UWisconsin CS 763: Security and Privacy in Data Science (Previously CS 839: Topics in Security and Privacy)
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# Paper Suggestions
### Differential Privacy
4 years ago
- Frank McSherry and Kunal Talwar.
[*Mechanism Design via Differential Privacy*](http://kunaltalwar.org/papers/expmech.pdf).
FOCS 2007.
- Cynthia Dwork, Moni Naor, Toniann Pitassi, and Guy Rothblum.
[*Differential Privacy under Continual Observation*](http://www.wisdom.weizmann.ac.il/~naor/PAPERS/continual_observation.pdf).
STOC 2010.
- T.-H. Hubert Chan, Elaine Shi, and Dawn Song.
[*Private and Continual Release of Statistics*](https://eprint.iacr.org/2010/076.pdf).
ICALP 2010.
- Moritz Hardt, Katrina Ligett, and Frank McSherry.
[*A Simple and Practical Algorithm for Differentially Private Data Release*](https://papers.nips.cc/paper/4548-a-simple-and-practical-algorithm-for-differentially-private-data-release.pdf).
NIPS 2012.
- Daniel Kifer and Ashwin Machanavajjhala.
[*A Rigorous and Customizable Framework for Privacy*](http://www.cse.psu.edu/~duk17/papers/pufferfish_preprint.pdf).
PODS 2012.
4 years ago
- Úlfar Erlingsson, Vasyl Pihur, and Aleksandra Korolova.
[*RAPPOR: Randomized Aggregatable Privacy-Preserving Ordinal Response*](https://arxiv.org/pdf/1407.6981.pdf).
CCS 2014.
- Cynthia Dwork, Moni Naor, Omer Reingold, and Guy N. Rothblum.
[*Pure Differential Privacy for Rectangle Queries via Private Partitions*](https://guyrothblum.files.wordpress.com/2017/06/dnrr15.pdf).
- Matthew Joseph, Aaron Roth, Jonathan Ullman, and Bo Waggoner.
[*Local Differential Privacy for Evolving Data*](https://arxiv.org/abs/1802.07128).
NIPS 2018.
- Albert Cheu, Adam Smith, Jonathan Ullman, David Zeber, and Maxim Zhilyaev.
[*Distributed Differential Privacy via Shuffling*](https://arxiv.org/pdf/1808.01394).
- Jingcheng Liu and Kunal Talwar.
[*Private Selection from Private Candidates*](https://arxiv.org/pdf/1811.07971).
STOC 2019.
3 years ago
### Adversarial Machine Learning
- Christian Szegedy, Wojciech Zaremba, Ilya Sutskever, Joan Bruna, Dumitru Erhan, Ian Goodfellow, and Rob Fergus.
[*Intriguing Properties of Neural Networks*](https://arxiv.org/pdf/1312.6199.pdf).
ICLR 2014.
- Ian J. Goodfellow, Jonathon Shlens, and Christian Szegedy.
[*Explaining and Harnessing Adversarial Examples*](https://arxiv.org/abs/1412.6572).
ICLR 2015.
- Nicholas Carlini and David Wagner.
[*Towards Evaluating the Robustness of Neural Networks*](https://arxiv.org/pdf/1608.04644.pdf).
S&P 2017.
- Kevin Eykholt, Ivan Evtimov, Earlence Fernandes, Bo Li, Amir Rahmati, Chaowei Xiao, Atul Prakash, Tadayoshi Kohno, and Dawn Song.
[*Robust Physical-World Attacks on Deep Learning Models*](https://arxiv.org/pdf/1707.08945.pdf).
CVPR 2018.
- Nicholas Carlini and David Wagner.
[*Adversarial Examples Are Not Easily Detected: Bypassing Ten Detection Methods*](https://arxiv.org/pdf/1705.07263.pdf).
AISec 2017.
- Jacob Steinhardt, Pang Wei Koh, and Percy Liang.
[*Certified Defenses for Data Poisoning Attacks*](https://arxiv.org/pdf/1706.03691.pdf).
NIPS 2017.
- Aleksander Madry, Aleksandar Makelov, Ludwig Schmidt, Dimitris Tsipras, and Adrian Vladu.
[*Towards Deep Learning Models Resistant to Adversarial Attacks*](https://arxiv.org/pdf/1706.06083.pdf).
ICLR 2018.
- Vitaly Feldman.
