Security, Cloud and Edge Lab

Giovanni Gambigliani Zoccoli

Research Assistant

Department of Engineering "Enzo Ferrari"
University of Modena and Reggio Emilia
Via Vivarelli, 10
41125 - Modena, Italy
Tel.: +39 0592056273
E-mail: giovanni.gambiglianizoccoli[AT]
PGP Key: 0x50A976BA70F7A9FB

Curriculum Vitae: Ita


  • Automotive Cyber-Security
  • Misbehaviour Detection in C-ITS


Zoccoli, G. G.; Pollicino, F.; Stabili, D.; Marchetti, M.
21st IEEE International Symposium on Network Computing and Applications, NCA 2022

This paper proposes SixPack v2, an enhanced version of the SixPack attack that allows to evade even state-of-the-art misbehavior detection systems. As the original SixPack, SixPack v2 is a dynamic attack targeting other C-ITS entities by simulating the sudden activation of the braking system with consequent activation of the Anti-lock Braking System. SixPack v2 achieves better evasion by improving the main phases of the attack (FakeBrake, Recovery, and Rejoin) through a novel path-reconstruction algorithm that generates a more realistic representation of the real vehicle trajectory. We experimentally evaluate the evasion capabilities of SixPack v2 using the F2MD framework on the LuSTMini city scenario, and we compared the detection performance of the F2MD framework on both versions of SixPack. Results show that SixPack v2 evades detection with a significantly higher likelihood with respect to the initial version of the attack, even against the latest version of F2MD.

Year: 2022 | Pages: 243 - 249

ISBN: 979-8-3503-9730-7 | DOI: 10.1109/NCA57778.2022.10013565