- Title
- An evidence theoretic approach for traffic signal intrusion detection
- Creator
- Chowdhury, Abdullahi; Karmakar, Gour; Kamruzzaman, Joarder; Das, Rajkumar; Newaz, Shah
- Date
- 2023
- Type
- Text; Journal article
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/194308
- Identifier
- vital:18319
- Identifier
-
https://doi.org/10.3390/s23104646
- Identifier
- ISSN:1424-8220
- Abstract
- The increasing attacks on traffic signals worldwide indicate the importance of intrusion detection. The existing traffic signal Intrusion Detection Systems (IDSs) that rely on inputs from connected vehicles and image analysis techniques can only detect intrusions created by spoofed vehicles. However, these approaches fail to detect intrusion from attacks on in-road sensors, traffic controllers, and signals. In this paper, we proposed an IDS based on detecting anomalies associated with flow rate, phase time, and vehicle speed, which is a significant extension of our previous work using additional traffic parameters and statistical tools. We theoretically modelled our system using the Dempster-Shafer decision theory, considering the instantaneous observations of traffic parameters and their relevant historical normal traffic data. We also used Shannon's entropy to determine the uncertainty associated with the observations. To validate our work, we developed a simulation model based on the traffic simulator called SUMO using many real scenarios and the data recorded by the Victorian Transportation Authority, Australia. The scenarios for abnormal traffic conditions were generated considering attacks such as jamming, Sybil, and false data injection attacks. The results show that the overall detection accuracy of our proposed system is 79.3% with fewer false alarms.
- Publisher
- MDPI AG
- Relation
- Sensors Vol. 23, no. 10 (2023), p. 4646
- Rights
- All metadata describing materials held in, or linked to, the repository is freely available under a CC0 licence
- Rights
- Copyright Authors
- Rights
- Open Access
- Subject
- Analysis; Anomalies; Communication; Communications networks; Decision theory; Driving conditions; Entropy (Information theory); False alarms; False information; Flow velocity; Image analysis; Intelligent transportation systems; Intrusion detection; Intrusion detection systems; Jamming; Methods; Parameters; Roads & highways; Sensors; Traffic assignment; Traffic congestion; Traffic control; Traffic engineering; Traffic flow; Traffic information; Traffic models; Traffic signals; Traffic speed; Transportation planning; Vehicles; 4008 Electrical engineering; 4009 Electronics, sensors and digital hardware; 4606 Distribute computing and systems software
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