[*Does Learning Require Memorization? A Short Tale about a Long Tail*](https://arxiv.org/pdf/1906.05271).
arXiv 2019.
- Nicholas Carlini, Chang Liu, Úlfar Erlingsson, Jernej Kos, and Dawn Song.
[*The Secret Sharer: Evaluating and Testing Unintended Memorization in Neural Networks*](https://arxiv.org/pdf/1802.08232).
USENIX Security 2019.
3 years ago
### Applied Cryptography
4 years ago
- Benjamin Braun, Ariel J. Feldman, Zuocheng Ren, Srinath Setty, Andrew J. Blumberg, and Michael Walfish.
4 years ago
[*Verifying Computations with State*](https://eprint.iacr.org/2013/356.pdf).
SOSP 2013.
4 years ago
- Bryan Parno, Jon Howell, Craig Gentry, and Mariana Raykova.
[*Pinocchio: Nearly Practical Verifiable Computation*](https://eprint.iacr.org/2013/279.pdf).
S&P 2013.
4 years ago
- Aseem Rastogi, Matthew A. Hammer and Michael Hicks.
[*Wysteria: A Programming Language for Generic, Mixed-Mode Multiparty Computations*](http://www.cs.umd.edu/~aseem/wysteria-tr.pdf).
S&P 2014.
- Shai Halevi and Victor Shoup.
[*Algorithms in HElib*](https://www.shoup.net/papers/helib.pdf).
CRYPTO 2014.
- Shai Halevi and Victor Shoup.
[*Bootstrapping for HElib*](https://www.shoup.net/papers/boot.pdf).
- Léo Ducas and Daniele Micciancio.
[*FHEW: Bootstrapping Homomorphic Encryption in Less than a Second*](https://eprint.iacr.org/2014/816.pdf).
- Peter Kairouz, Sewoong Oh, and Pramod Viswanath.
[*Secure Multi-party Differential Privacy*](https://papers.nips.cc/paper/6004-secure-multi-party-differential-privacy.pdf).
NIPS 2015.
4 years ago
- Arjun Narayan, Ariel Feldman, Antonis Papadimitriou, and Andreas Haeberlen.
4 years ago
[*Verifiable Differential Privacy*](https://www.cis.upenn.edu/~ahae/papers/verdp-eurosys2015.pdf).
- Henry Corrigan-Gibbs and Dan Boneh.
[*Prio: Private, Robust, and Scalable Computation of Aggregate Statistics*](https://people.csail.mit.edu/henrycg/files/academic/papers/nsdi17prio.pdf).
NSDI 2017.
- Valerie Chen, Valerio Pastro, Mariana Raykova.
[*Secure Computation for Machine Learning With SPDZ*](https://arxiv.org/pdf/1901.00329).
NIPS 2018.
- Wenting Zheng, Raluca Ada Popa, Joseph E. Gonzalez, Ion Stoica.
[*Helen: Maliciously Secure Coopetitive Learning for Linear Models*](https://arxiv.org/pdf/1907.07212).
S&P 2019.
3 years ago
### Algorithmic Fairness
- Cynthia Dwork, Moritz Hardt, Toniann Pitassi, Omer Reingold, and Rich Zemel.
[*Fairness through Awarness*](https://arxiv.org/pdf/1104.3913).
ITCS 2012.
- Moritz Hardt, Eric Price, and Nathan Srebro.
[*Equality of Opportunity in Supervised Learning*](https://arxiv.org/pdf/1610.02413).
NIPS 2016.
- Tolga Bolukbasi, Kai-Wei Chang, James Zou, Venkatesh Saligrama, and Adam Kalai.
[*Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings*](https://arxiv.org/pdf/1607.06520).
NIPS 2016.
- Jon Kleinberg, Sendhil Mullainathan, and Manish Raghavan.
[*Inherent Trade-Offs in the Fair Determination of Risk Scores*](https://arxiv.org/pdf/1609.05807).
ITCS 2017.
- Úrsula Hébert-Johnson, Michael P. Kim, Omer Reingold, and Guy N. Rothblum.
[*Multicalibration: Calibration for the (Computationally-Identifiable) Masses*](https://arxiv.org/pdf/1711.08513.pdf).
ICML 2018.
- Michael Kearns, Seth Neel, Aaron Roth, and Zhiwei Steven Wu.
[*Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness*](https://arxiv.org/pdf/1711.05144).
