Trust and Distrust in Adaptive Inter-enterprise Collaboration Management

Ruohomaa, Sini; Kutvonen, Lea

doi:10.4067/s0718-18762010000200008

Cited by 15 publications

(22 citation statements)

References 47 publications

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“…Pilarcos has a computational measure for the degree of certainty [7]. As a result, specific trust decisions can be identified as needing human attention.…”

Section: Related Work On Changes and Uncertainty In Reputation Flowsmentioning

confidence: 99%

“…We build on our existing Pilarcos trust management system, presented in earlier work [7]. Our model separates reputation analysis policies from trust decision policies in order to be able to use the same reputation information in a variety of decision-making contexts.…”

Section: Introductionmentioning

confidence: 99%

“…Indeed, it is natural to divide decision processes in partially supervised systems to multiple levels as well, with a human intervention as the last option if other attempts fail. We have discussed different levels of policy in earlier work [7].…”

Section: Related Work On Changes and Uncertainty In Reputation Flowsmentioning

confidence: 99%

“…As a baseline risk tolerance policy, we will use a simple additive policy that gives more weight to negative than positive outcomes (by a factor of 3), and further weight on major effects as opposed to minor effects (another factor of 3) [7]. As an example, an actor with 10 experiences stored, of which 4 represent major positive outcomes, 2 minor positive, 2 minor negative and 1 major negative, would receive a trust score of (4 * 3) + 2 + 2 * (−3) + 1 * (−3) * 3 = −1.…”

Section: Detecting Changes In Service Performancementioning

confidence: 99%

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Detecting and Reacting to Changes in Reputation Flows

2011

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Abstract. In inter-enterprise collaboration, autonomic services from different organizations must independently determine which other services they can rely on. Reputation-based trust management in the Pilarcos open service ecosystem combines shared experience information on the actors' past behaviour and the decision context to estimate the risks of a collaboration. The trust decision process is semi-automatic, with selected decisions forwarded to a human user. A particularly interesting feature of the decision process is incongruity, that is, unexpected changes in service performance. In the classical example, a previously well-behaved service turns malicious to cash in its good reputation as illgained monetary profit. If the reputation system swiftly reacts to such changes, it protects its user more efficiently and deters misbehaviour. We present a new model for detecting and reacting to incongruities in a reputation-based trust management system. The model is based on the concept of reputation epochs, dividing an actor's reputation into periods of internally consistent behaviour. In contrast to earlier approaches, this model provides the necessary flexibility for the trust management system to adjust to constantly changing business situations.

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“…Pilarcos has a computational measure for the degree of certainty [7]. As a result, specific trust decisions can be identified as needing human attention.…”

Section: Related Work On Changes and Uncertainty In Reputation Flowsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Related Work On Changes and Uncertainty In Reputation Flowsmentioning

confidence: 99%

Section: Detecting Changes In Service Performancementioning

confidence: 99%

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Detecting and Reacting to Changes in Reputation Flows

2011

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“…Each service must independently determine which other services it should collaborate with; a trust decision is made to determine this willingness to rely on another service. The Pilarcos inter-enterprise collaboration management infrastructure [9,8] contains a trust management system to automate these decisions in routine cases [17]; selected difficult or high-stake decisions are forwarded to a human user based on policy-defined rules [6].…”

Section: Introductionmentioning

confidence: 99%

From Subjective Reputation to Verifiable Experiences — Augmenting Peer-Control Mechanisms for Open Service Ecosystems

Ruohomaa

Kaur

Kutvonen

2012

IFIP Advances in Information and Communication Technology

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Abstract. In inter-enterprise collaborations, autonomous services from different organizations must independently determine which other services they can rely on. Reputation-based trust management in Pilarcos utilizes shared experience information on the actors' past behaviour in estimating the risks of a collaboration; these experiences are shared between members of the service ecosystem through a reputation system. As the reputation system becomes an essential peer-control mechanism for the open service ecosystem, it must be augmented with sanctions for misbehaviour and appropriate incentives for correct behaviour. A fair sanctioning system cannot be built on traditional subjective reports, as rebuttal of undeserved reports requires shared, objective measures. To make the shared experience information objective and verifiable, we associate it with whether the relevant collaboration contract was followed, backed up with evidence in the form of nonrepudiable receipts. In this way, we are able to protect automated reputation-based trust decisions from being skewed by misinformation.

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Behavioural Evaluation of Reputation-Based Trust Systems

Ruohomaa

Kutvonen

2013

Lecture Notes in Business Information Processing

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Abstract. In the field of trust and reputation systems research, there is a need for common and more mature evaluation metrics for the purpose of producing meaningful comparisons of system proposals. In the state of the art, evaluations are based on simulated comparisons of how quickly negative reputation reports spread in the network or which decision policy gains more points against others in a specific gamelike setting, for example. We propose a next step in identifying criteria for a maturity model on the behavioural analysis of reputation-based trust systems.

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Trust and Distrust in Adaptive Inter-enterprise Collaboration Management

Abstract: This paper is available online at www.jtaer.com DOI: 10.4067/S0718-1876201000020000

Cited by 15 publications

References 47 publications

Detecting and Reacting to Changes in Reputation Flows

Detecting and Reacting to Changes in Reputation Flows

From Subjective Reputation to Verifiable Experiences — Augmenting Peer-Control Mechanisms for Open Service Ecosystems

Behavioural Evaluation of Reputation-Based Trust Systems

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