Distributed Anonymity Based on Blockchain in Vehicular Ad Hoc Network by Block Size Calibrating
Keywords:
blockchain, VANET, security, anonymity, cryptographyAbstract
The network connectivity problem is one of the critical challenges of an anonymous server implementation in the VANET. The objective and main contribution of this paper are to assure the anonymity in VANET environments. In the proposed blockchain method, before packaging transactions into blocks, anonymity risk reduced through techniques such as k-anonymity, graph processing, dummy node, and silence period. This paper addresses the challenges of anonymous servers, such as update challenges and single point of failure, by exploiting append-only, distributed, and anonymity features. Although mounting the blockchain process with asymmetric cryptography solves the connectivity challenge, start-up delay and network overhead are severe. The significant feature of the proposed method solves this delay challenge by aggregating many transactions into a block and fixing constraint range of multicasting blocks. Also, aggregating transactions of various end-users into a block preserves the path anonymity. The asymmetric cryptography with ring public and private keys protects the identity anonymity as well as unlinkability. The robust anonymity mechanism existence and the traceability of all transactions constitute the main advantages of the proposed method. The simulation is running by the python to evaluate blockchain performance in VANET with connectivity failure and rapidly changing topology. The results indicate the stabilization of the proposed method in the VANET environment.
References
. B. Zhou, J. Pei, and W. Luk, “A brief survey on anonymization techniques for privacy preserving publishing of social network data,” ACM Sigkdd Explor. Newsl., vol. 10, no. 2, pp. 12–22, 2008.
. P. Shi, L. Xiong, and B. Fung, “Anonymizing data with quasi-sensitive attribute values,” in Proceedings of the 19th ACM international conference on Information and knowledge management, 2010, pp. 1389–1392.
. X. Liu, H. Zhao, M. Pan, H. Yue, X. Li, and Y. Fang, “Traffic-aware multiple mix zone placement for protecting location privacy,” in INFOCOM, 2012 Proceedings IEEE, 2012, pp. 972–980.
. K. Miura and F. Sato, “Evaluation of a hybrid method of user location anonymization,” in Proceedings 8th International Conference on Broadband, Wireless Computing, Communication and Applications, BWCCA, 2013, pp. 191–198.
. R. Al-Dhubhani and J. M. Cazalas, “An adaptive geo-indistinguishability mechanism for continuous LBS queries,” Wirel. Networks, pp. 1–19, 2017.
. A. K. Tyagi and N. Sreenath, “Location privacy preserving techniques for location based services over road networks,” in International Conference on Communications and Signal Processing (ICCSP), 2015, pp. 1319–1326.
. I. Memon, L. Chen, Q. A. Arain, H. Memon, and G. Chen, “Pseudonym changing strategy with multiple mix zones for trajectory privacy protection in road networks,” Int. J. Commun. Syst., vol. 31, no. 1, 2018.
. Q. A. Arain et al., “Privacy preserving dynamic pseudonym-based multiple mix-zones authentication protocol over road networks,” Wirel. Pers. Commun., vol. 95, no. 2, pp. 505–521, 2017.
. S. Zakhary and A. Benslimane, “On location-privacy in opportunistic mobile networks, a survey,” J. Netw. Comput. Appl., vol. 103, pp. 157–170, 2018.
. G. P. Corser, A. Banihani, J. Cox, R. Hoque, H. Fu, and Y. Zhu, “Location Privacy, Application Overhead and Congestion in VANET Location Based Services,” in Big Data Security on Cloud (BigDataSecurity), IEEE International Conference on High Performance and Smart Computing (HPSC), and IEEE International Conference on Intelligent Data and Security (IDS), 2017 IEEE 3rd International Conference on, 2017, pp. 243–248.
. P. Mahapatra and A. Naveena, “Enhancing Identity Based Batch Verification Scheme for Security and Privacy in VANET,” in Advance Computing Conference (IACC), 2017 IEEE 7th International, 2017, pp. 391–396.
