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Open Access

Meet-Cloud for Secure and Accurate Distribution of Negative Messages in Vehicular Ad hoc Network

School of Computer and Electronic Information, Guangxi University, Nanning 530004, China.
Department of Computer Science, Virginia Commonwealth University, Richmond, VA 23220, USA.
School of Computer Engineering and Applied Mathematics, Changsha University, Changsha 410003, China.
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Abstract

Keeping Vehicular Ad hoc Network (VANET) from attacks requires secure and efficient distribution of information about bad entities. Negative messages are pieces of information that define the negative attributes of vehicles. By formally defining the negative message, we observe that accuracy is essential for its efficient distribution. We formally define the coverage percentage and accurate coverage percentage to describe the availability and distribution efficiency of negative message. These two metrics can jointly evaluate the performance of a distribution method. To obtain both high coverage percentage and high accurate coverage percentage, we propose meet-cloud, a scheme based on meet-table and cloud computing to securely and accurately distribute negative messages in VANET. A meet-table in a Road Side Unit (RSU) records the vehicles it encounters. All meet-tables are sent to cloud service to aggregate a global meet-table. The algorithm for distributing and redistributing negative messages are designed. Security analysis shows that meet-cloud is secure against fake and holding on to negative message attacks. Simulations and analysis demonstrate that meet-cloud is secure under denial of service and fake meet-table attacks. The simulation results also justify that meet-cloud outperforms the RSU broadcast and epidemic model.

