{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T01:26:10Z","timestamp":1760059570822,"version":"build-2065373602"},"reference-count":50,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2025,6,26]],"date-time":"2025-06-26T00:00:00Z","timestamp":1750896000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["BDCC"],"abstract":"<jats:p>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\u2019s 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.<\/jats:p>","DOI":"10.3390\/bdcc9070169","type":"journal-article","created":{"date-parts":[[2025,6,26]],"date-time":"2025-06-26T05:53:13Z","timestamp":1750917193000},"page":"169","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Confidential Intelligent Traffic Light Control System: Prevention of Unauthorized Traceability"],"prefix":"10.3390","volume":"9","author":[{"given":"Ahmad","family":"Audat","sequence":"first","affiliation":[{"name":"Cybersecurity Department, Information Technology College, Amman Arab University, Amman 11953, Jordan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3844-6409","authenticated-orcid":false,"given":"Maram Bani","family":"Younes","sequence":"additional","affiliation":[{"name":"Cybersecurity Department, Information Technology College, American University of Madaba, Madaba 11821, Jordan"}]},{"given":"Marah","family":"Yahia","sequence":"additional","affiliation":[{"name":"Software Engineering Department, Information Technology College, Jadara University, Irbid 21110, Jordan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8878-6540","authenticated-orcid":false,"given":"Said","family":"Ghoul","sequence":"additional","affiliation":[{"name":"Software Engineering Department, Information Technology College, Philadelphia University, Amman 19392, Jordan"}]}],"member":"1968","published-online":{"date-parts":[[2025,6,26]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"41","DOI":"10.23919\/ICN.2023.0004","article-title":"Emma: An accurate, efficient, and multi-modality strategy for autonomous vehicle angle prediction","volume":"4","author":"Song","year":"2023","journal-title":"Intell. Converg. Netw."},{"key":"ref_2","unstructured":"Hu, S., Tao, Y., Xu, G., Deng, Y., Chen, X., Fang, Y., and Kwong, S. (March, January 25). Cp-guard: Malicious agent detection and defense in collaborative bird\u2019s eye view perception. Proceedings of the AAAI Conference on Artificial Intelligence, Philadelphia, PA, USA."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Qiao, J., Zhang, D., and de Jonge, D. (2022, January 2\u20134). Priority-based traffic management protocols for autonomous vehicles on road networks. Proceedings of the AI 2021: Advances in Artificial Intelligence: 34th Australasian Joint Conference, Sydney, NSW, Australia.","DOI":"10.1007\/978-3-030-97546-3_20"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"e7686","DOI":"10.1002\/cpe.7686","article-title":"CCITL: A cloud-based smart traffic management protocol using intelligent traffic light system in VANETs","volume":"35","author":"Gaouar","year":"2023","journal-title":"Concurr. Comput. Pract. Exp."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"103059","DOI":"10.1016\/j.trc.2021.103059","article-title":"Network-wide traffic signal control optimization using a multi-agent deep reinforcement learning","volume":"125","author":"Li","year":"2021","journal-title":"Transp. Res. Part Emerg. Technol."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Younes, M.B., and Boukerche, A. (2013, January 9\u201313). A performance evaluation of a context-aware path recommendation protocol for vehicular ad-hoc networks. Proceedings of the 2013 IEEE Global Communications Conference (GLOBECOM), Atlanta, GA, USA.","DOI":"10.1109\/GLOCOM.2013.6831123"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Rapelli, M., Casetti, C., and Sgarbi, M. (2020, January 7\u201311). A Distributed V2V-Based Virtual Traffic Light System. Proceedings of the 2020 International Conference on COMmunication Systems and NETworkS (COMSNETS), Bangalore, India.","DOI":"10.1109\/COMSNETS48256.2020.9027339"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"50","DOI":"10.1186\/s12544-020-00440-8","article-title":"The traffic signal control problem for intersections: A review","volume":"12","author":"Eom","year":"2020","journal-title":"Eur. Transp. Res. Rev."