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ORCIDDavid Evans 0001
David E. Evans 0001
Person information
- affiliation: University of Virginia, Charlottesville, USA
- affiliation (PhD 2000): MIT, Cambridge, MA, USA
Other persons with the same name
- David Evans — disambiguation page
- David Evans 0002 — Derby University, UK
- David Evans 0003 — University of Waterloo, Canada
- David Evans 0004 — Fermi National Accelerator Laboratory, Batavia, IL, USA (and 1 more)
- David Evans 0005 — University of Sheffield, UK
- David Evans 0006 — The University of Melbourne, Faculty of Architecture, Building and Planning, Parkville, Australia
- David Evans 0007 — University of Pennsylvania, Philadelphia, PA, USA
- David Evans 0008 — Philips Research Laboratories, Redhill, UK
- David Evans 0009 — University of Melbourne, Carlton, Australia
- David Evans 0010 — Nottingham University Hospital NHS Trust, UK
- David Evans 0011 — Western Washington University, Bellingham, WA, USA
- David Evans 0012 — WSP Development & Transportation, Bristol, UK
- David Evans 0013
![[0000-0001-7093-5694]](https://dblp.uni-trier.de/img/orcid-mark.12x12.png "0000-0001-7093-5694")
— University of Bristol, School of Management, Cabot Institute for Environment, UK - David E. Evans 0003 — University of East Anglia, School of Mathematics, Norwich, UK
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2020 – today
- 2024
[c84]Hannah Chen, Yangfeng Ji, David Evans:
Addressing Both Statistical and Causal Gender Fairness in NLP Models. NAACL-HLT (Findings) 2024: 561-582- [c83]Fnu Suya, Anshuman Suri, Tingwei Zhang, Jingtao Hong, Yuan Tian, David Evans:
SoK: Pitfalls in Evaluating Black-Box Attacks. SaTML 2024: 387-407 - [c82]Hojjat Aghakhani, Wei Dai, Andre Manoel, Xavier Fernandes, Anant Kharkar, Christopher Kruegel, Giovanni Vigna, David Evans, Ben Zorn, Robert Sim:
TrojanPuzzle: Covertly Poisoning Code-Suggestion Models. SP 2024: 1122-1140 - [c81]Bargav Jayaraman, Esha Ghosh, Melissa Chase, Sambuddha Roy, Wei Dai, David Evans:
Combing for Credentials: Active Pattern Extraction from Smart Reply. SP 2024: 1443-1461 - [i48]Michael Duan, Anshuman Suri, Niloofar Mireshghallah, Sewon Min, Weijia Shi, Luke Zettlemoyer, Yulia Tsvetkov, Yejin Choi, David Evans, Hannaneh Hajishirzi:
Do Membership Inference Attacks Work on Large Language Models? CoRR abs/2402.07841 (2024) - [i47]Hannah Chen, Yangfeng Ji, David Evans:
Addressing Both Statistical and Causal Gender Fairness in NLP Models. CoRR abs/2404.00463 (2024) - [i46]Josephine Lamp, Lu Feng, David Evans:
DP-RuL: Differentially-Private Rule Learning for Clinical Decision Support Systems. CoRR abs/2405.09721 (2024) - [i45]Anshuman Suri, Xiao Zhang, David Evans:
Do Parameters Reveal More than Loss for Membership Inference? CoRR abs/2406.11544 (2024) - [i44]Hannah Chen, Yangfeng Ji, David Evans:
The Mismeasure of Man and Models: Evaluating Allocational Harms in Large Language Models. CoRR abs/2408.01285 (2024) - 2023
- [c80]Yulong Tian, Fnu Suya, Anshuman Suri, Fengyuan Xu, David Evans:
Manipulating Transfer Learning for Property Inference. CVPR 2023: 15975-15984 - [c79]Josephine Lamp, Mark Derdzinski, Christopher Hannemann, Joost van der Linden, Lu Feng, Tianhao Wang, David E. Evans:
GlucoSynth: Generating Differentially-Private Synthetic Glucose Traces. NeurIPS 2023 - [c78]Fnu Suya, Xiao Zhang, Yuan Tian, David Evans:
