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PROV-GTS: a template-based PROV graph transformation system for obscuring provenance confidential information

PROV-GTS: a template-based PROV graph transformation system for obscuring provenance confidential information
PROV-GTS: a template-based PROV graph transformation system for obscuring provenance confidential information
Provenance is a record that describes the people, institutions, entities, and activities involved in producing, influencing, or delivering a piece of data or a thing. Provenance can be used to trace the source of ingredients in food industry, record the intermediate and final results of scientific workflows, and follow the origin of online posts and news. Data provenance becomes a significant metadata in validating the origin of information and asserting its quality. It has been adopted in many significant domains for different purposes, for example, validating experimental results in scientific workflow systems,improving health services in healthcare, trustworthiness of data from sensor networks,and managing access control systems. In particular, the provenance of information is crucial in deciding whether information is to be trusted.

In order to establish trust and confirm the quality and originality using provenance information,it is important to share provenance among collaborators in scientific workow systems or publicly over open environments such as the Web. PROV is a recent W3C specification for sharing provenance over the Web.

However, sharing provenance may expose confidential information such as the medical history of a patient, the identity of an agent, and the bank account details of an individual.It is therefore crucial for the sensitive and confidential information of provenance data to be obscured to enable trustworthiness prior to sharing provenance in open environments such as the Web.

This research work describes PROV-GTS, a provenance graph transformation system,whose principled definition is based on PROV properties, and which seeks to preserve graph integrity by avoiding false independencies and false dependencies while obscuring restricted provenance information. The system is formally established as a template based framework and formalised using category theory concepts, such as functors, diagrams,and natural transformation. PROV-GTS is shown to preserve graph connectivity,to be terminating and to be confluent with deterministic and consistent rule applications.The performance evaluation based on real-world provenance graphs demonstrates a high connectivity preservation with minimum graph reduction.
University of Southampton
Hussein, Jamal A.
808629ee-60b0-4c13-9460-246494192723
Hussein, Jamal A.
808629ee-60b0-4c13-9460-246494192723
Sassone, Vladimiro
df7d3c83-2aa0-4571-be94-9473b07b03e7

Hussein, Jamal A. (2017) PROV-GTS: a template-based PROV graph transformation system for obscuring provenance confidential information. University of Southampton, Doctoral Thesis, 187pp.

Record type: Thesis (Doctoral)

Abstract

Provenance is a record that describes the people, institutions, entities, and activities involved in producing, influencing, or delivering a piece of data or a thing. Provenance can be used to trace the source of ingredients in food industry, record the intermediate and final results of scientific workflows, and follow the origin of online posts and news. Data provenance becomes a significant metadata in validating the origin of information and asserting its quality. It has been adopted in many significant domains for different purposes, for example, validating experimental results in scientific workflow systems,improving health services in healthcare, trustworthiness of data from sensor networks,and managing access control systems. In particular, the provenance of information is crucial in deciding whether information is to be trusted.

In order to establish trust and confirm the quality and originality using provenance information,it is important to share provenance among collaborators in scientific workow systems or publicly over open environments such as the Web. PROV is a recent W3C specification for sharing provenance over the Web.

However, sharing provenance may expose confidential information such as the medical history of a patient, the identity of an agent, and the bank account details of an individual.It is therefore crucial for the sensitive and confidential information of provenance data to be obscured to enable trustworthiness prior to sharing provenance in open environments such as the Web.

This research work describes PROV-GTS, a provenance graph transformation system,whose principled definition is based on PROV properties, and which seeks to preserve graph integrity by avoiding false independencies and false dependencies while obscuring restricted provenance information. The system is formally established as a template based framework and formalised using category theory concepts, such as functors, diagrams,and natural transformation. PROV-GTS is shown to preserve graph connectivity,to be terminating and to be confluent with deterministic and consistent rule applications.The performance evaluation based on real-world provenance graphs demonstrates a high connectivity preservation with minimum graph reduction.

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Available under License University of Southampton Thesis Licence.
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Published date: 12 June 2017

Identifiers

Local EPrints ID: 417985
URI: http://eprints.soton.ac.uk/id/eprint/417985
PURE UUID: 90ecac02-ab4d-49c3-9dc9-bceeb604fec3
ORCID for Jamal A. Hussein: ORCID iD orcid.org/0000-0003-0490-5029

Catalogue record

Date deposited: 20 Feb 2018 17:30
Last modified: 29 Jan 2020 17:25

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Contributors

Author: Jamal A. Hussein ORCID iD
Thesis advisor: Vladimiro Sassone

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