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"17899","DOI":"10.1109\/TITS.2022.3159714","article-title":"Gain with no pain: Exploring intelligent traffic signal control for emergency vehicles","volume":"23","author":"Cao","year":"2022","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Pinto, A.C., and Mattioli, G.V. (2014). Intelligent Traffic Lights Control System Using Fuzzy Logic (No. 2014-36-0359), SAE International. SAE Technical Paper.","DOI":"10.4271\/2014-36-0359"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"431","DOI":"10.1007\/s12469-020-00235-z","article-title":"Fog-based dynamic traffic light control system for improving public transport","volume":"12","author":"Hossan","year":"2020","journal-title":"Public Transp."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1388","DOI":"10.3390\/futuretransp4040067","article-title":"Vehicular Traffic Flow Detection and Monitoring for Implementation of Smart Traffic Light: A Case Study for Road Intersection in Limeira, Brazil","volume":"4","author":"Ximenes","year":"2024","journal-title":"Future Transp."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Younes, M.B., Boukerche, A., and Mammeri, A. (2016, January 3\u20136). Context-aware traffic light self-scheduling algorithm for intelligent transportation systems. Proceedings of the 2016 IEEE Wireless Communications and Networking Conference, Doha, Qatar.","DOI":"10.1109\/WCNC.2016.7564924"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Sachan, A., and Kumar, N. (2022). Intelligent Traffic Control System for Emergency Vehicles. IoT and Analytics for Sensor Networks: Proceedings of ICWSNUCA 2021, Springer.","DOI":"10.1007\/978-981-16-2919-8_14"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"5887","DOI":"10.1109\/TVT.2015.2472367","article-title":"Intelligent traffic light controlling algorithms using vehicular networks","volume":"65","author":"Younes","year":"2015","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"24595","DOI":"10.1007\/s11042-018-7008-z","article-title":"A fog-based security framework for intelligent traffic light control system","volume":"78","author":"Khalid","year":"2019","journal-title":"Multimed. Tools Appl."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"817","DOI":"10.1016\/j.future.2017.02.017","article-title":"Secure intelligent traffic light control using fog computing","volume":"78","author":"Liu","year":"2018","journal-title":"Future Gener. Comput. Syst."},{"key":"ref_18","first-page":"1","article-title":"Intelligent traffic management system based on the internet of vehicles (IoV)","volume":"2021","author":"AlShalfan","year":"2021","journal-title":"J. Adv. Transp."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"687","DOI":"10.1016\/j.future.2019.02.029","article-title":"Security and privacy based access control model for internet of connected vehicles","volume":"97","author":"Habib","year":"2019","journal-title":"Future Gener. Comput. Syst."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Younes, M.B., and Boukerche, A. (2015, January 9\u201312). SCOOL: A secure traffic congestion control protocol for VANETs. Proceedings of the 2015 IEEE Wireless Communications and Networking Conference (WCNC), New Orleans, LA, USA.","DOI":"10.1109\/WCNC.2015.7127768"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Younes, M.B., Alonso, G.R., and Boukerche, A. (2012, January 3\u20137). A distributed infrastructure-based congestion avoidance protocol for vehicular ad hoc networks. Proceedings of the 2012 IEEE Global Communications Conference (GLOBECOM), Anaheim, CA, USA.","DOI":"10.1109\/GLOCOM.2012.6503093"},{"key":"ref_22","first-page":"1769","article-title":"A framework for dynamic smart traffic light management system","volume":"13","author":"Alharbi","year":"2021","journal-title":"Int. J. Inf. Technol."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"108656","DOI":"10.1016\/j.asoc.2022.108656","article-title":"Urban traffic light scheduling for pedestrian\u2013vehicle mixed-flow networks using discrete sine\u2013cosine algorithm and its variants","volume":"120","author":"Gupta","year":"2022","journal-title":"Appl. Soft Comput."