Anonymization and risk

Perfect anonymization of data sets that contain personal information has failed. But the process of protecting data subjects in shared information remains integral to privacy practice and policy. While the deidentification debate has been vigorous and productive, there is no clear direction for poli...

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Published inWashington law review Vol. 91; no. 2; p. 703
Main Authors Rubinstein, Ira S, Hartzog, Woodrow
Format Journal Article
LanguageEnglish
Published Seattle Washington Law Review Association 01.06.2016
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ISSN0043-0617

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Abstract Perfect anonymization of data sets that contain personal information has failed. But the process of protecting data subjects in shared information remains integral to privacy practice and policy. While the deidentification debate has been vigorous and productive, there is no clear direction for policy. As a result, the law has been slow to adapt a holistic approach to protecting data subjects when data sets are released to others. Currently, the law is focused on whether an individual can be identified within a given set. We argue that the best way to move data release policy past the alleged failures of anonymization is to focus on the process of minimizing risk of reidentification and sensitive attribute disclosure, not preventing harm. Process-based data release policy, which resembles the law of data security, will help us move past the limitations of focusing on whether data sets have been "anonymized." It draws upon different tactics to protect the privacy of data subjects, including accurate deidentification rhetoric, contracts prohibiting reidentification and sensitive attribute disclosure, data enclaves, and query-based strategies to match required protections with the level of risk. By focusing on process, data release policy can better balance privacy and utility where nearly all data exchanges carry some risk.
AbstractList Perfect anonymization of data sets that contain personal information has failed. But the process of protecting data subjects in shared information remains integral to privacy practice and policy. While the deidentification debate has been vigorous and productive, there is no clear direction for policy. As a result, the law has been slow to adapt a holistic approach to protecting data subjects when data sets are released to others. Currently, the law is focused on whether an individual can be identified within a given set. We argue that the best way to move data release policy past the alleged failures of anonymization is to focus on the process of minimizing risk of reidentification and sensitive attribute disclosure, not preventing harm. Process-based data release policy, which resembles the law of data security, will help us move past the limitations of focusing on whether data sets have been "anonymized." It draws upon different tactics to protect the privacy of data subjects, including accurate deidentification rhetoric, contracts prohibiting reidentification and sensitive attribute disclosure, data enclaves, and query-based strategies to match required protections with the level of risk. By focusing on process, data release policy can better balance privacy and utility where nearly all data exchanges carry some risk.
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Author Hartzog, Woodrow
Rubinstein, Ira S
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Copyright Washington Law Review Association Jun 2016
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Snippet Perfect anonymization of data sets that contain personal information has failed. But the process of protecting data subjects in shared information remains...
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SubjectTerms Anonymity
Data integrity
Data security
Datasets
Laws, regulations and rules
Privacy
Right of privacy
Risk management
Studies
Title Anonymization and risk
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