With the rapid development of intelligent transportation, carpooling with
the help of Vehicular Networks plays an important role in improving
transportation efficiency and solving
environmental problems. However, attackers usually launch attacks and
cause privacy leakage of carpooling users. In addition, the trust issue between
unfamiliar vehicles and passengers reduces the efficiency of carpooling. To
address these issues, this paper introduced a trusted and privacy-preserving carpooling matching scheme in
Vehicular Networks (TPCM). TPCM
scheme introduced travel preferences during carpooling matching, according to
the passengers’ individual travel preferences needs, which adopted the privacy set intersection technology based on the
Bloom filter to match the passengers with the vehicles to achieve the
purpose of protecting privacy and meeting
the individual needs of passengers simultaneously. TPCM scheme adopted a
multi-faceted trust management model, which calculated the trust value of different travel preferences of vehicle
based on passengers’ carpooling feedback to evaluate the vehicle’s
trustworthiness from multi-faceted when carpooling matching. Moreover, a series
of experiments were conducted to verify the effectiveness and robustness of the
proposed scheme. The results show that the proposed scheme has high accuracy,
lower computational and communication costs when compared with the existing
carpooling schemes.
References
[1]
Liu, Z., Ma, J., Weng, J., Huang, F., Wu, Y., Wei, L. and Li, Y. (2021) LPPTE: A Light-weight Privacy-Preserving Trust Evaluation Scheme for Facilitating Distributed Data Fusion in Cooperative Vehicular Safety Applications. Information Fusion, 73, 144-156. https://doi.org/10.1016/j.inffus.2021.03.003
[2]
Chang, I.C., Hung, S.N. and Yen, C.E. (2019) Designing a Dynamic Carpooling System Integrated with the VANET-Based Route-Planning Algorithm. Journal of the Chinese Institute of Engineers, 42, 132-142. https://doi.org/10.1080/02533839.2018.1552841
[3]
Wang, Y., Gu, J., Wang, S. and Wang, J. (2019) Understanding Consumers’ Willingness to Use Ride-Sharing Services: The Roles of Perceived Value and Perceived Risk. Transportation Research Part C: Emerging Technologies, 105, 504-519. https://doi.org/10.1016/j.trc.2019.05.044
[4]
Tamannaei, M. and Irandoost, I. (2019) Carpooling Problem: A New Mathematical Model, Branch-and-Bound, and Heuristic Beam Search Algorithm. Journal of Intelligent Transportation Systems, 23, 203-215. https://doi.org/10.1080/15472450.2018.1484739
[5]
Li, M., Zhu, L.H., Zhang, Z.J. and Xu, R.X. (2017) Achieving Differential Privacy of Trajectory Data Publishing in Participatory Sensing. Information Sciences, 400-401, 1-13. https://doi.org/10.1016/j.ins.2017.03.015
[6]
Sherif, A.B., Rabieh, K., Mahmoud, M.M. and Liang, X. (2016) Privacy-Preserving Ride Sharing Scheme for Autonomous Vehicles in Big Data Era. IEEE Internet of Things Journal, 4, 611-618. https://doi.org/10.1109/JIOT.2016.2569090
[7]
Yu, H., Jia, X., Zhang, H., Yu, X. and Shu, J. (2019) PSRide: Privacy-Preserving Shared Ride Matching for Online Ride Hailing Systems. IEEE Transactions on Dependable and Secure Computing, 18, 1425-1440. https://doi.org/10.1109/TDSC.2019.2931295
[8]
Wang, F., Zhu, H., Liu, X., Lu, R., Li, F., Li, H. and Zhang, S. (2018) Efficient and Privacy-Preserving Dynamic Spatial Query Scheme for Ride-Hailing Services. IEEE Transactions on Vehicular Technology, 67, 11084-11097. https://doi.org/10.1109/TVT.2018.2868869
[9]
Wernke, M., Dürr, F. and Rothermel, K. (2013) PShare: Ensuring Location Privacy in Non-Trusted Systems through Multi-Secret Sharing. Pervasive and Mobile Computing, 9, 339-352. https://doi.org/10.1016/j.pmcj.2013.01.001
[10]
Yu, H., Zhang, H., Yu, X., Du, X. and Guizani, M. (2020) PGRide: Privacy-Preserving Group Ridesharing Matching in Online Ride Hailing Services. IEEE Internet of Things Journal, 8, 5722-5735. https://doi.org/10.1109/JIOT.2020.3030274
[11]
Gruteser, M. and Grunwald, D. (2003) Anonymous Usage of Location-Based Services through Spatial and Temporal Cloaking. Proceedings of the 1st International Conference on Mobile Systems, Applications and Services, San Francisco, 5-8 May 2003, 31-42. https://doi.org/10.1145/1066116.1189037
[12]
Kou, B., Cao, S. and Lv, J. (2020, July) A Privacy Protection Scheme for Carpooling Service Using Fog Computing. Journal of Physics: Conference Series, 1601, Article ID: 032019. https://doi.org/10.1088/1742-6596/1601/3/032019
[13]
Li, M., Zhu, L. and Lin, X. (2018) Efficient and Privacy-Preserving Carpooling Using Blockchain-Assisted Vehicular Fog Computing. IEEE Internet of Things Journal, 6, 4573-4584. https://doi.org/10.1109/JIOT.2018.2868076
[14]
Tyagi, A.K. and Sreenath, N. (2016) Vehicular Ad Hoc Networks: New Challenges in Carpooling and Parking Services. International Journal of Computer Science and Information Security, 14, 13-24.
