Abstract
The flexibility and convenience of mobile commerce is more in line with the needs of e-commerce in the new era, but it also brings a series of unique security issues in the mobile environment. The serious information asymmetry between the two sides of the transaction creates more opportunities for fraud. This has caused consumers to lose trust in the mobile commerce market. The phenomenon of mobile commerce fraud and lack of trust has become one of the main factors hindering the development of mobile commerce. The paper proposes a dynamic trust computing model which is based on mobile agent, which realizes the qualitative and quantitative conversion of trust. To stop malicious users from credit hype and deception, a special attribute evaluation method and trust punishment method are proposed. The new user trust degree assignment method has been improved, and a method of dynamically setting the initial trust degree of new users based on the minimum trust degree of the previous system is proposed, which resists the ruin behavior of abandoning the reputation data at random. By adopting the transaction evaluation system and weights. The system introduces a multi-factor mechanism. The model better reflects the influence of subjective factors such as individual preference and risk attitude on trust calculation, and enhances the sensitivity of trust algorithm in trading individual attributes. Detailed theoretical analysis and a large number of simulation experiments verify the mechanism can solve the problem of trust computing in mobile network transactions.
Keywords
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
China Internet Network Information Center: The 41st Statistical Report on the Development of China’s Internet. http://www.cac.gov.cn/2018-01/31/c_1122347026.htm. http://www.cac.gov.cn/2018-01/31/c_1122346138.htm (2018)
Ae, K.Y., Rasik, P.: A trust prediction framework in rating-based on experience sharing social networks without a Web of Trust. Inf. Sci. 191(3), 128–145 (2012)
Nan, H., Ling, L., Sambamurthy, V.: Fraud detection in online consumer reviews. Decis. Support Syst. 50(3), 614–626 (2011)
Zhang, Z.Q., Xie, X.Q., et al.: CRank: a credit assessment model in C2C e-Commerce. Inf. Syst. Dev. 5, 333–343 (2011)
Yun, Y.: C2C transactions in the dynamic credit evaluation model. Inf. Sci. 28(4), 563–566 (2010)
Yaghoubi, N.: Trust models in e-Business: analytical-compare approach. Interdiscip. J. Contemp. Res. Bus. 2(9), 398–416 (2011)
Zhang, X.: A strengthening of security solutions C2C transaction integrity. Microelectron. Comput. 27(5), 194–198 (2010)
Marsh, S.: Formalising trust as a computational concept. Ph.D. thesis, University of Stirling (1994)
Blaze, M., Feigenbaum, J., Lacy, J.: Decentralized trust management. In: Proceedings of the Symposium on Security and Privacy, Oakland, pp. 164–173 (1996)
Blaze, M., Feigenbaum, J., Keromytis, A.D.: Keynote: trust management for public-key infrastructures. In: Proceedings of the 1998 Security Protocols International Workshop, Cambridge, England, pp. 59–63 (1998)
Griffiths, N.: Task delegation using experience based multi-dimensional trust. In: Proceedings of the 4th International Joint Conference on Autonomous Agents and Multiagent Systems, Netherlands, pp. 489–496. ACM Press, London (2005)
Zhang, Q., Zhang, X., Wen, X.Z., Liu, J.R., Ting, S.: Construction of peer-to-peer multiple-grain trust model. J. Softw. 17(1), 96–107 (2006)
Wang, X., Liang, P., Ma, H., Xing, D., Wang, B.: A P2P trust model based on multi-dimensional trust evaluation. In: Li, K., Fei, M., Irwin, G.W., Ma, S. (eds.) LSMS 2007. LNCS, vol. 4688, pp. 347–356. Springer, Heidelberg (2007). https://doi.org/10.1007/978-3-540-74769-7_38
Guo, L., Yang, S., Wang, J., Zhou, J.: Trust model based on similarity measure of vectors in P2P networks. In: Zhuge, H., Fox, Geoffrey C. (eds.) GCC 2005. LNCS, vol. 3795, pp. 836–847. Springer, Heidelberg (2005). https://doi.org/10.1007/11590354_103
Reece, S., Rogers, A., Roberts, S., Jennings, N.R.: Rumours and reputation: evaluating multi-dimensional trust within a decentralized reputation system. In: Proceedings of the 6th International Joint Conference on Autonomous Agents and Multiagent Systems, pp. 1–8. ACM Press, Honolulu (2007)
Reece, S., Roberts, S., Rogers, A., Jennings, N.R.: A multi-dimensional trust model for heterogeneous contract observations. In: Proceedings of the 22th AAAI Conference on Artificial Intelligence, pp. 128–135. AAAI Press, London (2007)
Wang, S., Zhang, L., Li, H.-S.: Evaluation approach of subjective trust based on cloud model. J. Softw. 21(6), 1341–1352 (2010)
Shao, K., Luo, F., Mei, N.X., Liu, Z.T.: Normal distribution based dynamical recommendation trust model. J. Softw. 23(12), 3130–3148 (2012). http://www.jos.org.cn/1000-9825/4204.htm. (in Chinese)
Ashtiani, M., Azgomi, M.A.: Trust modeling based on a combination of fuzzy analytic hierarchy process and fuzzy VIKOR. Soft Comput. 20(1), 399–421 (2016)
Wu, T., Xiao, J., Qin, K., et al.: Cloud model-based method for range constrained thresholding. Comput. Electr. Eng. 42(2), 33–48 (2015)
McCole, P., Ramsey, E., Williams, J.: Trust considerations on attitudes towards online purchasing: the moderating effect of privacy and security concerns. J. Bus. Res. 63(9/10), 1018–1024 (2010)
Jun, X.: Survey of trust model based on uncertainty theory. J. Chin. Comput. Syst. 38(1), 99–106 (2017)
Jiang, W., Xu, Y., Guo, H., Zhang, L.: Multi agent system-based dynamic trust calculation model and credit management mechanism of online trading. Sci. China Inf. Sci. 44(9), 1084–1101 (2014)
Acknowledgement
Thanks to the online transaction data provided by Taobao Kaiwen Fila billion store. Thanks to the valuable comments from the review experts, which will improve the quality of this article. This work was supported by the National Natural Science Foundation of China (61472136; 61772196), the Hunan Provincial Focus Social Science Fund (2016ZDB006), Hunan Provincial Social Science Achievement Review Committee results appraisal identification project (Xiang social assessment 2016JD05) The authors gratefully acknowledge the financial support provided by the Key Laboratory of Hunan Province for New Retail Virtual Reality Technology (2017TP1026).
Author information
Authors and Affiliations
Corresponding authors
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Jiang, WJ., Chen, JH., Xu, YH., Wang, Y. (2019). Mobile Agent-Based Mobile Intelligent Business Security Transaction Model. In: Sun, Y., Lu, T., Xie, X., Gao, L., Fan, H. (eds) Computer Supported Cooperative Work and Social Computing. ChineseCSCW 2018. Communications in Computer and Information Science, vol 917. Springer, Singapore. https://doi.org/10.1007/978-981-13-3044-5_4
Download citation
DOI: https://doi.org/10.1007/978-981-13-3044-5_4
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-13-3043-8
Online ISBN: 978-981-13-3044-5
eBook Packages: Computer ScienceComputer Science (R0)