References

[1]
M. S. Kakkasageri and S. S. Manvi, Information management in vehicular ad hoc networks: A review, J. Netw. Comput. Appl., vol. 39, pp. 334-350, 2014.
[2]
H. Z. Zhu, M. L. Li, L. Y. Fu, G. T. Xue, Y. M. Zhu, and L. M. Ni, Impact of traffic influxes: Revealing exponential intercontact time in urban VANETs, IEEE Trans. Parallel Distrib. Syst., vol. 22, no. 8, pp. 1258-1266, 2011.
[3]
P. B. Farradyne, Vehicle Infrastructure Integration-VII Architecture and Functional Requirements, v1.0. 2005; http://ral.ucar.edu/project/vii.old/vii/docs/VIIArchandFuncRequirements.pdf.
[4]
J. J. Haas, Y. C. Hu, and K. P. Laberteaux, Efficient certificate revocation list organization and distribution, IEEE J. Sel. Areas Commun., vol. 29, no. 3, pp. 595-604, 2011.
[5]
B. H. Huang, J. W. Mo, Q. Lu, and W. Cheng, Optimizing propagation network of certificate revocation in VANET with meet-table, in Proc. 4th Int. Workshop on Network Optimization and Performance Evaluation, Zhangjiajie, China, 2016, pp. 147-154.
[6]
M. C. González, C. A. Hidalgo, and A. L. Barabási, Understanding individual human mobility patterns, Nature, vol. 453, no. 7196, pp. 779-782, 2008.
[7]
B. H. Huang and W. Cheng, Distributing negative messages in VANET based on meet-table and cloud computing, in Proc. 12th Int. Conf. on Wireless Algorithms, Systems, and Applications, Guilin, China, 2017, pp. 653-664.
[8]
R. Cattell, Scalable SQL and NoSQL data stores, ACM SIGMOD Rec., vol. 39, no. 4, pp. 12-27, 2010.
[9]
X. B. Tian, B. H. Huang, and M. Wu, A transparent middleware for encrypting data in MongoDB, in Peoc. 2014 IEEE Workshop on Electronics, Computer and Applications, Ottawa, Canada, 2014, pp. 906-909.
[10]
L. Yu, H. Y. Shen, K. Sapra, L. Ye, and Z. P. Cai, CoRE: Cooperative end-to-end traffic redundancy elimination for reducing cloud bandwidth cost, IEEE Trans. Parallel Distrib. Syst., vol. 28, no. 2, pp. 446-461, 2017.
[11]
L. Yu and Z. P. Cai, Dynamic scaling of virtual clusters with bandwidth guarantee in cloud datacenters, in Proc. 35th Annu. IEEE Int. Conf. on Computer Communications, San Francisco, CA, USA, 2016, pp. 1-9.
[12]
E. Ndashimye, S. K. Ray, N. I. Sarkar, and J. A. Gutiérrez, Vehicle-to-infrastructure communication over multi-tier heterogeneous networks: A survey, Comput. Netw., vol. 112, pp. 144-166, 2017.
[13]
T. Bouali, S. M. Senouci, and H. Sedjelmaci, A distributed detection and prevention scheme from malicious nodes in vehicular networks, Int. J. Commun. Syst., vol. 29, no. 10, pp. 1683-1704, 2016.
[14]
J. X. Ding, J. Gao, and H. Xiong, Understanding and modelling information dissemination patterns in vehicle-to-vehicle networks, in Proc. 23rd SIGSPATIAL Int. Conf. on Advances in Geographic Information Systems, Seattle, Washington, DC, USA, 2015, p. 41.
[15]
V. Naumov, R. Baumann, and T. Gross, An evaluation of inter-vehicle ad hoc networks based on realistic vehicular traces, in Proc. 7th ACM Int. Symposium on Mobile ad Hoc Networking and Computing, Florence, Italy, 2006, pp. 108-119.
[16]
San Francisco Municipal Transportation Agency, San Francisco transportation fact sheet, 2013, https://www.sfmta.com/sites/default/files/2013%20SAN%20FRANCISCO%20TRANSPORTATION%20FACT%20SHEET.pdf.
[17]
[18]
R. G. Engoulou, M. Bellaïche, S. Pierre, and A. Quintero, VANET security surveys, Comput. Commun., vol. 44, pp. 1-13, 2014.
[19]
S. Chokhani, Toward a national public key infrastructure, IEEE Commun. Mag., vol. 32, no. 9, pp. 70-74, 1994.
[20]
Y. S. Yeh, W. S. Lai, and C. J. Cheng, Applying lightweight directory access protocol service on session certification authority, Computr. Netw., vol. 38, no. 5, pp. 675-692, 2002.
[21]
T. P. Hormann, K. Wrona, and S. Holtmanns, Evaluation of certificate validation mechanisms, Comput. Commun., vol. 29, no. 3, pp. 291-305, 2006.
[22]
F. D. Cunha, A. C. Vianna, R. A. F. Mini, and A. A. F. Loureiro, Are vehicular networks small world?, in Proc. 2014 IEEE Conf. on Computer Communications Workshops, Toronto, Canada, 2014, pp. 195-196.
[23]
H. Zhang and J. Li, Modeling and dynamical topology properties of VANET based on complex networks theory, AIP Adv., vol. 5, p. 017150, 2015.
[24]
X. J. Wang, L. J. Guo, C. Y. Ai, J. B. Li, and Z. P. Cai, An urban area-oriented traffic information query strategy in VANETs, in Proc. 8th Int. Conf. on Wireless Algorithms, Systems, and Applications, Zhangjiajie, China, 2013, pp. 313-324.
[25]
F. Bonomi, R. Milito, J. Zhu, and S. Addepalli, Fog computing and its role in the internet of things, in Proc. 1st Edition of the MCC Workshop on Mobile Cloud Computing, Helsinki, Finland, 2012, pp. 13-16.
[26]
V. G. Menon, Moving from vehicular cloud computing to vehicular fog computing: Issues and challenges, Int. J. Comput. Sci. Eng., vol. 9, no. 2, pp. 14-18, 2017.
Tsinghua Science and Technology
Pages 377-388
Cite this article:
Huang B, Cheng X, Huang C, et al. Meet-Cloud for Secure and Accurate Distribution of Negative Messages in Vehicular Ad hoc Network. Tsinghua Science and Technology, 2018, 23(4): 377-388. https://doi.org/10.26599/TST.2018.9010016

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Received: 28 July 2017
Accepted: 14 September 2017
Published: 16 August 2018
© The authors 2018
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