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dc.contributor.authorCope, Jacquelineen
dc.contributor.authorMaglaras, Leandrosen
dc.contributor.authorSiewe, Francoisen
dc.contributor.authorChen, Fengen
dc.contributor.authorJanicke, Helgeen
dc.date.accessioned2017-03-28T13:55:44Z
dc.date.available2017-03-28T13:55:44Z
dc.date.issued2017-03-03
dc.identifier.citationCope, J. et al. (2017) A Framework for Minimising Data Leakage from Non-Production Systems. In: Somani, A.K. and Deka, G.C. eds. Big Data Analytics: Tools and Technology for Effective Planning. Chapman and Hallen
dc.identifier.isbn9781138032392
dc.identifier.urihttp://hdl.handle.net/2086/13922
dc.description.abstractThere is much research and advice around de-identification techniques and data governance. This brings together the practical aspects to propose a simplified business model and framework for informed decision making for the minimisation of data leakage from non-production systems using the topology of data classification, data protection and the requirements of non-production environments. The simplified model details the influences of legal and regulatory and business requirements on business systems and non-production environments. The framework identifies six stages, and the interactions required to progress from the legal and regulatory standards applicable to political and geographical areas, through organisational requirements and business system to the purpose of the non-production environment to data treatment and protection, with a demonstration of compliance which occurs throughout each stage of the framework. A table top exercise following a hypothetical, but realistic, scenario validates the model and framework.en
dc.language.isoenen
dc.publisherChapman and Hallen
dc.subjectBig dataen
dc.subjectframeworken
dc.subjectdata leakageen
dc.subjectprivacyen
dc.subjectde-identificationen
dc.subjectmaskingen
dc.titleA Framework for Minimising Data Leakage from Non-Production Systemsen
dc.typeBook chapteren
dc.researchgroupSoftware Technology Research Laboratory (STRL)en
dc.peerreviewedYesen
dc.funderN/Aen
dc.projectidN/Aen
dc.cclicenceN/Aen
dc.date.acceptance2017-03-03en
dc.researchinstituteCyber Technology Institute (CTI)en


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