264 lines
16 KiB
Markdown
264 lines
16 KiB
Markdown
# Assorted Papers
|
|
|
|
### Differential Privacy
|
|
- 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.
|
|
- Ilya Mironov.
|
|
[*On Significance of the Least Significant Bits For Differential Privacy*](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.366.5957&rep=rep1&type=pdf).
|
|
CCS 2012.
|
|
- 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.
|
|
- 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).
|
|
ASIACRYPT 2015.
|
|
- Martín Abadi, Andy Chu, Ian Goodfellow, H. Brendan McMahan, Ilya Mironov, Kunal Talwar, and Li Zhang.
|
|
[*Deep Learning with Differential Privacy*](https://arxiv.org/pdf/1607.00133).
|
|
CCS 2016.
|
|
- Martín Abadi, Úlfar Erlingsson, Ian Goodfellow, H. Brendan McMahan, Ilya Mironov, Nicolas Papernot, Kunal Talwar, and Li Zhang.
|
|
[*On the Protection of Private Information in Machine Learning Systems: Two Recent Approaches*](https://arxiv.org/pdf/1708.08022).
|
|
CSF 2016.
|
|
- Nicolas Papernot, Martín Abadi, Úlfar Erlingsson, Ian Goodfellow, and Kunal Talwar.
|
|
[*Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data*](https://arxiv.org/pdf/1610.05755).
|
|
ICLR 2017.
|
|
- Nicolas Papernot, Shuang Song, Ilya Mironov, Ananth Raghunathan, Kunal Talwar, and Úlfar Erlingsson.
|
|
[*Scalable Private Learning with PATE*](https://arxiv.org/pdf/1802.08908).
|
|
ICLR 2018.
|
|
- Matthew Joseph, Aaron Roth, Jonathan Ullman, and Bo Waggoner.
|
|
[*Local Differential Privacy for Evolving Data*](https://arxiv.org/abs/1802.07128).
|
|
NeurIPS 2018.
|
|
- Albert Cheu, Adam Smith, Jonathan Ullman, David Zeber, and Maxim Zhilyaev.
|
|
[*Distributed Differential Privacy via Shuffling*](https://arxiv.org/pdf/1808.01394).
|
|
EUROCRYPT 2019.
|
|
- Úlfar Erlingsson, Vitaly Feldman, Ilya Mironov, Ananth Raghunathan, Kunal Talwar, and Abhradeep Thakurta.
|
|
[*Amplification by Shuffling: From Local to Central Differential Privacy via Anonymity*](https://arxiv.org/pdf/1811.12469).
|
|
SODA 2019.
|
|
- Jingcheng Liu and Kunal Talwar.
|
|
[*Private Selection from Private Candidates*](https://arxiv.org/pdf/1811.07971).
|
|
STOC 2019.
|
|
|
|
### Adversarial ML
|
|
- Battista Biggio, Blaine Nelson, and Pavel Laskov.
|
|
[*Poisoning Attacks against Support Vector Machines*](https://arxiv.org/pdf/1206.6389).
|
|
ICML 2012.
|
|
- 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.
|
|
- Matt Fredrikson, Somesh Jha, and Thomas Ristenpart.
|
|
[*Model Inversion Attacks that Exploit Confidence Information and Basic Countermeasures*](https://www.cs.cmu.edu/~mfredrik/papers/fjr2015ccs.pdf).
|
|
CCS 2015.
|
|
- Nicholas Carlini and David Wagner.
|
|
[*Towards Evaluating the Robustness of Neural Networks*](https://arxiv.org/pdf/1608.04644.pdf).
|
|
S&P 2017.
|
|
- Reza Shokri, Marco Stronati, Congzheng Song, and Vitaly Shmatikov.
|
|
[*Membership Inference Attacks against Machine Learning Models*](https://arxiv.org/pdf/1610.05820).
|
|
S&P 2017.
|
|
- 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.
|
|
- 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.
|
|
- 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.
|
|
- Aditi Raghunathan, Jacob Steinhardt, and Percy Liang.
|
|
[*Certified Defenses against Adversarial Examples*](https://arxiv.org/pdf/1801.09344).
|
|
ICLR 2018.
|
|
- Florian Tramèr, Alexey Kurakin, Nicolas Papernot, Ian Goodfellow, Dan Boneh, and Patrick McDaniel.
|
|
[*Ensemble Adversarial Training: Attacks and Defenses*](https://arxiv.org/pdf/1705.07204).
|
|
ICLR 2018.
|
|
- Ali Shafahi, W. Ronny Huang, Mahyar Najibi, Octavian Suciu, Christoph Studer, Tudor Dumitras, and Tom Goldstein.
