Alheeti, Khattab M Ali and Gruebler, Anna and McDonald-Maier, Klaus and Fernando, Anil (2016) Prediction of DoS attacks in external communication for self-driving vehicles using a fuzzy petri net model. In: 2016 IEEE International Conference on Consumer Electronics (ICCE), 2016-01-07 - 2016-01-11, Las Vegas, NV.
Alheeti, Khattab M Ali and Gruebler, Anna and McDonald-Maier, Klaus and Fernando, Anil (2016) Prediction of DoS attacks in external communication for self-driving vehicles using a fuzzy petri net model. In: 2016 IEEE International Conference on Consumer Electronics (ICCE), 2016-01-07 - 2016-01-11, Las Vegas, NV.
Alheeti, Khattab M Ali and Gruebler, Anna and McDonald-Maier, Klaus and Fernando, Anil (2016) Prediction of DoS attacks in external communication for self-driving vehicles using a fuzzy petri net model. In: 2016 IEEE International Conference on Consumer Electronics (ICCE), 2016-01-07 - 2016-01-11, Las Vegas, NV.
Abstract
In this paper we propose a security system to protect external communications for self-driving and semi self-driving cars. The proposed system can detect malicious vehicles in an urban mobility scenario. The anomaly detection system is based on fuzzy petri nets (FPN) to detect packet dropping attacks in vehicular ad hoc networks. The experimental results show the proposed FPN-IDS can successfully detect DoS attacks in external communication of self-driving vehicles.
Item Type: | Conference or Workshop Item (Paper) |
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Additional Information: | Published proceedings: 2016 IEEE International Conference on Consumer Electronics (ICCE) |
Uncontrolled Keywords: | Security; self-driving cars; platoon; IDS; FPN |
Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
Divisions: | Faculty of Science and Health Faculty of Science and Health > Computer Science and Electronic Engineering, School of |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 13 Dec 2016 21:23 |
Last Modified: | 30 Oct 2024 20:04 |
URI: | http://repository.essex.ac.uk/id/eprint/18129 |
Available files
Filename: Prediction of DoS Attacks Accepted.pdf