Trust and Privacy Enabled Service Composition Using Social Experience

Mokarizadeh, Shahab; Dokoohaki, Nima; Matskin, Mihhail; Küngas, Peep

doi:10.1007/978-3-642-16283-1_26

Cited by 10 publications

(6 citation statements)

References 17 publications

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“…Mokarizadeh et al in [21] propose to use service reputation scores for improving the quality of automatic service selection and composition. They assess the reputation of a service based on analysing relationships in a social network model.…”

Section: H Threats To Validitymentioning

confidence: 99%

Reputation Evaluation with Malicious Feedback Prevention Using a HITS-Based Model

Tibermacine¹,

Tibermacine²,

Kerdoudi

2019

2019 IEEE International Conference on Web Services (ICWS)

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The reputation of web services is calculated by aggregating user feedback ratings. Though reputation is a subjective metric, it can be considered as a good indicator about services Quality of Experience, and henceforth, it can be used for recommending services in an open ecosystem. In this work, we propose a three-phase process for evaluating web service reputation by aggregating user feedback ratings. The relationship between users and services is modeled as a bipartite graph where an adapted HITS (Hypertext Induced Topic Search) algorithm is employed to distinguish between honest and malicious users in Phase I. Then, this model is used to evaluate, in Phase III, the reputation of web services from user ratings after punishing malicious users in Phase II. An experiment on a dataset of real Web services was conducted to validate the effectiveness of the proposed model in evaluating Web service reputation.

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Section: H Threats To Validitymentioning

confidence: 99%

Reputation Evaluation with Malicious Feedback Prevention Using a HITS-Based Model

Tibermacine¹,

Tibermacine²,

Kerdoudi

2019

2019 IEEE International Conference on Web Services (ICWS)

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“…Hence, the notion of trust becomes necessary to filter this big data [20]. Because the user's experience is vulnerable to his malicious manipulation [21], only the experience provided by trusted users should be taken into account. Based on this assumption, some research studies [22,23] have focused on users' interactions to compute the social trust by combining with other factors namely the interest similarity [24], the users' proximity [25,26].…”

Section: Context and Problem Statementmentioning

confidence: 99%

Social collaborative service recommendation approach based on user’s trust and domain-specific expertise

Kalaï

Zayani

Amous

et al. 2018

Future Generation Computer Systems

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“…Mokarizadeh et al presented in a framework for selecting WSs for service orchestration using the trustworthiness of the former as a measurement of their quality. Such trustworthiness, in turn, is computed using the reputation scores provided by different users' profiles, and such profiles are extracted from social networks storing the previous experiences of those users with the services.…”

Section: Survey On Reputation‐based Web Service Orchestrationmentioning

confidence: 99%

Reputation‐based Web service orchestration in cloud computing: A survey

Mármol¹,

Kuhnen²

2013

Concurrency and Computation

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Cloud computing is no longer the future but the present. Every day, more and more companies and service providers transfer their businesses and operations to the cloud, benefiting from its multiple advantages. Moreover, the flexibility offered by many cloud services allows to easily build sophisticated services by just composing simpler ones, rather than creating them from zero. Yet, to mitigate potential security threats and keep the maximum performance at any time, a smart selection of those composite services constitutes a key aspect. In this paper, we introduce the reader to the problem of Web service selection based on their reputation scores and subsequently present a survey on some of the most relevant reputation-based Web service orchestration schemes for cloud computing in the literature. For each one of these approaches, a thorough analysis of their pros and cons has been performed, providing a comprehensive comparison amongst all of them leading to the conclusion that, to the best of our knowledge, there is no one single model elegantly fitting to each and every situation that could occur in such a dynamic environment like cloud computing. Finally, we present some current challenges and future research trends in the field of reputation-based service orchestration in cloud computing.Yet, to create a successful composite service, such as when building a puzzle, the correct pieces need to be chosen. For one or another reason (failure, malware, exhausted resources, etc), the individual services composing the bigger one might unexpectedly change their behaviour throughout time [10,11], degrading their performance (and, in turn, the performance of the composite service) or even constituting a security threat or breach. Therefore, it is a wise strategy not to base a composite service on fixed simpler ones, but rather making the latter replaceable whenever needed in order to keep always the maximum performance and level of assurance.Trust and reputation management has emerged in the last years as a smart and accurate solution to tackle these issues [12][13][14][15]. Actually those systems have been widely accepted and deployed, finding them in a multitude of different environments and scenarios [16,17]. This appealing area of knowledge has captured the attention of both industry and academia, leading to several successful products [13] and patents [18][19][20][21][22][23].In this paper, we performed a survey of some of the main research approaches dealing with the problem of reputation-based Web service (WS) orchestration for cloud computing environments. We described each of those solutions, thoroughly analysing their advantages and shortcomings. Moreover, a comprehensive comparative amongst them led us to the conclusion that none of the studied models gracefully fits to each and every situation that could emerge in a highly dynamic environment such as cloud computing. Finally, we also studied some current research challenges, as well as future trends in the field of reputation-based service orchestration in ...

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Trust and Privacy Enabled Service Composition Using Social Experience

Cited by 10 publications

References 17 publications

Reputation Evaluation with Malicious Feedback Prevention Using a HITS-Based Model

Reputation Evaluation with Malicious Feedback Prevention Using a HITS-Based Model

Social collaborative service recommendation approach based on user’s trust and domain-specific expertise

Reputation‐based Web service orchestration in cloud computing: A survey

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