Trust and Risk Relationship Analysis on a Workflow Basis: A Use Case

Valentina Viduto, Karim Djemame, Paul Townend, Jie Xu, Sarah Fores, Lydia Lau, Vania Dimitrova, Martyn Fletcher, Stephen Hobson, Jim Austin, John McAvoy, Charlie E. Dibsdale

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Trust and risk are often seen in proportion to each other; as such, high trust may induce low risk and vice versa. However, recent research argues that trust and risk relationship is implicit rather than proportional. Considering that trust and risk are implicit, this paper proposes for the first time a novel approach to view trust and risk on a basis of a W3C PROV provenance data model applied in a healthcare domain. We argue that high trust in healthcare domain can be placed in data despite of its high risk, and low trust data can have low risk depending on data quality attributes and its provenance. This is demonstrated by our trust and risk models applied to the BII case study data. The proposed theoretical approach first calculates risk values at each workflow step considering PROV concepts and second, aggregates the final risk score for the whole provenance chain. Different from risk model, trust of a workflow is derived by applying DS/AHP method. The results prove our assumption that trust and risk relationship is implicit.
LanguageEnglish
Title of host publicationProceedings of the Ninth International Conference on Internet Monitoring and Protection
EditorsJaime Lloret Mauri, Constantion Paleologu
Place of PublicationParis, France
PublisherInternational Academy, Research, and Industry Association (IARIA)
Pages7-12
Number of pages6
ISBN (Electronic)9781612083629
Publication statusPublished - 20 Jul 2014
Externally publishedYes
Event9th International Conference on Internet Monitoring and Protection - Paris, France
Duration: 20 Jul 201424 Jul 2014
Conference number: 9
https://www.iaria.org/conferences2014/ICIMP14.html (Link to Conference Website)

Conference

Conference9th International Conference on Internet Monitoring and Protection
Abbreviated titleICIMP 2014
CountryFrance
CityParis
Period20/07/1424/07/14
Internet address

Fingerprint

Risk model
Healthcare
Proportion
Value at risk
Trust model
AHP method
Quality attributes
Data quality

Cite this

Viduto, V., Djemame, K., Townend, P., Xu, J., Fores, S., Lau, L., ... Dibsdale, C. E. (2014). Trust and Risk Relationship Analysis on a Workflow Basis: A Use Case. In J. L. Mauri, & C. Paleologu (Eds.), Proceedings of the Ninth International Conference on Internet Monitoring and Protection (pp. 7-12). Paris, France: International Academy, Research, and Industry Association (IARIA).
Viduto, Valentina ; Djemame, Karim ; Townend, Paul ; Xu, Jie ; Fores, Sarah ; Lau, Lydia ; Dimitrova, Vania ; Fletcher, Martyn ; Hobson, Stephen ; Austin, Jim ; McAvoy, John ; Dibsdale, Charlie E. / Trust and Risk Relationship Analysis on a Workflow Basis : A Use Case. Proceedings of the Ninth International Conference on Internet Monitoring and Protection. editor / Jaime Lloret Mauri ; Constantion Paleologu. Paris, France : International Academy, Research, and Industry Association (IARIA), 2014. pp. 7-12
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title = "Trust and Risk Relationship Analysis on a Workflow Basis: A Use Case",
abstract = "Trust and risk are often seen in proportion to each other; as such, high trust may induce low risk and vice versa. However, recent research argues that trust and risk relationship is implicit rather than proportional. Considering that trust and risk are implicit, this paper proposes for the first time a novel approach to view trust and risk on a basis of a W3C PROV provenance data model applied in a healthcare domain. We argue that high trust in healthcare domain can be placed in data despite of its high risk, and low trust data can have low risk depending on data quality attributes and its provenance. This is demonstrated by our trust and risk models applied to the BII case study data. The proposed theoretical approach first calculates risk values at each workflow step considering PROV concepts and second, aggregates the final risk score for the whole provenance chain. Different from risk model, trust of a workflow is derived by applying DS/AHP method. The results prove our assumption that trust and risk relationship is implicit.",
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Viduto, V, Djemame, K, Townend, P, Xu, J, Fores, S, Lau, L, Dimitrova, V, Fletcher, M, Hobson, S, Austin, J, McAvoy, J & Dibsdale, CE 2014, Trust and Risk Relationship Analysis on a Workflow Basis: A Use Case. in JL Mauri & C Paleologu (eds), Proceedings of the Ninth International Conference on Internet Monitoring and Protection. International Academy, Research, and Industry Association (IARIA), Paris, France, pp. 7-12, 9th International Conference on Internet Monitoring and Protection, Paris, France, 20/07/14.

