Abstract
Big data is widely considered as the next big trend in e-Government environments but at the same time one of the most emerging and critical issues due to the challenges it imposes. The large amount of data being retained by governmental Service Providers that can be (potentially) exploited during Data Mining and analytics processes, include personal data and personally identifiable information, raising privacy concerns, mostly regarding data minimization and purpose limitation. This paper addresses the consideration of Central Government to aggregate information without revealing personal identifiers of individuals and proposes a privacy preserving methodology that can be easily incorporated into already deployed electronic services and e-Government frameworks through the adoption of scalable and adaptable salted hashing techniques.
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This work has been supported by the national project “Secure and Privacy-Aware eGovernment Sevices – SPAGOS” (Grant Agreement 11SYN_9_2059), under “SYNERGAGIA 2011” programme, of the Operational programme “Competitiveness and Entrepreneurship”.
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Drogkaris, P., Gritzalis, A. (2015). A Privacy Preserving Framework for Big Data in e-Government Environments. In: Fischer-Hübner, S., Lambrinoudakis, C., López, J. (eds) Trust, Privacy and Security in Digital Business. TrustBus 2015. Lecture Notes in Computer Science(), vol 9264. Springer, Cham. https://doi.org/10.1007/978-3-319-22906-5_16
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DOI: https://doi.org/10.1007/978-3-319-22906-5_16
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