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arXiv:1607.00133stat.ML

Deep Learning with Differential Privacy

Martín Abadi, Andy Chu, Ian Goodfellow, H. Brendan McMahan, Ilya Mironov, Kunal Talwar, Li Zhang

Abstract

Machine learning techniques based on neural networks are achieving remarkable results in a wide variety of domains. Often, the training of models requires large, representative datasets, which may be crowdsourced and contain sensitive information. The models should not expose private information in these datasets. Addressing this goal, we develop new algorithmic techniques for learning and a refined analysis of privacy costs within the framework of differential privacy. Our implementation and experiments demonstrate that we can train deep neural networks with non-convex objectives, under a modest privacy budget, and at a manageable cost in software complexity, training efficiency, and model quality.

arXiv comments
Journal reference
Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security (ACM CCS), pp. 308-318, 2016
DOI
doi:10.1145/2976749.2978318
Subjects
stat.MLMachine Learning (Statistics) cs.CRCryptography and Security cs.LGMachine Learning

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Linked by 3 identifiable commenters in 3 comments across 3 threads, from Oct 2016 to Mar 2022.

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Discussed in comments3 threads

  1. Launch HN: Sarus (YC W22) – Work on sensitive data with differential privacy 1 comment

    • If the model training is designed to profile just one user, no, the model won't work by design. What you describe is an attack on the privacy of that user and we do want to make sure they fail. The way differential privacy works with machine learning is that it guarantees that…

      maximeagoView on HNParent context

  2. The Algorithmic Foundations of Differential Privacy (2014) [pdf] 1 comment

    • One problem I've found with differential privacy is that no one talks about how to set \epsilon. I've read this book, and it's quite well written and complete, but as the title says it focuses on the algorithmic foundations. This paper [1] is much better for practitioners, and…

      singhracView on HNParent context

  3. Paul Erdős: a life that added up to something (1996) 1 comment

    • I admit I geeked out and calculated this a couple months ago, after I was credited on my first academic paper (my career is in programming) If you count video games, I have a Bacon number of 3 because I was credited on Tiger Woods 2003-2005 with an artist named Sylvain Doreau…

      chubotView on HNParent context

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