ICML 2018.
- Alekh Agarwal, Alina Beygelzimer, Miroslav Dudík, John Langford, and Hanna Wallach.
[*A Reductions Approach to Fair Classification*](https://arxiv.org/pdf/1803.02453).
ICML 2019.
- Ben Hutchinson and Margaret Mitchell.
[*50 Years of Test (Un)fairness: Lessons for Machine Learning*](https://arxiv.org/pdf/1811.10104).
FAT\* 2019.
### Programming Languages and Verification
4 years ago
- Martín Abadi and Andrew D. Gordon.
[*A Calculus for Cryptographic Protocols: The Spi Calculus*](https://www.microsoft.com/en-us/research/wp-content/uploads/2016/11/ic99spi.pdf).
Information and Computation, 1999.
- Frank McSherry.
[*Privacy Integrated Queries*](http://citeseerx.ist.psu.edu/viewdoc/download?rep=rep1&type=pdf&doi=
SIGMOD 2009.
- Jason Reed and Benjamin C. Pierce.
[*Distance Makes the Types Grow Stronger: A Calculus for Differential Privacy*](https://www.cis.upenn.edu/~bcpierce/papers/dp.pdf).
ICFP 2010.
- Daniel B. Griffin, Amit Levy, Deian Stefan, David Terei, David Mazières, John C. Mitchell, and Alejandro Russo.
[*Hails: Protecting Data Privacy in Untrusted Web Applications*](https://www.usenix.org/system/files/conference/osdi12/osdi12-final-35.pdf).
OSDI 2012.
- Danfeng Zhang, Aslan Askarov, and Andrew C. Myers.
[*Language-Based Control and Mitigation of Timing Channels*](https://www.cs.cornell.edu/andru/papers/pltiming-pldi12.pdf).
PLDI 2012.
- Andrew Miller, Michael Hicks, Jonathan Katz, and Elaine Shi.
[*Authenticated Data Structures, Generically*](https://www.cs.umd.edu/~mwh/papers/gpads.pdf).
POPL 2014.
4 years ago
- Gilles Barthe, Marco Gaboardi, Emilio Jesús Gallego Arias, Justin Hsu, Aaron Roth, and Pierre-Yves Strub.
4 years ago
[*Higher-Order Approximate Relational Refinement Types for Mechanism Design and Differential Privacy*](https://arxiv.org/pdf/1407.6845.pdf).
POPL 2015.
4 years ago
- Samee Zahur and David Evans.
[*Obliv-C: A Language for Extensible Data-Oblivious Computation*](https://eprint.iacr.org/2015/1153.pdf).
IACR 2015.
- Chang Liu, Xiao Shaun Wang, Kartik Nayak, Yan Huang, and Elaine Shi.
[*ObliVM: A Programming Framework for Secure Computation*](http://www.cs.umd.edu/~elaine/docs/oblivm.pdf).
S&P 2015.
- Andrew Ferraiuolo, Rui Xu, Danfeng Zhang, Andrew C. Myers, and G. Edward Suh.
4 years ago
[*Verification of a Practical Hardware Security Architecture Through Static Information Flow Analysis*](http://www.cse.psu.edu/~dbz5017/pub/asplos17.pdf).
ASPLOS 2017.
# Supplemental Material
4 years ago
- Cynthia Dwork and Aaron Roth.
[*Algorithmic Foundations of Data Privacy*](https://www.cis.upenn.edu/~aaroth/Papers/privacybook.pdf).
- Gilles Barthe, Marco Gaboardi, Justin Hsu, and Benjamin C. Pierce.
[*Programming Language Techniques for Differential Privacy*](https://dl.acm.org/citation.cfm?id=2893591&dl=ACM&coll=DL).
- Michael Walfish and Andrew J. Blumberg.
[*Verifying Computations without Reexecuting Them*](http://delivery.acm.org/10.1145/2650000/2641562/p74-walfish.pdf?ip=
- Véronique Cortier, Steve Kremer, and Bogdan Warinschi.
[*A Survey of Symbolic Methods in Computational Analysis of Cryptographic Systems*](https://hal.inria.fr/inria-00379776/document).
- Dan Boneh and Victor Shoup.
[*A Graduate Course in Applied Cryptography*](https://crypto.stanford.edu/~dabo/cryptobook/BonehShoup_0_4.pdf).