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A Literature Study on Privacy Patterns Research
Karlstads universitet, Fakulteten för hälsa, natur- och teknikvetenskap (from 2013), Institutionen för matematik och datavetenskap (from 2013). (SERG - SOFTWARE ENGINEERING)ORCID-id: 0000-0002-0107-2108
Karlstads universitet, Fakulteten för hälsa, natur- och teknikvetenskap (from 2013), Institutionen för matematik och datavetenskap (from 2013). (PRISEC - PRIVACY AND SECURITY)ORCID-id: 0000-0002-0418-4121
Karlstads universitet, Fakulteten för hälsa, natur- och teknikvetenskap (from 2013), Institutionen för matematik och datavetenskap (from 2013). (SERG - SOFTWARE ENGINEERING)ORCID-id: 0000-0002-3180-9182
2017 (Engelska)Ingår i: SEAA 2017 - 43rd Euromicro Conference Series on Software Engineering and Advanced Applications, IEEE, 2017, s. 194-200Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]

Context: Facing the implementation of the EU General Data Protection Regulation in May 2018, many commercial software providers will soon need to adapt their products to new privacy-related constraints. Privacy patterns defined for different aspects of the software engineering process promise to be a useful concept for this task. In this situation, it seems valuable to characterize the state of the research related to privacy patterns.Objective: To identify, characterize and classify the contributions made by published research results related to patterns in the context of considering privacy concerns in engineering software. Method: A literature review in form of a mapping study of scientific articles was performed. The resulting map structures the relevant body of work into multiple dimensions, illustrating research focuses and gaps.Results: Results show that empirical evidence in this field is scarce and that holistic approaches to engineering privacy into software based on patterns are lacking. This potentially hinders industrial adoption.Conclusion: Based on these results, we recommend to empirically validate existing privacy patterns, to consolidate them in pattern catalogues and languages, and to move towards seamless approaches from engineering privacy requirements to implementation.

Ort, förlag, år, upplaga, sidor
IEEE, 2017. s. 194-200
Nyckelord [en]
privacy patterns, privacy, software engineering, mapping study
Nationell ämneskategori
Datavetenskap (datalogi)
Forskningsämne
Datavetenskap
Identifikatorer
URN: urn:nbn:se:kau:diva-65025DOI: 10.1109/SEAA.2017.28ISI: 000426074600029ISBN: 978-1-5386-2141-7 (digital)ISBN: 978-1-5386-2142-4 (tryckt)OAI: oai:DiVA.org:kau-65025DiVA, id: diva2:1154009
Konferens
2017 43rd Euromicro Conference on Software Engineering and Advanced Applications (SEAA) Aug 30 - Sept 1. Vienna, Austria
Tillgänglig från: 2017-11-01 Skapad: 2017-11-01 Senast uppdaterad: 2019-11-10Bibliografiskt granskad

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Lenhard, JörgFritsch, LotharHerold, Sebastian

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Lenhard, JörgFritsch, LotharHerold, Sebastian
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Institutionen för matematik och datavetenskap (from 2013)
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