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Sun, G., Qi, R., Liu, Y., and Xu, F. (2024). A dynamic traffic signal scheduling system based on improved greedy algorithm. PLoS ONE, 19.","DOI":"10.1371\/journal.pone.0298417"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Aleko, D.R., and Djahel, S. (2020). An efficient adaptive traffic light control system for urban road traffic congestion reduction in smart cities. Information, 11.","DOI":"10.3390\/info11020119"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"103004","DOI":"10.1109\/ACCESS.2024.3433016","article-title":"Automatic Control of Traffic Lights at Multiple Intersections Based on Artificial Intelligence and ABST Light","volume":"12","author":"Jin","year":"2024","journal-title":"IEEE Access"},{"key":"ref_27","first-page":"2464","article-title":"Traffic Management system and Traffic Light Control in Smart City to Reduce Traffic Congestion","volume":"13","author":"Wided","year":"2023","journal-title":"Int. J. Autom. Amart Technol."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"7807003","DOI":"10.1155\/hbe2\/7807003","article-title":"A New Image Encryption Method Using an Optimized Smart Codebook","volume":"2025","author":"Sihwail","year":"2025","journal-title":"Hum. Behav. Emerg. Technol."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Ibrahim, D., Sihwail, R., Arrifin, K.A.Z., Abuthawabeh, A., and Mizher, M. (2023). A novel color visual cryptography approach based on Harris Hawks Optimization Algorithm. Symmetry, 15.","DOI":"10.3390\/sym15071305"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"629","DOI":"10.1016\/j.jksuci.2019.03.008","article-title":"A simple flexible cryptosystem for meshed 3D objects and images","volume":"33","author":"Mizher","year":"2021","journal-title":"J. King Saud-Univ.-Comput. Inf. Sci."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"070004","DOI":"10.1063\/5.0174729","article-title":"A review of cybersecurity for internet-of-things based on next generation healthcare networks","volume":"2979","author":"Mizher","year":"2023","journal-title":"AIP Conf. Proc."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Said, S.O., Sihwail, R., Shehadeh, H., Hashim, I., and Alieyan, K. (2023). Hybrid Newton\u2013sperm swarm optimization algorithm for nonlinear systems. Mathematics, 11.","DOI":"10.3390\/math11061473"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1177\/0361198118756885","article-title":"Vulnerability of traffic control system under cyberattacks with falsified data","volume":"2672","author":"Feng","year":"2018","journal-title":"Transp. Res. Rec."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Chen, C., Wei, H., Xu, N., Zheng, G., Yang, M., Xiong, Y., Xu, K., and Li, Z. (2020, January 7\u201312). Toward a thousand lights: Decentralized deep reinforcement learning for large-scale traffic signal control. Proceedings of the AAAI Conference on Artificial Intelligence, New York, NY, USA.","DOI":"10.1609\/aaai.v34i04.5744"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"4919","DOI":"10.1109\/TITS.2020.2984033","article-title":"Fuzzy inference enabled deep reinforcement learning-based traffic light control for intelligent transportation system","volume":"22","author":"Kumar","year":"2020","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Zheng, G., Xiong, Y., Zang, X., Feng, J., Wei, H., Zhang, H., and Li, Z. (2019, January 3\u20137). Learning phase competition for traffic signal control. Proceedings of the 28th ACM International Conference on Information and Knowledge Management, Beijing, China.","DOI":"10.1145\/3357384.3357900"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"1243","DOI":"10.1109\/TVT.2018.2890726","article-title":"A deep reinforcement learning network for traffic light cycle control","volume":"68","author":"Liang","year":"2019","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Shinde, S.M. (2017, January 5\u20136). Adaptive traffic light control system. Proceedings of the 2017 1st International Conference on Intelligent Systems and Information Management (ICISIM), Aurangabad, India.","DOI":"10.1109\/ICISIM.2017.8122189"},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Wang, Y., Yang, X., Liang, H., and Liu, Y. (2018). A review of the self-adaptive traffic signal control system based on future traffic environment. J. Adv. Transp., 2018.","DOI":"10.1155\/2018\/1096123"},{"key":"ref_40","first-page":"753","article-title":"Intelligent traffic light flow control system using wireless sensors networks","volume":"26","author":"Yousef","year":"2010","journal-title":"J. Inf. Sci. Eng."