What Distributions are Robust to Indiscriminate Poisoning Attacks for Linear Learners? NeurIPS 2023 - [c77]Anshuman Suri, Yifu Lu, Yanjin Chen, David Evans:
Dissecting Distribution Inference. SaTML 2023: 150-164 - [c76]Ahmed Salem, Giovanni Cherubin, David Evans, Boris Köpf, Andrew Paverd, Anshuman Suri, Shruti Tople, Santiago Zanella Béguelin:
SoK: Let the Privacy Games Begin! A Unified Treatment of Data Inference Privacy in Machine Learning. SP 2023: 327-345 - [c75]Lingxiao Wang, Bargav Jayaraman, David Evans, Quanquan Gu:
Efficient Privacy-Preserving Stochastic Nonconvex Optimization. UAI 2023: 2203-2213 - [i43]Hojjat Aghakhani, Wei Dai, Andre Manoel, Xavier Fernandes, Anant Kharkar, Christopher Kruegel, Giovanni Vigna, David Evans, Ben Zorn, Robert Sim:
TrojanPuzzle: Covertly Poisoning Code-Suggestion Models. CoRR abs/2301.02344 (2023) - [i42]Josephine Lamp, Mark Derdzinski, Christopher Hannemann, Joost van der Linden, Lu Feng, Tianhao Wang, David Evans:
GlucoSynth: Generating Differentially-Private Synthetic Glucose Traces. CoRR abs/2303.01621 (2023) - [i41]Yulong Tian, Fnu Suya, Anshuman Suri, Fengyuan Xu, David Evans:
Manipulating Transfer Learning for Property Inference. CoRR abs/2303.11643 (2023) - [i40]Rachel Cummings, Damien Desfontaines, David Evans, Roxana Geambasu, Matthew Jagielski, Yangsibo Huang, Peter Kairouz, Gautam Kamath, Sewoong Oh, Olga Ohrimenko, Nicolas Papernot, Ryan Rogers, Milan Shen, Shuang Song, Weijie J. Su, Andreas Terzis, Abhradeep Thakurta, Sergei Vassilvitskii, Yu-Xiang Wang, Li Xiong, Sergey Yekhanin, Da Yu, Huanyu Zhang, Wanrong Zhang:
Challenges towards the Next Frontier in Privacy. CoRR abs/2304.06929 (2023) - [i39]Fnu Suya, Xiao Zhang, Yuan Tian, David Evans:
When Can Linear Learners be Robust to Indiscriminate Poisoning Attacks? CoRR abs/2307.01073 (2023) - [i38]Fnu Suya, Anshuman Suri, Tingwei Zhang, Jingtao Hong, Yuan Tian, David Evans:
SoK: Pitfalls in Evaluating Black-Box Attacks. CoRR abs/2310.17534 (2023) - [i37]Valentin Hartmann, Anshuman Suri, Vincent Bindschaedler, David Evans, Shruti Tople, Robert West:
SoK: Memorization in General-Purpose Large Language Models. CoRR abs/2310.18362 (2023) - [i36]Evan Rose, Fnu Suya, David Evans:
Understanding Variation in Subpopulation Susceptibility to Poisoning Attacks. CoRR abs/2311.11544 (2023) - 2022
- [j19]Anshuman Suri, David Evans:
Formalizing and Estimating Distribution Inference Risks. Proc. Priv. Enhancing Technol. 2022(4): 528-551 (2022) - [j18]Hussain M. J. Almohri, Layne T. Watson, David Evans, Stephen C. Billups:
Dynamic System Diversification for Securing Cloud-based IoT Subnetworks. ACM Trans. Auton. Adapt. Syst. 17: 2:1-2:23 (2022) - [j17]Yulong Tian, Fnu Suya, Fengyuan Xu, David Evans:
Stealthy Backdoors as Compression Artifacts. IEEE Trans. Inf. Forensics Secur. 17: 1372-1387 (2022) - [c74]Bargav Jayaraman, David Evans:
Are Attribute Inference Attacks Just Imputation? CCS 2022: 1569-1582 - [c73]Hannah Chen, Yangfeng Ji, David E. Evans:
Balanced Adversarial Training: Balancing Tradeoffs between Fickleness and Obstinacy in NLP Models. EMNLP 2022: 632-647 - [c72]Fatemehsadat Mireshghallah, Archit Uniyal, Tianhao Wang, David E. Evans, Taylor Berg-Kirkpatrick:
An Empirical Analysis of Memorization in Fine-tuned Autoregressive Language Models. EMNLP 2022: 1816-1826 - [c71]Xiao Zhang, David E. Evans:
Understanding Intrinsic Robustness Using Label Uncertainty. ICLR 2022 - [c70]Nathan Brunelle, David Evans:
