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Toward Practical Anonymity: A White Paper on Privacy Risk, Metrics, and Governance in Synthetic Data
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STANDARD published on 9.10.2025
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Designation standards: IEEE White Paper
Publication date standards: 9.10.2025
SKU: NS-1243877
Approximate weight : 300 g (0.66 lbs)
Country: International technical standard
Category: Technical standards IEEE
- Active.
Structured synthetic data is presented as a maturing technology for privacy preservation that facilitates compliance with data protection regulations. The difficulty of defining when such data can be considered anonymous under existing legal frameworks is highlighted, given the absence of a universal standard, even as emerging best practices begin to provide guidance for privacy compliance. A comprehensive analysis is provided of the relevant legal and regulatory context, empirical methods for privacy risk evaluation, and adversarial threat modeling approaches. Privacy risk metrics and technical mitigation techniques are examined, and governance considerations for enterprise data management and compliance are addressed. Finally, the need for industry standard-setting initiatives is underscored, and a recommendation is made to pursue formal standards for privacy-preserving data synthesis.
ISBN: 979-8-8557-2728-9
Number of Pages: 56
Product Code: STDVA28346
Keywords: data management, data protection, Industry Connections, privacy, standards development, synthetic data, white paper
Category: Computer Security and Privacy
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