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22 Stan. Tech. L. Rev. 1 (2019)
Privacy and Synthetic Datasets

handle is hein.journals/stantlr22 and id is 1 raw text is: Privacy and Synthetic Datasets Steven M. Bellovin,* Preetam K. Dutta,t and Nathan Reitinger* 22 STAN. TECH. L. REV. 1 (2019) ABSTRACT Sharing is a virtue, instilled in us from childhood Unfortunately, when it comes to big data-i e., databases possessing the potential to usher in a whole new world of scientific progress-the legal landscape is either too greedy or too Laissez-Faire. Either all identifiers must be stripped from the data, rendering it useless, or one-step remo ved personally identifiable in- formation maybe shared freely, freelysharingsecrets. In part this is a result of the historic solution to database privacy, anonymization, a subtractive technique incurringnot onlypoorprivacy results, butalso lackluster utility In anonymization 'sstead, differentialprivacyarose; itpro vides better, near- perfect privacy, but is nonetheless subtractive in terms of utility Today, anothersolution isleaninginto the fore, synthetic data. Using the magic of machine learning, synthetic data offers a generative, additive ap- proach-the creation ofalmost-but-not-quite replica data. In fact, as we rec- ommend, synthetic data may be combined with differential privacy to achieve a best-of-both- worlds scenario. After unpacking the technical nu- ances ofsynthetic data, we analyze itslegal implications, finding the familiar ambiguity-privacystatutes either overweigh (i.e., inappropriately exclude data sharing) or downplay (i.e., inappropriately permit data sharing) the potentialforsynthetic data to leak secrets. We conclude by finding thatsyn- thetic data is a valid, privacy-conscious alternative to raw data, but not a * Steven M. Bellovin is the Percy K. and Vida L.W. Hudson Professor of Computer Science at Columbia University, affiliate faculty at its law school, and a Visiting Scholar at the Center for Law and Information Policy at Fordham University School of Law. t Preetam Dutta is a doctoral student at the Department of Computer Science at Columbia University. t Nathan Reitinger is an attorney and a master's student at the Department of Computer Science at Columbia University. 1

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