Multi-dimensional evidence-based trust management with multi-trusted paths
Future Generation Computer Systems
An anti-collusion trust model in P2P networks
WISM'11 Proceedings of the 2011 international conference on Web information systems and mining - Volume Part I
Context-sensitive trust computing in distributed environments
Knowledge-Based Systems
Credibility-Based trust management for services in cloud environments
ICSOC'11 Proceedings of the 9th international conference on Service-Oriented Computing
Trust management of services in cloud environments: Obstacles and solutions
ACM Computing Surveys (CSUR)
Generating trusted graphs for trust evaluation in online social networks
Future Generation Computer Systems
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Abstract: Credential chains are needed in trusted peer-to-peer (P2P) applications, where trust delegation must be established between each pair of peers at specific role level. Role-based trust is refined from the coarse-grained trust model used in most P2P reputation systems. This paper offers a novel heuristic-weighting approach to selecting the most likely path to construct a role-based trust chain. We apply history-sensitive heuristics to measure the path complexity and assess the chaining efficiency. We discover successive edges of a trust chain, adaptively, to match with the demands from various P2P applications. New heuristic chaining algorithms are developed for backward, forward, and bi-directional discovery of trust chains. Our heuristic chain discovery scheme shortens the search time, reduces the memory requirement, and enhances the chaining accuracy in scalable P2P networks. Consider a trust graph over N credentials and M distinct role nodes. Our heuristic trust-chain discovery algorithms require O(N2logN) search time and O(M) memory space, if the secondary heuristics are generated off-line in advance. These are improved from O(N3) search time and O(NM) space required in non-heuristic discovery algorithms by Li, Winsborough, and Mitchell (2003). Our analytical results are verified by extensive simulation experiments over typical classes of role-based trust graphs.