. K. Logeshwari and L. Lakshmanan, “Authenticated anonymous secure on demand routing protocol in VANET (Vehicular adhoc network),” in Information Communication and Embedded Systems (ICICES), 2017 International Conference on, 2017, pp. 1–7.
. C. Zuo, K. Liang, Z. L. Jiang, J. Shao, and J. Fang, “Cost-effective privacy-preserving vehicular urban sensing system,” Pers. Ubiquitous Comput., vol. 21, no. 5, pp. 893–901, 2017.
. Z. Lu, W. Liu, Q. Wang, G. Qu, and Z. Liu, “A privacy-preserving trust model based on blockchain for vanets,” IEEE Access, vol. 6, pp. 45655–45664, 2018.
. R. Shrestha, R. Bajracharya, A. P. Shrestha, and S. Y. Nam, “A new-type of blockchain for secure message exchange in VANET,” Digit. Commun. Networks, 2019.
. S. Alboaie, D. Cosovan, L.-D. Chiorean, and M. F. Vaida, “Lamport n-time signature scheme,” in 2018 IEEE International Conference on Automation, Quality and Testing, Robotics (AQTR), 2018, pp. 1–6.
. S. Haber and W. S. Stornetta, “How to time-stamp a digital document,” in Conference on the Theory and Application of Cryptography, 1990, pp. 437–455.
. D. Bayer, S. Haber, and W. S. Stornetta, “Improving the efficiency and reliability of digital time-stamping,” in Sequences II, Springer, 1993, pp. 329–334.
. A. Kiayias and A. Mitrofanova, “Financial Cryptography and Data Security,” Lect. Notes Comput. Sci., vol. 3570, pp. 109–124, 2005.
. E. C. Ferrer, “The blockchain: a new framework for robotic swarm systems,” in Proceedings of the Future Technologies Conference, 2018, pp. 1037–1058.
. L. Baird, M. Harmon, and P. Madsen, “Hedera: A Governing Council & Public Hashgraph Network.” 2018.
. L. Baird, “The swirlds hashgraph consensus algorithm: Fair, fast, byzantine fault tolerance,” Swirlds, Inc. Tech. Rep. SWIRLDS-TR-2016, vol. 1, 2016.
. B. Leiding, P. Memarmoshrefi, and D. Hogrefe, “Self-managed and blockchain-based vehicular ad-hoc networks,” in Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct, 2016, pp. 137–140.
. L. Li et al., “CreditCoin: A privacy-preserving blockchain-based incentive announcement network for communications of smart vehicles,” IEEE Trans. Intell. Transp. Syst., vol. 19, no. 7, pp. 2204–2220, 2018.
. A. Dorri, M. Steger, S. S. Kanhere, and R. Jurdak, “Blockchain: A distributed solution to automotive security and privacy,” IEEE Commun. Mag., vol. 55, no. 12, pp. 119–125, 2017.
. S. Rowan, M. Clear, M. Huggard, and C. Mc Goldrick, “Securing vehicle to vehicle data sharing using blockchain through visible light and acoustic side-channels,” arXiv preprint arXiv:1704.02553. eprint.
. M. Singh and S. Kim, “Blockchain based intelligent vehicle data sharing framework,” arXiv Prepr. arXiv1708.09721, 2017.
. M. Yuan, L. Chen, S. Y. Philip, and T. Yu, “Protecting sensitive labels in social network data anonymization,” IEEE Trans. Knowl. Data Eng., vol. 25, no. 3, pp. 633–647, 2013.
. P. Samarati and L. Sweeney, “Protecting privacy when disclosing information: k-anonymity and its enforcement through generalization and suppression,” technical report, SRI International, 1998.
. N. Li, T. Li, and S. Venkatasubramanian, “t-closeness: Privacy beyond k-anonymity and l-diversity,” in Data Engineering, 2007. ICDE 2007. IEEE 23rd International Conference on, 2007, pp. 106–115.
. X. Wang et al., “Survey on blockchain for Internet of Things,” Comput. Commun., 2019.
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