Trust and Risk Relationship Analysis on a Workflow Basis : A Use Case. / Viduto, Valentina; Djemame, Karim; Townend, Paul; Xu, Jie; Fores, Sarah; Lau, Lydia; Dimitrova, Vania; Fletcher, Martyn; Hobson, Stephen; Austin, Jim; McAvoy, John; Dibsdale, Charlie E.

Proceedings of the Ninth International Conference on Internet Monitoring and Protection. ed. / Jaime Lloret Mauri; Constantion Paleologu. Paris, France : International Academy, Research, and Industry Association (IARIA), 2014. p. 7-12.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

TY - GEN

T1 - Trust and Risk Relationship Analysis on a Workflow Basis

T2 - A Use Case

AU - Viduto, Valentina

AU - Djemame, Karim

AU - Townend, Paul

AU - Xu, Jie

AU - Fores, Sarah

AU - Lau, Lydia

AU - Dimitrova, Vania

AU - Fletcher, Martyn

AU - Hobson, Stephen

AU - Austin, Jim

AU - McAvoy, John

AU - Dibsdale, Charlie E.

N1 - No authors are affiliated to Huddersfield on the output. SH 2/8/17

PY - 2014/7/20

Y1 - 2014/7/20

N2 - Trust and risk are often seen in proportion to each other; as such, high trust may induce low risk and vice versa. However, recent research argues that trust and risk relationship is implicit rather than proportional. Considering that trust and risk are implicit, this paper proposes for the first time a novel approach to view trust and risk on a basis of a W3C PROV provenance data model applied in a healthcare domain. We argue that high trust in healthcare domain can be placed in data despite of its high risk, and low trust data can have low risk depending on data quality attributes and its provenance. This is demonstrated by our trust and risk models applied to the BII case study data. The proposed theoretical approach first calculates risk values at each workflow step considering PROV concepts and second, aggregates the final risk score for the whole provenance chain. Different from risk model, trust of a workflow is derived by applying DS/AHP method. The results prove our assumption that trust and risk relationship is implicit.

AB - Trust and risk are often seen in proportion to each other; as such, high trust may induce low risk and vice versa. However, recent research argues that trust and risk relationship is implicit rather than proportional. Considering that trust and risk are implicit, this paper proposes for the first time a novel approach to view trust and risk on a basis of a W3C PROV provenance data model applied in a healthcare domain. We argue that high trust in healthcare domain can be placed in data despite of its high risk, and low trust data can have low risk depending on data quality attributes and its provenance. This is demonstrated by our trust and risk models applied to the BII case study data. The proposed theoretical approach first calculates risk values at each workflow step considering PROV concepts and second, aggregates the final risk score for the whole provenance chain. Different from risk model, trust of a workflow is derived by applying DS/AHP method. The results prove our assumption that trust and risk relationship is implicit.

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KW - provenance

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KW - DS/AHP model

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BT - Proceedings of the Ninth International Conference on Internet Monitoring and Protection

A2 - Mauri, Jaime Lloret

A2 - Paleologu, Constantion

PB - International Academy, Research, and Industry Association (IARIA)

CY - Paris, France

ER -

Viduto V, Djemame K, Townend P, Xu J, Fores S, Lau L et al. Trust and Risk Relationship Analysis on a Workflow Basis: A Use Case. In Mauri JL, Paleologu C, editors, Proceedings of the Ninth International Conference on Internet Monitoring and Protection. Paris, France: International Academy, Research, and Industry Association (IARIA). 2014. p. 7-12