Confidential Intelligent Traffic Light Control System: Prevention of Unauthorized Traceability
Many research studies have designed intelligent traffic light scheduling algorithms. Some researchers rely on specialized sensors and hardware to gather real-time traffic data at signalized road intersections. Others benefit from artificial intelligence techniques and/or cloud computing technologies...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-06-01
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| Series: | Big Data and Cognitive Computing |
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| Online Access: | https://www.mdpi.com/2504-2289/9/7/169 |
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| author | Ahmad Audat Maram Bani Younes Marah Yahia Said Ghoul |
| author_facet | Ahmad Audat Maram Bani Younes Marah Yahia Said Ghoul |
| author_sort | Ahmad Audat |
| collection | DOAJ |
| description | Many research studies have designed intelligent traffic light scheduling algorithms. Some researchers rely on specialized sensors and hardware to gather real-time traffic data at signalized road intersections. Others benefit from artificial intelligence techniques and/or cloud computing technologies. The technology of vehicular networks has been widely used to gather the traffic characteristics of competing traffic flows at signalized road intersections. Intelligent traffic light controlling systems aim to fairly liberate competing traffic at signalized road intersections and eliminate traffic crises. These algorithms have been initially developed without focusing on the consequences of security threats or attacks. However, the accuracy of gathered traffic data at each road intersection affects its performance. Fake and corrupted packets highly affect the accuracy of the gathered traffic data. Thus, in this work, we aim to investigate the aspects of security and confidentiality of intelligent traffic light systems. The possible attacks on the confidentiality of intelligent traffic light systems are examined. Then, a confidential traffic light control system that protects the privacy of traveling vehicles and drivers is presented. The proposed algorithm mainly prevents unauthorized traceability and linkability attacks that threaten people’s lives and violate their privacy. Finally, the proposed algorithm is evaluated through extensive experiments to verify its correctness and benefits compared to traditional insecure intelligent traffic light systems. |
| format | Article |
| id | doaj-art-cdbe1b730e2f4b40bd240cfe4859269c |
| institution | DOAJ |
| issn | 2504-2289 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Big Data and Cognitive Computing |
| spelling | doaj-art-cdbe1b730e2f4b40bd240cfe4859269c2025-08-20T03:13:42ZengMDPI AGBig Data and Cognitive Computing2504-22892025-06-019716910.3390/bdcc9070169Confidential Intelligent Traffic Light Control System: Prevention of Unauthorized TraceabilityAhmad Audat0Maram Bani Younes1Marah Yahia2Said Ghoul3Cybersecurity Department, Information Technology College, Amman Arab University, Amman 11953, JordanCybersecurity Department, Information Technology College, American University of Madaba, Madaba 11821, JordanSoftware Engineering Department, Information Technology College, Jadara University, Irbid 21110, JordanSoftware Engineering Department, Information Technology College, Philadelphia University, Amman 19392, JordanMany research studies have designed intelligent traffic light scheduling algorithms. Some researchers rely on specialized sensors and hardware to gather real-time traffic data at signalized road intersections. Others benefit from artificial intelligence techniques and/or cloud computing technologies. The technology of vehicular networks has been widely used to gather the traffic characteristics of competing traffic flows at signalized road intersections. Intelligent traffic light controlling systems aim to fairly liberate competing traffic at signalized road intersections and eliminate traffic crises. These algorithms have been initially developed without focusing on the consequences of security threats or attacks. However, the accuracy of gathered traffic data at each road intersection affects its performance. Fake and corrupted packets highly affect the accuracy of the gathered traffic data. Thus, in this work, we aim to investigate the aspects of security and confidentiality of intelligent traffic light systems. The possible attacks on the confidentiality of intelligent traffic light systems are examined. Then, a confidential traffic light control system that protects the privacy of traveling vehicles and drivers is presented. The proposed algorithm mainly prevents unauthorized traceability and linkability attacks that threaten people’s lives and violate their privacy. Finally, the proposed algorithm is evaluated through extensive experiments to verify its correctness and benefits compared to traditional insecure intelligent traffic light systems.https://www.mdpi.com/2504-2289/9/7/169smart traffic lightsecurityconfidentialitytraceabilitylinkability |
| spellingShingle | Ahmad Audat Maram Bani Younes Marah Yahia Said Ghoul Confidential Intelligent Traffic Light Control System: Prevention of Unauthorized Traceability Big Data and Cognitive Computing smart traffic light security confidentiality traceability linkability |
| title | Confidential Intelligent Traffic Light Control System: Prevention of Unauthorized Traceability |
| title_full | Confidential Intelligent Traffic Light Control System: Prevention of Unauthorized Traceability |
| title_fullStr | Confidential Intelligent Traffic Light Control System: Prevention of Unauthorized Traceability |
| title_full_unstemmed | Confidential Intelligent Traffic Light Control System: Prevention of Unauthorized Traceability |
| title_short | Confidential Intelligent Traffic Light Control System: Prevention of Unauthorized Traceability |
| title_sort | confidential intelligent traffic light control system prevention of unauthorized traceability |
| topic | smart traffic light security confidentiality traceability linkability |
| url | https://www.mdpi.com/2504-2289/9/7/169 |
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