},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Rezgui, J., Barri, M., and Gayta, R. (2019, January 17\u201319). Smart traffic light scheduling algorithms. Proceedings of the 2019 International Conference on Smart Applications, Communications and Networking (SmartNets), Sharm El Sheik, Egypt.","DOI":"10.1109\/SmartNets48225.2019.9069760"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"174","DOI":"10.1080\/23307706.2021.2024460","article-title":"Cloud assisted Internet of things intelligent transportation system and the traffic control system in the smart city","volume":"10","author":"Liu","year":"2023","journal-title":"J. Control Decis."},{"key":"ref_43","unstructured":"Yuan, S., Li, H., Han, X., Xu, G., Jiang, W., Ni, T., Zhao, Q., and Fang, Y. (2024). ITPatch: An Invisible and Triggered Physical Adversarial Patch against Traffic Sign Recognition. arXiv."},{"key":"ref_44","unstructured":"Yuan, S., Xu, G., Li, H., Zhang, R., Qian, X., Jiang, W., Cao, H., and Zhao, Q. (2025). FIGhost: Fluorescent Ink-based Stealthy and Flexible Backdoor Attacks on Physical Traffic Sign Recognition. arXiv."},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Alqarqaz, M., Younes, M.B., and Qaddoura, R. (2023). An object classification approach for autonomous vehicles using machine learning techniques. World Electr. Veh. J., 14.","DOI":"10.3390\/wevj14020041"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"558","DOI":"10.1016\/j.ins.2022.10.132","article-title":"Semantic Attribute-Based Encryption: A framework for combining ABE schemes with semantic technologies","volume":"616","author":"Arshad","year":"2022","journal-title":"Inf. Sci."},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Aldolimi, W.S., Hnaif, A.A., and Alia, M.A. (2021, January 14\u201315). Light fidelity to transfer secure data using advanced encryption standard algorithm. Proceedings of the 2021 International Conference on Information Technology (ICIT), Amman, Jordan.","DOI":"10.1109\/ICIT52682.2021.9491769"},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Rehmani, M.H., and Saleem, Y. (2015). Network simulator NS-2. Encyclopedia of Information Science and Technology, IGI Global. [3rd ed.].","DOI":"10.4018\/978-1-4666-5888-2.ch615"},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Nawej, C., Owolawi, P., and Walingo, T. (2021, January 23\u201326). Design and simulation of vanets testbed using openstreetmap, sumo, and ns-2. Proceedings of the 2021 IEEE 6th International Conference on Computer and Communication Systems (ICCCS), Chengdu, China.","DOI":"10.1109\/ICCCS52626.2021.9449197"},{"key":"ref_50","doi-asserted-by":"crossref","unstructured":"Kusari, A., Li, P., Yang, H., Punshi, N., Rasulis, M., Bogard, S., and LeBlanc, D.J. (2023, January 4\u20139). Enhancing SUMO simulator for simulation based testing and validation of autonomous vehicles. Proceedings of the 2022 IEEE Intelligent Vehicles Symposium (IV), Aachen, Germany.","DOI":"10.1109\/IV51971.2022.9827241"}],"container-title":["Big Data and Cognitive Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2504-2289\/9\/7\/169\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T17:58:59Z","timestamp":1760032739000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2504-2289\/9\/7\/169"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,6,26]]},"references-count":50,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2025,7]]}},"alternative-id":["bdcc9070169"],"URL":"https:\/\/doi.org\/10.3390\/bdcc9070169","relation":{},"ISSN":["2504-2289"],"issn-type":[{"type":"electronic","value":"2504-2289"}],"subject":[],"published":{"date-parts":[[2025,6,26]]}}}