Comfortable Cohorts and Tractable Teams: Making Large Computing Theory Courses Feel Small. SIGCSE (1) 2022: 717-723 - [i35]Fatemehsadat Mireshghallah, Archit Uniyal, Tianhao Wang, David Evans, Taylor Berg-Kirkpatrick:
Memorization in NLP Fine-tuning Methods. CoRR abs/2205.12506 (2022) - [i34]Bargav Jayaraman, David Evans:
Are Attribute Inference Attacks Just Imputation? CoRR abs/2209.01292 (2022) - [i33]Hannah Chen, Yangfeng Ji, David Evans:
Balanced Adversarial Training: Balancing Tradeoffs between Fickleness and Obstinacy in NLP Models. CoRR abs/2210.11498 (2022) - [i32]Anshuman Suri, Yifu Lu, Yanjin Chen, David Evans:
Dissecting Distribution Inference. CoRR abs/2212.07591 (2022) - [i31]Ahmed Salem, Giovanni Cherubin, David Evans, Boris Köpf, Andrew Paverd, Anshuman Suri, Shruti Tople, Santiago Zanella Béguelin:
SoK: Let The Privacy Games Begin! A Unified Treatment of Data Inference Privacy in Machine Learning. CoRR abs/2212.10986 (2022) - 2021
- [j16]Peter Kairouz, H. Brendan McMahan, Brendan Avent, Aurélien Bellet, Mehdi Bennis, Arjun Nitin Bhagoji, Kallista A. Bonawitz, Zachary Charles, Graham Cormode, Rachel Cummings, Rafael G. L. D'Oliveira, Hubert Eichner, Salim El Rouayheb, David Evans, Josh Gardner, Zachary Garrett, Adrià Gascón, Badih Ghazi, Phillip B. Gibbons, Marco Gruteser, Zaïd Harchaoui, Chaoyang He, Lie He, Zhouyuan Huo, Ben Hutchinson, Justin Hsu, Martin Jaggi, Tara Javidi, Gauri Joshi, Mikhail Khodak, Jakub Konecný, Aleksandra Korolova, Farinaz Koushanfar, Sanmi Koyejo, Tancrède Lepoint, Yang Liu, Prateek Mittal, Mehryar Mohri, Richard Nock, Ayfer Özgür, Rasmus Pagh, Hang Qi, Daniel Ramage, Ramesh Raskar, Mariana Raykova, Dawn Song, Weikang Song, Sebastian U. Stich, Ziteng Sun, Ananda Theertha Suresh, Florian Tramèr, Praneeth Vepakomma, Jianyu Wang, Li Xiong, Zheng Xu, Qiang Yang, Felix X. Yu, Han Yu, Sen Zhao:
Advances and Open Problems in Federated Learning. Found. Trends Mach. Learn. 14(1-2): 1-210 (2021) - [j15]Bargav Jayaraman, Lingxiao Wang, Katherine Knipmeyer, Quanquan Gu, David Evans:
Revisiting Membership Inference Under Realistic Assumptions. Proc. Priv. Enhancing Technol. 2021(2): 348-368 (2021) - [c69]David Evans:
When Models Learn Too Much. CODASPY 2021: 1 - [c68]Hui Xu, Guanpeng Li, Homa Alemzadeh, Rakesh Bobba, Varun Chandrasekaran, David E. Evans, Nicolas Papernot, Karthik Pattabiraman, Florian Tramèr:
Fourth International Workshop on Dependable and Secure Machine Learning - DSML 2021. DSN Workshops 2021: xvi - [c67]Jack Prescott, Xiao Zhang, David E. Evans:
Improved Estimation of Concentration Under ℓp-Norm Distance Metrics Using Half Spaces. ICLR 2021 - [c66]Fnu Suya, Saeed Mahloujifar, Anshuman Suri, David Evans, Yuan Tian:
Model-Targeted Poisoning Attacks with Provable Convergence. ICML 2021: 10000-10010 - [i30]Yulong Tian, Fnu Suya, Fengyuan Xu, David Evans:
Stealthy Backdoors as Compression Artifacts. CoRR abs/2104.15129 (2021) - [i29]Anshuman Suri, David Evans:
Formalizing Distribution Inference Risks. CoRR abs/2106.03699 (2021) - [i28]Anshuman Suri, David Evans:
Formalizing and Estimating Distribution Inference Risks. CoRR abs/2109.06024 (2021) - 2020
- [j14]Hussain M. J. Almohri, Layne T. Watson, David Evans:
Predictability of IP Address Allocations for Cloud Computing Platforms. IEEE Trans. Inf. Forensics Secur. 15: 500-511 (2020) - [j13]Hussain M. J. Almohri, Layne T. Watson, David Evans:
An Attack-Resilient Architecture for the Internet of Things. IEEE Trans. Inf. Forensics Secur. 15: 3940-3954 (2020) - [c65]Hannah Chen, Yangfeng Ji, David Evans:
