1 citations · 1 across the 1 of their papers we have counts for
5 papers
Defending Network Intrusion Detection Systems Based on Graph Neural Networks Against Structural Adversarial Attacks
Dimitri Galli, Andrea Venturi, Dario Stabili +2
Graph Neural Networks (GNNs) represent a promising solution for Machine Learning (ML) based Network Intrusion Detection Systems (NIDS), thanks to their ability to leverage both net…
RADAR: a Radio-based Analytics for Dynamic Association and Recognition of pseudonyms in VANETs
Giovanni Gambigliani Zoccoli, Filip Valgimigli, Dario Stabili +1
This paper presents RADAR, a tracking algorithm for vehicles participating in Cooperative Intelligent Transportation Systems (C-ITS) that exploits multiple radio signals emitted by…
Finding (and exploiting) vulnerabilities on IP Cameras: the Tenda CP3 case study
Dario Stabili, Tobia Bocchi, Filip Valgimigli +1
Consumer IP cameras are now the most widely adopted solution for remote monitoring in various contexts, such as private homes or small offices. While the security of these devices…
HackCar: a test platform for attacks and defenses on a cost-contained automotive architecture
Dario Stabili, Filip Valgimigli, Edoardo Torrini +1
In this paper, we introduce the design of HackCar, a testing platform for replicating attacks and defenses on a generic automotive system without requiring access to a complete veh…
Problem space structural adversarial attacks for Network Intrusion Detection Systems based on Graph Neural Networks
Andrea Venturi, Dario Stabili, Mirco Marchetti
Machine Learning (ML) algorithms have become increasingly popular for supporting Network Intrusion Detection Systems (NIDS). Nevertheless, extensive research has shown their vulner…