Trust Type Based Semantic Web Services Assessment and Selection

Kim, Yukyong; Doh, Kyung-Goo

doi:10.1109/icact.2008.4494190

Cited by 6 publications

(8 citation statements)

References 10 publications

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“…Several aggregation schemes such as sequence, conditional sequence, parallel and parallel-loop have been proposed in [120]. Here S i :: τ i denotes assignment of trust value τ i to node S i , & denotes AND operator and ⊗ is a sequence operator.…”

Section: Operatorsmentioning

confidence: 99%

Trust Computations and Trust Dynamics in Mobile Adhoc Networks: A Survey

Govindan

Mohapatra

2012

IEEE Commun. Surv. Tutorials

322

181

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Trust is an important aspect of mobile adhoc networks (MANETs). It enables entities to cope with uncertainty and uncontrollability caused by the free will of others. Trust computations and management are highly challenging issues in MANETs due to computational complexity constraints, and the independent movement of component nodes. This prevents the direct application of techniques suited for other networks. In MANETs, an untrustworthy node can wreak considerable damage and adversely affect the quality and reliability of data. Therefore, analyzing the trust level of a node has a positive influence on the confidence with which an entity conducts transactions with that node. In this work we present a detailed survey on various trust computing approaches that are geared towards MANETs. We highlight the summary and comparisons of these approaches. In addition, we analyze various works on trust dynamics including trust propagation, prediction and aggregation algorithms, the influence of network dynamics on trust dynamics and the impact of trust on security services.

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Section: Operatorsmentioning

confidence: 99%

Trust Computations and Trust Dynamics in Mobile Adhoc Networks: A Survey

Govindan

Mohapatra

2012

IEEE Commun. Surv. Tutorials

322

181

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“…The M imic operator introduces a new mediator role that plays trustees of the source role as a trustee in the source trust model, and plays the target role as a trustor in the target trust model. This leads to the corresponding extension of the trust models relations of L x (see lines 7-9) and L y (see lines [10][11][12]. Table 4 details the associated trust roles, metric and relations where new mediator role and extended relations are highlighted in grey.…”

Section: Role Mappingmentioning

confidence: 99%

“…In the case of Web service composition, some approaches (e.g., [15]) evaluate the recommendation for each service by evaluating its provider, whereas other approaches (e.g., [11]) evaluate the service itself in terms of its previous invocations, performance, reliability, etc. Then, trust is composed and/or aggregated according to the service composition flow (sequence, concurrent, conditional and loop).…”

Section: Trust Operationsmentioning

confidence: 99%

“…In the algorithm, the mediator interacts with r s (see lines 2-4) and r t (see lines 5-7). Then, the mediator computes the matching relation for each output relation (see lines [11][12][13][14][15][16][17][18] of the reply, where we assume that there is only one such relation (see lines 12-13) and requests its value using the appropriate request operation (see lines [16][17][18]. We further consider that the mediator (µr) embeds a library of mediation functions that translate and normalize heterogeneous trust metrics, which are invoked by mediation operations µo (see lines [12][13][14].…”

Section: Operation Mediationmentioning

confidence: 99%

“…To do so, o e is extended (see lines [9][10][11][12][13][14][15][16][17][18] to enable the mediator role µr (when it performs this operation) to retrieve similar o e output relations in T M C , i.e., the relations l a and l b that are respectively similar to l 1 and l 2 . The operation o e can hence call o 4 or o 7 to search for l 1 or l 2 .…”

Section: Operation Mediationmentioning

confidence: 99%

See 2 more Smart Citations

Composing Trust Models towards Interoperable Trust Management

et al. 2011

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A QoS‐based fine‐grained reputation system in the grid environment

Cui

Xiang

et al. 2011

Concurrency and Computation

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SUMMARY The accuracy of feedback presentation, the sensitivity, and the robustness of reputation evaluation are critical issues to be addressed in a reputation system under the grid environment. This paper proposes a QoS‐based fine‐grained grid reputation system, where economic elements are considered to make the reputation system more sensitive in the commercial grid environments. A novel fine‐grained feedback presentation model based on aggregation of objective QoS attributes and subjective opinions of evaluators is proposed to enable a semi‐automatic, personalized and accurate feedback presentation. Through the introduction of a punishment factor and the adaptive reference of a previous trust value, the proposed reputation system effectively improves the sensitivity of the reputation evaluation. Moreover, the weighted combination of interorganizational trust, direct trust and recommended trust makes the reputation system more robust against collusion attacks. Simulation results show that the proposed reputation system can practically predict feedback and effectively resist malicious attacks such as fake transaction attacks and badmouthing attacks. This provides a clear advantage in the applications of grid service selection. Copyright © 2011 John Wiley & Sons, Ltd.

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Trust Type Based Semantic Web Services Assessment and Selection

Cited by 6 publications

References 10 publications

Trust Computations and Trust Dynamics in Mobile Adhoc Networks: A Survey

Trust Computations and Trust Dynamics in Mobile Adhoc Networks: A Survey

Composing Trust Models towards Interoperable Trust Management

A QoS‐based fine‐grained reputation system in the grid environment

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