|
|
[*Poison Frogs! Targeted Clean-Label PoisoningAttacks on Neural Networks*](https://arxiv.org/pdf/1804.00792).
|
|
NeurIPS 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 2019.
|
|
- Vitaly Feldman.
|
|
[*Does Learning Require Memorization? A Short Tale about a Long Tail*](https://arxiv.org/pdf/1906.05271).
|
|
arXiv 2019.
|
|
|
|
### Applied Cryptography
|
|
- Benjamin Braun, Ariel J. Feldman, Zuocheng Ren, Srinath Setty, Andrew J. Blumberg, and Michael Walfish.
|
|
[*Verifying Computations with State*](https://eprint.iacr.org/2013/356.pdf).
|
|
SOSP 2013.
|
|
- Bryan Parno, Jon Howell, Craig Gentry, and Mariana Raykova.
|
|
[*Pinocchio: Nearly Practical Verifiable Computation*](https://eprint.iacr.org/2013/279.pdf).
|
|
S&P 2013.
|
|
- 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).
|
|
EUROCRYPT 2015.
|
|
- Léo Ducas and Daniele Micciancio.
|
|
[*FHEW: Bootstrapping Homomorphic Encryption in Less than a Second*](https://eprint.iacr.org/2014/816.pdf).
|
|
EUROCRYPT 2015.
|
|
- 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.
|
|
- Arjun Narayan, Ariel Feldman, Antonis Papadimitriou, and Andreas Haeberlen.
|
|
[*Verifiable Differential Privacy*](https://www.cis.upenn.edu/~ahae/papers/verdp-eurosys2015.pdf).
|
|
EUROSYS 2015.
|
|
- 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.
|
|
- Zahra Ghodsi, Tianyu Gu, Siddharth Garg.
|
|
[*SafetyNets: Verifiable Execution of Deep Neural Networks on an Untrusted Cloud*](https://arxiv.org/pdf/1706.10268).
|
|
NIPS 2017.
|
|
- Valerie Chen, Valerio Pastro, Mariana Raykova.
|
|
[*Secure Computation for Machine Learning With SPDZ*](https://arxiv.org/pdf/1901.00329).
|
|
NeurIPS 2018.
|
|
- Jialong Zhang, Zhongshu Gu, Jiyong Jang, Hui Wu, Marc Ph. Stoecklin, Heqing Huang, and Ian Molloy.
|
|
[*Protecting Intellectual Property of Deep Neural Networks with Watermarking*](https://gzs715.github.io/pubs/WATERMARK_ASIACCS18.pdf).
|
|
AsiaCCS 2018.
|
|
- Yossi Adi, Carsten Baum, Moustapha Cisse, Benny Pinkas, and Joseph Keshet.
|
|
[*Turning Your Weakness Into a Strength: Watermarking Deep Neural Networks by Backdooring*](https://arxiv.org/pdf/1802.04633).
|
|
USENIX 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.
|
|
- Bita Darvish Rouhani, Huili Chen, and Farinaz Koushanfar.
|
|
[*DeepSigns: A Generic Watermarking Framework for IP Protection of Deep Learning Models*](https://arxiv.org/pdf/1804.00750).
|
|
ASPLOS 2019.
|
|
- Roshan Dathathri, Olli Saarikivi, Hao Chen, Kim Laine, Kristin Lauter, Saeed Maleki, Madanlal Musuvathi, and Todd Mytkowicz.
|
|
[*CHET: an optimizing compiler for fully-homomorphic neural-network inferencing*](https://dl.acm.org/ft_gateway.cfm?id=3314628&ftid=2065506&dwn=1).
|
|
PLDI 2019.
|
|
|
|
### 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.
|
|
- Jieyu Zhao, Tianlu Wang, Mark Yatskar, Vicente Ordonez, and Kai-Wei Chang.
|
|
[*Men Also Like Shopping: Reducing Gender Bias Amplification using Corpus-level Constraints*](https://arxiv.org/pdf/1707.09457).
|
|
EMNLP 2017.
|
|
- 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.
|
|
- Niki Kilbertus, Mateo Rojas-Carulla, Giambattista Parascandolo, Moritz Hardt, Dominik Janzing, and Bernhard Schölkopf.
|
|
[*Avoiding Discrimination through Causal Reasoning*](https://arxiv.org/pdf/1706.02744).
|
|
NIPS 2017.
|
|
- Matt J. Kusner, Joshua R. Loftus, Chris Russell, Ricardo Silva.
|
|
[*Counterfactual Fairness*](https://arxiv.org/pdf/1703.06856).
|
|
NIPS 2017.
|
|
- Razieh Nabi and Ilya Shpitser.
|
|
[*Fair Inference on Outcomes*](https://arxiv.org/pdf/1705.10378).
