Detecting intrusion in the traffic signals of an intelligent traffic system
- Authors: Chowdhury, Abdullahi , Karmakar, Gour , Kamruzzaman, Joarder , Saha, Tapash
- Date: 2018
- Type: Text , Conference proceedings
- 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
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- Description: 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%).
- Description: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
An evidence theoretic approach for traffic signal intrusion detection
- Authors: Chowdhury, Abdullahi , Karmakar, Gour , Kamruzzaman, Joarder , Das, Rajkumar , Newaz, Shah
- Date: 2023
- Type: Text , Journal article
- Relation: Sensors Vol. 23, no. 10 (2023), p. 4646
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- Description: 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.