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Automated generation of personal data reports from relational databases
Department of Computing and Mathematics Manchester Metropolitan University Manchester, M1 5GD, UK..
Department of Computing and Mathematics Manchester Metropolitan University Manchester, M1 5GD, UK..
Department of Computing and Mathematics Manchester Metropolitan University Manchester, M1 5GD, UK..
2011 (English)In: Journal of Information & Knowledge Management, ISSN 0219-6492, E-ISSN 1793-6926, Vol. 10, no 02, p. 193-208Article in journal (Refereed) Published
Abstract [en]

This paper presents a novel approach for extracting personal data and automatically generating Personal Data Reports (PDRs) from relational databases. Such PDRs can be used among other purposes for compliance with Subject Access Requests of Data Protection Acts. Two methodologies with different usability characteristics are introduced: (1) the GDSBased Method and (2) the By Schema Browsing Method. The proposed methdologies combine the use of graphs and query languages for the construction of PDRs. The novelty of these methodologies is that they do not require any prior knowledge of either the database schema or of any query language by the users. An optimisation algorithm is proposed that employs Hash Tables and reuses already found data. We conducted several queries on two standard benchmark databases (i.e. TPC-H and Microsoft Northwind) and we present the performance results.

Place, publisher, year, edition, pages
World Scientific Publishing Co. , 2011. Vol. 10, no 02, p. 193-208
Keywords [en]
Data extraction, privacy protection, relational databases
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:uu:diva-318235DOI: 10.1142/S0219649211002936OAI: oai:DiVA.org:uu-318235DiVA, id: diva2:1085995
Available from: 2017-03-30 Created: 2017-03-30 Last updated: 2017-11-29Bibliographically approved

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Fakas, Georgios John

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