|
|
AAAI 2018.
|
|
- 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.
|
|
|
|
### PL and Verification
|
|
- 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.
|
|
- Noah Goodman, Vikash Mansinghka, Daniel M. Roy, Keith Bonawitz, Joshua B. Tenenbaum.
|
|
[*Church: a language for generative models*](https://arxiv.org/pdf/1206.3255).
|
|
UAI 2008.
|
|
- Frank McSherry.
|
|
[*Privacy Integrated Queries*](http://citeseerx.ist.psu.edu/viewdoc/download?rep=rep1&type=pdf&doi=10.1.1.211.4503).
|
|
SIGMOD 2009.
|
|
- Marta Kwiatkowska, Gethin Norman, and David Parker.
|
|
[*Advances and Challenges of Probabilistic Model Checking*](https://www.prismmodelchecker.org/papers/allerton10.pdf).
|
|
Allerton 2010.
|
|
- 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.
|
|
- Andrew D. Gordon, Thomas A. Henzinger, Aditya V. Nori, and Sriram K. Rajamani.
|
|
[*Probabilistic Programming*](https://www.microsoft.com/en-us/research/wp-content/uploads/2016/02/fose-icse2014.pdf).
|
|
ICSE 2014.
|
|
- Gilles Barthe, Marco Gaboardi, Emilio Jesús Gallego Arias, Justin Hsu, Aaron Roth, and Pierre-Yves Strub.
|
|
[*Higher-Order Approximate Relational Refinement Types for Mechanism Design and Differential Privacy*](https://arxiv.org/pdf/1407.6845.pdf).
|
|
POPL 2015.
|
|
- 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.
|
|
- Gilles Barthe, Marco Gaboardi, Benjamin Grégoire, Justin Hsu, and Pierre-Yves Strub.
|
|
[*A Program Logic for Union Bounds*](https://arxiv.org/pdf/1602.05681).
|
|
ICALP 2016.
|
|
- Christian Albert Hammerschmidt, Sicco Verwer, Qin Lin, and Radu State.
|
|
[*Interpreting Finite Automata for Sequential Data*](https://arxiv.org/pdf/1611.07100).
|
|
NIPS 2016.
|
|
- Joost-Pieter Katoen.
|
|
[*The Probabilistic Model Checking Landscape*](https://moves.rwth-aachen.de/wp-content/uploads/lics2016_tutorial_katoen.pdf).
|
|
LICS 2016.
|
|
- Andrew Ferraiuolo, Rui Xu, Danfeng Zhang, Andrew C. Myers, and G. Edward Suh.
|
|
[*Verification of a Practical Hardware Security Architecture Through Static Information Flow Analysis*](http://www.cse.psu.edu/~dbz5017/pub/asplos17.pdf).
|
|
ASPLOS 2017.
|
|
- Frits Vaandrager.
|
|
[*Model Learning*](https://m-cacm.acm.org/magazines/2017/2/212445-model-learning/fulltext).
|
|
CACM 2017.
|
|
- Timon Gehr, Matthew Mirman, Dana Drachsler-Cohen, Petar Tsankov, Swarat Chaudhuri, and Martin Vechev
|
|
[*AI2: Safety and Robustness Certification of Neural Networks with Abstract Interpretation*](https://files.sri.inf.ethz.ch/website/papers/sp2018.pdf).
|
|
S&P 2018.
|
|
- Marc Fischer, Mislav Balunovic, Dana Drachsler-Cohen, Timon Gehr, Ce Zhang, and Martin Vechev.
|
|
[*DL2: Training and Querying Neural Networks with Logic*](http://proceedings.mlr.press/v97/fischer19a/fischer19a.pdf).
|
|
ICML 2019.
|
|
|
|
# Supplemental Material
|
|
- 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=24.59.48.254&id=2641562&acc=OA&key=4D4702B0C3E38B35%2E4D4702B0C3E38B35%2E4D4702B0C3E38B35%2E757E42EE4C319386&__acm__=1533144327_267b96b7bd723efc52072f0f79f6720d).
|
|
- 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).
|
|
- David Hand.
|
|
[*Statistics and the Theory of Measurement*](http://www.lps.uci.edu/~johnsonk/CLASSES/MeasurementTheory/Hand1996.StatisticsAndTheTheoryOfMeasurement.pdf).
|
|
- Judea Pearl.
|
|
[*Causal inference in statistics: An overview*](http://ftp.cs.ucla.edu/pub/stat_ser/r350.pdf).
|
|
- Yehuda Lindell and Benny Pinkas.
|
|
[*Secure Multiparty Computation for Privacy-Preserving Data Mining*](https://eprint.iacr.org/2008/197.pdf).
|