unsupervised Stacking for AnomalyBased Intrusion Detection
Tommaso Zoppi, Andrea Ceccarelli
In the last decades, researchers, practitioners and companies struggled in devising mechanisms to detect malicious activities originating security threats. Amongst the many solutio…
Unsupervised Anomaly Detectors to Detect Intrusions in the Current Threat Landscape
Tommaso Zoppi, Andrea ceccarelli, Tommaso Capecchi +1
Anomaly detection aims at identifying unexpected fluctuations in the expected behavior of a given system. It is acknowledged as a reliable answer to the identification of zero-day…