- Title
- Detecting intrusion in the traffic signals of an intelligent traffic system
- Creator
- Chowdhury, Abdullahi; Karmakar, Gour; Kamruzzaman, Joarder; Saha, Tapash
- Date
- 2018
- Type
- Text; Conference proceedings
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/166872
- Identifier
- vital:13513
- Identifier
-
https://doi.org/10.1007/978-3-030-01950-1_41
- Identifier
- ISBN:03029743 (ISSN); 9783030019495 (ISBN)
- Abstract
- Traffic systems and signals are used to improve traffic flow, reduce congestion, increase travel time consistency and ensure safety of road users. Malicious interruption or manipulation of traffic signals may cause disastrous instants including huge delays, financial loss and loss of lives. Intrusion into traffic signals by hackers can create such interruption whose consequences will only increase with the introduction of driverless vehicles. Recently, many traffic signals across the world are reported to have intruded, highlighting the importance of accurate detection. To reduce the impact of an intrusion, in this paper, we introduce an intrusion detection technique using the flow rate and phase time of a traffic signal as evidential information to detect the presence of an intrusion. The information received from flow rate and phase time are fused with the Dempster Shaffer (DS) theory. Historical data are used to create the probability mass functions for both flow rate and phase time. We also developed a simulation model using a traffic simulator, namely SUMO for many types of real traffic situations including intrusion. The performance of the proposed Intrusion Detection System (IDS) is appraised with normal traffic condition and induced intrusions. Simulated results show our proposed system can successfully detect intruded traffic signals from normal signals with significantly high accuracy (above 91%).; Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
- Publisher
- Springer Verlag
- Relation
- 20th International Conference on Information and Communications Security, ICICS 2018; Lille, France; 29th-31st October 2018; published in Lecure Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 11149 LNCS, p. 696-707
- Rights
- Copyright © Springer Nature Switzerland AG 2018.
- Rights
- This metadata is freely available under a CCO license
- Subject
- Intelligent traffic system; Intrusion detection; Traffic signal
- Reviewed
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