Privacy and Data Balkanization: Circumventing the Barriers

Bernardo A. Huberman; Tad Hogg

doi:10.59471/raia202116

Autores/as

Bernardo A. Huberman CableLabs
Tad Hogg Institute for Molecular Manufacturing

DOI:

https://doi.org/10.59471/raia202116

Palabras clave:

Data, Privacy

Resumen

The rapid growth in digital data forms the basis for a wide range of new services and research, e.g, large-scale medical studies. At the same time, increasingly restrictive privacy concerns and laws are leading to significant overhead in arranging for sharing or combining different data sets to obtain these benefits. For new applications, where the benefit of combined data is not yet clear, this overhead can inhibit organizations from even trying to determine whether they can mutually benefit from sharing their data. In this paper, we discuss techniques to overcome this difficulty by employing private information transfer to determine whether there is a benefit from sharing data, and whether there is room to negotiate acceptable prices. These techniques involve cryptographic protocols. While currently considered secure, these protocols are potentially vulnerable to the development of quantum technology, particularly for ensuring privacy over significant periods of time into the future. To mitigate this concern, we describe how developments in practical quantum technology can improve the security of these protocols.

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» G. Bellala and B. A. Huberman, First Monday, Volume 21, Number 9 5 September (2016)

» J. Bovenberg et al., “How to fix the GDPR’s frustration of global biomedical research”, Science 370:40- 42 (2020)

» O. Goldreich et al., How to Play any Mental Game. Proc. STOC 1987: 218-229

» The Economist survey of Data Sovereignty: Geopolitics - Governments are erecting borders for data | Special report, Feb. 20, 2020

» T Hogg, P Harsha, K-Y Chen, Quantum Auctions, Int J of Quantum Information 5:751-780 (2007)

» T Hogg and Li Zhang, Private Database Queries Using Quantum States with Limited Coherence Times,

Intl J. of Quantum Information 7:459-474 (2009)

» B A. Huberman and T Hogg, Protecting the Privacy of Human Subjects, Science 307:1200-1201 (2005)

» B. A. Huberman and T. Hogg, Protecting privacy while revealing data. Nat Biotechnol 20, 332 (2002)

» B. A. Huberman and T. Hogg, Quantum Solution of Coordination Problems, Quantum Information Processing 2:421-432 (2003)

» B. A. Huberman, B. Lund and J. Wang. Quantum Secured Internet Transport, Information Systems Frontiers (2020), Springer, vol. 22(6), pages 1561-1567.

» D. Lazer et al., “Computational social science: Obstacles and opportunities”, Science 369:1060-1062 (2020) doi: 10.1126/science.aaz8170

» D. A. Meyer, Quantum Strategies, Physical Review Letters 82:1052-1055 (1999)

» A. Pah et al., “How to build a more open justice system”, Science 369:134 (2020) doi: 10.1126/science. aba6914

» W. N. Price et al. “Knowledge transfer for large-scale vaccine manufacturing”, Science 369:912 (2020) doi: 10.1126/science.abc9588

» L. Rocher, J.M. Hendrickx and Y.A. de Montjoye, Estimating the success of re-identifications in incomplete datasets using generative models. Nature Communications 10, 3069 (2019)

» Kerina H. Jones, David V. Ford, Chris Jones, Rohan Dsilva, Simon Thompson, Caroline J. Brooks, Martin

L. Heaven, Daniel S. Thayer, Cynthia L. McNerney and Ronan A. Lyons, 2014. “A case study of the secure anonymous information linkage (SAIL) gateway: A privacy-protecting remote access system for health- related research and evaluation,” Journal of Biomedical Informatics, volume 50, pp. 196–204.

» Tim Churches and Peter Christen, 2004. “Some methods for blindfolded record linkage,” BMC Medical Informatics and Decision Making, volume 4, number 9, at http://bmcmedinformdecismak. biomedcentral.com/articles/10.1186/1472-6947-4-9

» Rainer Schnell, Tobias Bachteler and Jorg Reiher, 2009. “Privacy-preserving record linkage using Bloom filters,” BMC Medical Informatics and Decision Making, volume 9, number 41, at http:// bmcmedinformdecismak.biomedcentral.com/articles/10.1186/1472-6947-9-41,

» Ibrahim Lazrig, Tarik Moataz, Indrajit Ray, Indrakshi Ray, Toan Ong, Michael Kahn, Frédéric Cuppens and Nora Cuppens, 2015. “Privacy preserving record matching using automated semi-trusted broker,” In: Pierangela Samarati (editor). Data and Applications Security and Privacy XXIX. Lecture Notes in Computer Science, volume 9149. Berlin: Springer International, pp. 103–118.

» Andrew D. Boyd, Paul R. Saxman, Dale A. Hunscher, Kevin A. Smith, Timothy D. Morris, Michelle Kaston, Frederick Bayoff, Bruce Rogers, Pamela Hayes, Namrata Rajeev, Eva Kline-Rogers, Kim Eagle, Daniel Clauw, John F. Greden, Lee A. Green and Brian D. Athey, 2009. “The University of Michigan Honest Broker: A Web-based service for clinical and translational research and practice,” Journal of American Medical Informatics Association, volume 16, number 6, pp. 784–791.

» Rajiv Dhir, Ashok A. Patel, Sharon Winters, Michelle Bisceglia, Dennis Swanson, Roger Aamodt and Michael J. Becich, 2008. “A multi-disciplinary approach to honest broker services for tissue banks and clinical data: A pragmatic and practical model,” Cancer, volume 113, number 7, pp. 1,705–1,715.

» Andrew C. Yao, 1982. “Protocols for secure computations,” SFCS ’08: 23rd Annual Symposium on Foundations of Computer Science, pp. 160–164.

» Rakesh Agrawal, Alexandre Evfimievski and Ramakrishnan Srikant, 2003. “Information sharing across private databases,” SIGMOD ’03: Proceedings of the 2003 ACM SIGMOD International Conference on Management of Data, pp. 86–97.

» L. Dusserre, C. Quantin and H. Bouzelat, 1995. “A one way public key cryptosystem for the linkage of nominal files in epidemicological studies,” Medical Informatics, volume 8, part 1, pp. 644–647.

» Frank Niedermeyer, Simone Steinmetzer, Martin Kroll and Rainer Schnell, 2014. “Cryptanalysis of basic Bloom filters used for privacy preserving record linkage,” Journal of Privacy and Confidentiality, volume 6, number 2, pp. 59–79