ServiceTrust: Trust Management in Service Provision Networks

Su, Zhiyuan; Liu, Ling; Li, Mingchu; Fan, Xinxin; Zhou, Yang

doi:10.1109/scc.2013.31

Cited by 32 publications

(54 citation statements)

References 10 publications

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“…Unfortunately, as we show in this paper that the trust model in [Su, et al 2013] is severely handicapped and is vulnerable to malicious spies with camouflage or colluding collectives. This observation motivates us to develop ServiceTrust ++ to against the six threat models by incorporating the above-mentioned three unique features.…”

Section: Introductionmentioning

confidence: 93%

“…Moreover, by using trust propagation with uniform distribution in global trust computation, the benefit of feedback similarity weighted local trust is further decreased because malicious peers acting as spies or camouflage can continue to gain higher global trust by collecting local trust values from good peers. For example, our experiments in Section 4.5 show that trust propagation with uniform distribution are vulnerable under Threat model E and Threat model F even for the trust model in [Su, et al 2013] where feedback similarity is utilized in local trust computation.…”

Section: Global Trust Computation By Controlled Propagationmentioning

confidence: 99%

“…Most of the existing works, even those in recent years [Kuter, et al 2010, Guha, et al 2004, Ortega, et al 2012, Su et al 2013, are based on the uniform trust propagation model for addressing the rating sparsity problems and malicious collective problems in trust and reputation management. However, we argue that trust and reputation in real world never follow the uniform propagation model.…”

Section: Conditional Trust Propagation Based On Rating Similarity Thrmentioning

confidence: 99%

“…1 most cited trust model in the literature of trust and reputation management. Second, although there are many existing trust models in the literature, none to date except ServiceTrust [Su, et al 2013] has shown to prevail over EigenTrust [Kamvar, et al 2003] in terms of attack resilience against the four attack models used by EigenTrust. Third, ServiceTrust in [Su, et al 2013] is a result of our early research on attack resilient trust management.…”

Section: Experimental Evaluationmentioning

confidence: 99%

“…It is worth noting that our preliminary work in [Su, et al 2013] is limited to countering the basic four attack models by employing feedback similarity into the local trust computation. Unfortunately, as we show in this paper that the trust model in [Su, et al 2013] is severely handicapped and is vulnerable to malicious spies with camouflage or colluding collectives.…”

Section: Introductionmentioning

confidence: 99%

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Reliable and Resilient Trust Management in Distributed Service Provision Networks

Liu

et al. 2015

ACM Trans. Web

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Distributed service networks are popular platforms for service providers to offer services to consumers and for service consumers to acquire services from unknown parties. eBay and Amazon are two well-known examples of enabling and hosting such service networks to connect service providers to service consumers. Trust management is a critical component for scaling such distributed service networks to a large and growing number of participants. In this paper, we present ServiceTrust ++ , a feedback quality sensitive and attack resilient trust management scheme for empowering distributed service networks with effective trust management capability. Comparing with existing trust models, ServiceTrust ++ has several novel features. First, we present six attack models to capture both independent and colluding attacks with malicious cliques, malicious spies and malicious camouflages. Second, we aggregate the feedback ratings based on the variances of participants' feedback behaviors and incorporate feedback similarity as weight into the local trust algorithm. Third, we compute the global trust of a participant by employing conditional trust propagation based on feedback similarity threshold. This allows ServiceTrust ++ to control and prevent malicious spies and malicious camouflage peers to boost their global trust scores by manipulating the feedback ratings of good peers and by taking advantage of the uniform trust propagation. Finally, we systematically combine trust decaying strategy with threshold-value based conditional trust propagation to further strengthen the robustness of our global trust computation against sophisticated malicious feedbacks. Experimental evaluation with both simulation-based networks and real network dataset Epinion show that ServiceTrust ++ is highly resilient against all six attack models and highly effective compared to EigenTrust, the most popular and representative trust propagation model to date.

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Section: Introductionmentioning

confidence: 93%

Section: Global Trust Computation By Controlled Propagationmentioning

confidence: 99%

Section: Conditional Trust Propagation Based On Rating Similarity Thrmentioning

confidence: 99%

Section: Experimental Evaluationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Reliable and Resilient Trust Management in Distributed Service Provision Networks

Liu

et al. 2015

ACM Trans. Web

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A survey of the state‐of‐the‐art approaches for evaluating trust in software ecosystems

Hou,

Jansen

2024

J Software Evolu Process

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Third‐party software has streamlined the software engineering process, allowed software engineers to focus on developing more advanced components, and reduced time and cost. This shift has led to software development strategies moving from competition to collaboration, resulting in the concept of software ecosystems, in which internal and external actors work together on shared platforms and place their trust in the ecosystem. However, the increase in shared components has also created challenges, especially in security, as the large dependency trees significantly enlarge a system's attack surface. The situation is made worse by the lack of effective ways to measure and ensure the trustworthiness of these components. In this article, we explore current approaches used to evaluate trust in software ecosystems, focusing on analyzing the specific techniques utilized, the primary factors in trust evaluation, the diverse formats for result presentation, as well as the software ecosystem entities considered in the approaches. Our goal is to provide the status of current trust evaluation approaches, including their limitations. We identify key challenges, including the limited coverage of software ecosystem entities; the objectivity, universality, and environmental impacts of the evaluation approaches; the risk assessment for the evaluation approaches; and the security attacks posed by trust evaluation in these approaches.

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