Abstract
Requesting a service on the Internet may require the user’s privacy data, and thus raising the risk of the user’s privacy leakage and violation. Hence, it is necessary for users to select services that protect their privacy information. However, previous studies on service selection usually focused only on the quality of service, seldom had they considered the user’s privacy concern. As such, their results may be unable to meet the user’s privacy protection requirement. Aiming at reducing the privacy risk of users in service selection, this paper proposes a fuzzy logic service selection approach. The approach uses a fuzzy model to allow a service user specifying personalized privacy preference and a service provider specifying flexible privacy requirements; then it leverages the service’s reputation, privacy policy and the user’s privacy preference to compute the privacy risk for each service candidate; finally, it ranks all service candidates based on their privacy risk degrees. Examples and evaluations show that the proposed approach is effective and efficient for reducing privacy risk in service selection.
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References
Jeong, B., Cho, H., Lee, C.: On the functional quality of service (FQoS) to discover and compose interoperable web services. Expert Syst. Appl. 36(3), 5411–5418 (2009)
Wang, P.: QoS-aware web services selection with intuitionistic fuzzy set under consumer’s vague perception. Expert Syst. Appl. Part 1 369(3), 4460–4466 (2009)
Fletcher, K.K., Liu, X.F., Tang, M.: Elastic personalized non-functional attribute preference and trade-off based service selection. ACM Trans. Web (TWEB) 9(1), 1–27 (2015)
Fan, W., Yang, S., Perros, H., et al.: A multi-dimensional trust-aware cloud service selection mechanism based on evidential reasoning approach. Int. J. Autom. Comput. 12(2), 208–219 (2015)
Featherman, M.S., Miyazaki, A.D., Sprott, D.E.: Reducing online privacy risk to facilitate e-service adoption: the influence of perceived ease of use and corporate credibility. J. Serv. Mark. 24(3), 219–229 (2010)
Sweeney, L.: k-anonymity: a model for protecting privacy. Int. J. Uncertainty Fuzziness Knowl.-Based Syst. 10(5), 557–570 (2002)
Ammar, N., Malik, Z., Medjahed, B., et al.: K-anonymity based approach for privacy-preserving web service selection. In: 2015 IEEE International Conference on Web Services (ICWS), pp. 281–288. IEEE (2015)
Li, X., Jung, T.: Search me if you can: privacy-preserving location query service. In: IEEE INFOCOM 2013, Turin, Italy, 14–19 April 2013, pp. 2760–2768 (2013)
Lin, L., Liu, T., Hu, J., Ni, J.: PQsel: combining privacy with quality of service in cloud service selection. Int. J. Big Data Intell. 3(3), 202–214 (2016)
Kapitsaki, G.M.: Reflecting user privacy preferences in context-aware web services. In: IEEE 20th International Conference on Web Services (ICWS), pp. 123–130. IEEE (2013)
Squicciarini, A., Carminati, B., Karumanchi, S.: A privacy-preserving approach for web service selection and provisioning. In: 2011 IEEE International Conference on Web Services (ICWS), pp. 33–40. IEEE (2011)
Lin, L., Liu, T., Hu, J., Zhang, J.: A privacy-aware cloud service selection method toward data life-cycle. In: 20th IEEE International Conference on Parallel and Distributed Systems (ICPADS), Hsinchu, Taiwan, pp. 752–759, 16–19 December 2014
Costante, E., Paci, F., Zannone, N.: Privacy-aware web service composition and ranking. In: 2013 IEEE 20th International Conference on Web Services (ICWS), pp. 131–138. IEEE (2013)
Carminati, B., Ferrari, E., Tran, N.H.: A privacy-preserving framework for constrained choreographed service composition. In: 2015 IEEE International Conference on Web Services (ICWS), 297–304. IEEE (2015)
Squicciarini, A.C., Carminati, B., Karumanc, S.: Privacy aware service selection of composite web services. In: 9th International Conference on Collaborative Computing: Networking, Applications and Worksharing (Collaboratecom), pp. 260–268. IEEE (2013)
Tbahriti, S.-E., Ghedira, C., Medjahed, B., Mrissa, M.: Privacy-enhanced web service composition. IEEE Trans. Serv. Comput. 7(2), 210–222 (2014)
Sajjanhar, A., Hou, J., Zhang, Y.: Algorithm for web services matching. In: Yu, J.X., Lin, X., Lu, H., Zhang, Y. (eds.) APWeb 2004. LNCS, vol. 3007, pp. 665–670. Springer, Heidelberg (2004). https://doi.org/10.1007/978-3-540-24655-8_72
Opricovic, S., Tzeng, G.H.: Defuzzification within a multicriteria decision model. Int. J. Uncertainty Fuzziness Knowl.-Based Syst. 11(5), 635–652 (2003)
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The work described in this paper is supported by the National Natural Science Foundation of China under Grant Nos. 61572186 and 61572187.
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Tang, M., Zeng, S., Liu, J., Cao, B. (2017). Service Selection Based on User Privacy Risk Evaluation. In: Wang, G., Atiquzzaman, M., Yan, Z., Choo, KK. (eds) Security, Privacy, and Anonymity in Computation, Communication, and Storage. SpaCCS 2017. Lecture Notes in Computer Science(), vol 10656. Springer, Cham. https://doi.org/10.1007/978-3-319-72389-1_25
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DOI: https://doi.org/10.1007/978-3-319-72389-1_25
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