Abstract
Choosing a trusted cloud service provider (CSP) is a major challenge for cloud users (CUs) in the cloud environment, as many CSPs offer cloud services (CSs) with the same functionality. Trust evaluation of CSPs is often based on information from quality of service (QoS) monitoring and CUs’ feedback ratings. Despite the volume of feedback ratings received in trust management systems, the quality of feedback storage is very low, as many CUs do not send their feedback ratings when using CSs. Additionally, a percentage of existing feedback ratings may not be valid, since some malicious CUs send unfair feedback ratings to change the trust evaluation results. As these lead to poor data quality, the accuracy of trust evaluation results might be affected. To overcome these limitations, this paper proposes a new multi-level trust management framework, which completes previous frameworks by defining new components to improve the data quality of feedback storage. In our framework, new components were defined to solve the invalidity and sparse problems of feedback storage. Certainly, the trust assessment of CSP would be more accurate based on high-quality feedback ratings. The performance of the MLTM was evaluated using two different datasets based on a real Quality of Web Services dataset (QWS) and an artificial data set (Cloud-Armor), whose quality was reduced for the purpose of this study. Analytical values revealed that our proposed approach significantly outperformed other approaches even with the poor data quality of feedback storage.
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Notes
Quality Web Service (QWS)—http://www.uoguelph.ca/~qmahmoud/qws/ and Cloud_Armor (Feedback Web Service Cloud Armor—http://cs.adelaide.edu.au/~cloudarmor/ds.html).
References
Fareghzadeh N, Seyyedi MA, Mohsenzadeh M (2018) Dynamic performance isolation management for cloud computing services. J Supercomput 74(1):417–455
Ghavipour M, Meybodi MR (2018) Trust propagation algorithm based on learning automata for inferring local trust in online social networks. Knowl Based Syst 143:307–316
Ramachandra G, Iftikhar M, Khan FA (2017) A comprehensive survey on security in cloud computing. Procedia Comput Sci 110:465–472
Serrano D, Bouchenak S, Kouki Y, de Oliveira Jr FA, Ledoux T, Lejeune J, Sens P (2016) SLA guarantees for cloud services. Future Gener Comput Syst 54:233–246
Werner J, Westphall CM, Westphall CB (2017) Cloud identity management: a survey on privacy strategies. Comput Netw 122:29–42
Abbadi IM, Alawneh M (2012) A framework for establishing trust in the cloud. Comput Electr Eng 38(5):1073–1087
Navimipour NJ, Rahmani AM, Navin AH, Hosseinzadeh M (2015) Expert cloud: a cloud-based framework to share the knowledge and skills of human resources. Comput Hum Behav 46:57–74
Tang C, Liu J (2015) Selecting a trusted cloud service provider for your SaaS program. Comput Secur 50:60–73
Fan WJ, Yang SL, Perros H, Pei J (2015) A multi-dimensional trust-aware cloud service selection mechanism based on evidential reasoning approach. Int J Autom Comput 12(2):208–219
Chong SK, Abawajy J, Hamid IRA, Ahmad M (2014) A multilevel trust management framework for service oriented environment. Procedia Soc Behav Sci 129:396–405
Shaikh R, Sasikumar M (2015) Trust model for measuring security strength of cloud computing service. Procedia Comput Sci 45:380–389
Alhanahnah M, Bertok P, Tari Z, Alouneh S (2018) Context-aware multifaceted trust framework for evaluating trustworthiness of cloud providers. Future Gener Comput Syst 79:488–499
Fan W, Perros H (2014) A novel trust management framework for multi-cloud environments based on trust service providers. Knowl Based Syst 70:392–406
Tang M, Dai X, Liu J, Chen J (2017) Towards a trust evaluation middleware for cloud service selection. Future Gener Comput Syst 74:302–312
Shirgahi H, Mohsenzadeh M, Javadi HHS (2018) A new method of trust mirroring estimation based on social networks parameters by fuzzy system. Int J Mach Learn Cybern 9(7):1153–1168
Chiregi M, Navimipour NJ (2018) Cloud computing and trust evaluation: a systematic literature review of the state-of-the-art mechanisms. J Electr Syst Inform Technol 5(3):608–622
Cho JH, Chan K, Adali S (2015) A survey on trust modeling. ACM Comput Surv (CSUR) 48(2):1–40
Dictionary MW (2006) The Merriam-Webster dictionary. Merriam-Webster (incorporated)
Shirgahi H, Mohsenzadeh M, Haj Seyyed Javadi H (2017) Trust estimation of the semantic web using semantic web clustering. J Exp Theor Artif Intell 29(3):537–556
Mui L, Mohtashemi M, Halberstadt A (2002) A computational model of trust and reputation for E-businesses. In: HICSS’02: Proceedings of the 35th Annual Hawaii International Conference on System Sciences (HICSS’02). IEEE Computer Society, 188
Rizvi S, Karpinski K, Kelly B, Walker T (2015) Utilizing third party auditing to manage trust in the cloud. Procedia Comput Sci 61:191–197
Singh S, Sidhu J (2017) Compliance-based multi-dimensional trust evaluation system for determining trustworthiness of cloud service providers. Future Gener Comput Syst 67:109–132
Vu LH, Hauswirth M, Aberer K (2005) QoS-based service selection and ranking with trust and reputation management. In: OTM Confederated International Conferences “On the Move to Meaningful Internet Systems”. Springer, Berlin, pp 466–483
Yau SS, Huang J, Yin Y (2010) Improving the trustworthiness of service QoS information in service-based systems. In: International Conference on Autonomic and Trusted Computing. Springer, Berlin, pp 208–218
He Q, Yan J, Jin H, Yang Y (2009) ServiceTrust: supporting reputation-oriented service selection. In: Service-Oriented Computing. Springer, Berlin, pp 269–284
Muchahari MK, Sinha SK (2012) A new trust management architecture for cloud computing environment. In: 2012 International Symposium on Cloud and Services Computing. IEEE, pp 136–140
Alhamad M, Dillon T, Chang E (2010) Sla-based trust model for cloud computing. In: 2010 13th international conference on network-based information systems, Sept 2010. IEEE, pp 321–324
Habib SM, Ries S, Muhlhauser M (2010) Cloud computing landscape and research challenges regarding trust and reputation. In: 2010 7th International Conference on Ubiquitous Intelligence and Computing and 7th International Conference on Autonomic and Trusted Computing. IEEE, pp 410–415
Trapero R, Modic J, Stopar M, Taha A, Suri N (2017) A novel approach to manage cloud security SLA incidents. Future Generat Comput Syst 72:193–205
Siadat S, Rahmani AM, Navid H (2017) Identifying fake feedback in cloud trust management systems using feedback evaluation component and Bayesian game model. J Supercomput 73(6):2682–2704
Koren Y, Bell R, Volinsky C (2009) Matrix factorization techniques for recommender systems. Computer 42(8):30–37
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Aghaee Ghazvini, G., Mohsenzadeh, M., Nasiri, R. et al. A new multi-level trust management framework (MLTM) for solving the invalidity and sparse problems of user feedback ratings in cloud environments. J Supercomput 77, 2326–2354 (2021). https://doi.org/10.1007/s11227-020-03348-1
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DOI: https://doi.org/10.1007/s11227-020-03348-1