Open Source Tools for Statistical Disclosure Control
| Autor: | Gadad, Veena, Sowmyarani C N |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: | |
| DOI: | 10.5281/zenodo.3686598 |
| Popis: | There is a large requirement of the quality data that gets collected from various sources because the effective development, planning and research depend on the same. Huge amount of data gets collected and is stored in cloud or data centers. However, this data consists of sensitive information such as salary, disease, political affinity etc. that an individual does not want others to know. If the collected data is published as it is, then there are high chances that there is disclosure of the sensitive data and to prevent this data anonymization is used. Data anonymization must also be carried out to make the data compliant with General Data Protection Regulation (GDPR). Statistical disclosure control (SDC) is a suite of techniques to carry out data anonymization and at the same time preserving the utility of the data. This paper focuses on usage of open source tools that are available for statistical disclosure control. {"references":["Leon Wallenberg, Ton de Waal (1996), \"Statistical disclosure control in practice\", Springer-Verlag; New York","A.G. De Waal, A. J. Hund pool, L.C.R.J. Wallenberg (1995), \"Argus: Software for statistical disclosure control of microdata\", US Census Bureau, pp. 1–19","Ancon Hund pool, Aid van de Watering, Ramya Ramaswamy (2008), \"Mu-argues, version 4.2 user's manual\", Statistics Netherlands; The Netherlands","Ancon Hund pool, Aid van de Watering, Ramya Ramaswamy (2007), \"Tau-ARGUS User's Manual\", Essent-Project; The Netherlands","Matthias Temple (2008), \"Statistical disclosure control for microdata using the R-package sac micro\", J. of Stat. Soft., Volume 67, Issue 4, pp. 1–36, DOI: 10.18637/jss. v067.i04"]} |
| Databáze: | OpenAIRE |
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