[15]
Liu, Z., Ma, J., Jiang, Z., Zhu, H. and Miao, Y. (2016) LSOT: A Lightweight Self-Organized Trust Model in VANETs. Mobile Information Systems, 2016, Article ID: 7628231. https://doi.org/10.1155/2016/7628231
[16]
Tangade, S., Manvi, S.S. and Lorenz, P. (2020) Trust Management Scheme Based on Hybrid Cryptography for Secure Communications in VANETs. IEEE Transactions on Vehicular Technology, 69, 5232-5243. https://doi.org/10.1109/TVT.2020.2981127
[17]
Jaimes, L.M.S., Ullah, K. and dos Santos Moreira, E. (2016) ARS: Anonymous Reputation System for Vehicular Ad Hoc Networks. 2016 8th IEEE Latin-American Conference on Communications (LATINCOM), Medellin, 15-17 November 2016, 1-6. https://doi.org/10.1109/LATINCOM.2016.7811600
[18]
Wang, S. and Yao, N. (2019) A RSU-Aided Distributed Trust Framework for Pseudonym-Enabled Privacy Preservation in VANETs. Wireless Networks, 25, 1099-1115. https://doi.org/10.1007/s11276-018-1681-8
[19]
Liu, Z., Guo, J., Huang, F., Cai, D., Wu, Y., Chen, X. and Konstantin Igorevich, K. (2021) Lightweight Trustworthy Message Exchange in Unmanned Aerial Vehicle Networks. IEEE Transactions on Intelligent Transportation Systems, 1-14. https://doi.org/10.1109/TITS.2021.3136304
[20]
Hallgren, P., Orlandi, C. and Sabelfeld, A. (2017) PrivatePool: Privacy-Preserving Ridesharing. 2017 IEEE 30th Computer Security Foundations Symposium (CSF), Santa Barbara, 21-25 August 2017, 276-291. https://doi.org/10.1109/CSF.2017.24
[21]
Salamanis, A., Kehagias, D.D., Tsoukalas, D. and Tzovaras, D. (2019) Reputation Assessment Mechanism for Carpooling Applications Based on Clustering User Travel Preferences. International Journal of Transportation Science and Technology, 8, 68-81. https://doi.org/10.1016/j.ijtst.2018.08.002
[22]
Caballero-Gil, C., Caballero-Gil, P., Molina-Gil, J., Martín-Fernández, F. and Loia, V. (2017) Trust-Based Cooperative Social System Applied to a Carpooling Platform for Smartphones. Sensors, 17, Article No. 245. https://doi.org/10.3390/s17020245
[23]
Baza, M., Lasla, N., Mahmoud, M., Srivastava, G. and Abdallah, M. (2019) B-Ride: Ride Sharing with Privacy-Preservation, Trust and Fair Payment Atop Public Blockchain. IEEE Transactions on Network Science and Engineering, 8, 1214-1299. https://doi.org/10.1109/TNSE.2019.2959230
[24]
Sánchez, D., Martínez, S. and Domingo-Ferrer, J. (2016) Co-Utile P2P Ridesharing via Decentralization and Reputation Management. Transportation Research Part C: Emerging Technologies, 73, 147-166. https://doi.org/10.1016/j.trc.2016.10.017
[25]
Abassi, R., Douss, A.B.C. and Sauveron, D. (2020) TSME: A Trust-Based Security Scheme for Message Exchange in Vehicular Ad Hoc Networks. Human-Centric Computing and Information Sciences, 10, Article No 43. https://doi.org/10.1186/s13673-020-00248-4
[26]
Farouk, F., Alkady, Y. and Rizk, R. (2020) Efficient Privacy-Preserving Scheme for Location Based Services in VANETSystem. IEEE Access, 8, 60101-60116. https://doi.org/10.1109/ACCESS.2020.2982636
[27]
Zhang, X. and Wang, D. (2019) Adaptive Traffic Signal Control Mechanism for Intelligent Transportation Based on a Consortium Blockchain. IEEE Access, 7, 97281-97295. https://doi.org/10.1109/ACCESS.2019.2929259
[28]
Kiss, S.Z., Hosszu, é., Tapolcai, J., Rónyai, L. and Rottenstreich, O. (2021) Bloom Filter with a False Positive Free zone. IEEE Transactions on Network and Service Management, 18, 2334-2349. https://doi.org/10.1109/TNSM.2021.3059075
[29]
Liu, Z., Huang, F., Weng, J., Cao, K., Miao, Y., Guo, J. and Wu, Y. (2020) BTMPP: Balancing Trust Management and Privacy Preservation for Emergency Message Dissemination in Vehicular Networks. IEEE Internet of Things Journal, 8, 5386-5407. https://doi.org/10.1109/JIOT.2020.3037098
[30]
Sun, G., Sun, S., Sun, J., Yu, H., Du, X. and Guizani, M. (2019) Security and Privacy Preservation in Fog-Based Crowd Sensing on the Internet of Vehicles. Journal of Network and Computer Applications, 134, 89-99. https://doi.org/10.1016/j.jnca.2019.02.018
[31]
Wang, D. and Zhang, X. (2020) Secure Ride-Sharing Services Based on a Consortium Blockchain. IEEE Internet of Things Journal, 8, 2976-2991. https://doi.org/10.1109/JIOT.2020.3023920
[32]
He, Y., Ni, J., Wang, X., Niu, B., Li, F. and Shen, X. (2018) Privacy-Preserving Partner Selection for Ride-Sharing Services. IEEE Transactions on Vehicular Technology, 67, 5994-6005. https://doi.org/10.1109/TVT.2018.2809039
