Automated Generation of Personal Data Reports from Relational Databases

Georgios John Fakas (), Ben Cawley () and Zhi Cai ()
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Georgios John Fakas: Department of Computing and Mathematics, Manchester Metropolitan University, Manchester, M1 5GD, UK
Ben Cawley: Department of Computing and Mathematics, Manchester Metropolitan University, Manchester, M1 5GD, UK
Zhi Cai: Department of Computing and Mathematics, Manchester Metropolitan University, Manchester, M1 5GD, UK

Journal of Information & Knowledge Management (JIKM), 2011, vol. 10, issue 02, 193-208

Abstract: 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) theGDSBased Methodand (2) theBy 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.

Keywords: Data extraction; privacy protection; relational databases (search for similar items in EconPapers)
Date: 2011
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DOI: 10.1142/S0219649211002936

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