Pointwise Paraphrase Appraisal is Potentially Problematic. ACL (student) 2020: 150-155 - [c64]Xiao Zhang, Jinghui Chen, Quanquan Gu, David Evans:
Understanding the Intrinsic Robustness of Image Distributions using Conditional Generative Models. AISTATS 2020: 3883-3893 - [c63]Homa Alemzadeh, Rakesh Bobba, Varun Chandrasekaran, David E. Evans, Nicolas Papernot, Karthik Pattabiraman, Florian Tramèr:
Third International Workshop on Dependable and Secure Machine Learning - DSML 2020. DSN Workshops 2020: x - [c62]Hannah Chen, Yangfeng Ji, David E. Evans:
Finding Friends and Flipping Frenemies: Automatic Paraphrase Dataset Augmentation Using Graph Theory. EMNLP (Findings) 2020: 4741-4751 - [c61]Sicheng Zhu, Xiao Zhang, David Evans:
Learning Adversarially Robust Representations via Worst-Case Mutual Information Maximization. ICML 2020: 11609-11618 - [c60]Fnu Suya, Jianfeng Chi, David Evans, Yuan Tian:
Hybrid Batch Attacks: Finding Black-box Adversarial Examples with Limited Queries. USENIX Security Symposium 2020: 1327-1344 - [i27]Sicheng Zhu, Xiao Zhang, David Evans:
Learning Adversarially Robust Representations via Worst-Case Mutual Information Maximization. CoRR abs/2002.11798 (2020) - [i26]Xiao Zhang, Jinghui Chen, Quanquan Gu, David Evans:
Understanding the Intrinsic Robustness of Image Distributions using Conditional Generative Models. CoRR abs/2003.00378 (2020) - [i25]Anshuman Suri, David Evans:
One Neuron to Fool Them All. CoRR abs/2003.09372 (2020) - [i24]Bargav Jayaraman, Lingxiao Wang, David Evans, Quanquan Gu:
Revisiting Membership Inference Under Realistic Assumptions. CoRR abs/2005.10881 (2020) - [i23]Hannah Chen, Yangfeng Ji, David Evans:
Pointwise Paraphrase Appraisal is Potentially Problematic. CoRR abs/2005.11996 (2020) - [i22]Fnu Suya, Saeed Mahloujifar, David Evans, Yuan Tian:
Model-Targeted Poisoning Attacks: Provable Convergence and Certified Bounds. CoRR abs/2006.16469 (2020) - [i21]Hannah Chen, Yangfeng Ji, David Evans:
Finding Friends and Flipping Frenemies: Automatic Paraphrase Dataset Augmentation Using Graph Theory. CoRR abs/2011.01856 (2020)
2010 – 2019
- 2019
- [c59]Xiao Zhang, David Evans:
Cost-Sensitive Robustness against Adversarial Examples. ICLR (Poster) 2019 - [c58]Mohammad Samin Yasar, David Evans, Homa Alemzadeh:
Context-aware Monitoring in Robotic Surgery. ISMR 2019: 1-7 - [c57]Saeed Mahloujifar, Xiao Zhang, Mohammad Mahmoody, David Evans:
Empirically Measuring Concentration: Fundamental Limits on Intrinsic Robustness. NeurIPS 2019: 5210-5221 - [c56]Bargav Jayaraman, David Evans:
Evaluating Differentially Private Machine Learning in Practice. USENIX Security Symposium 2019: 1895-1912 - [i20]Mohammad Samin Yasar, David Evans, Homa Alemzadeh:
Context-aware Monitoring in Robotic Surgery. CoRR abs/1901.09802 (2019) - [i19]Bargav Jayaraman, David Evans:
When Relaxations Go Bad: "Differentially-Private" Machine Learning. CoRR abs/1902.08874 (2019) - [i18]Saeed Mahloujifar, Xiao Zhang, Mohammad Mahmoody, David Evans:
Empirically Measuring Concentration: Fundamental Limits on Intrinsic Robustness. CoRR abs/1905.12202 (2019) - [i17]Fnu Suya, Jianfeng Chi, David Evans, Yuan Tian:
Hybrid Batch Attacks: Finding Black-box Adversarial Examples with Limited Queries. CoRR abs/1908.07000 (2019) - [i16]Lingxiao Wang, Bargav Jayaraman, David Evans, Quanquan Gu:
Efficient Privacy-Preserving Nonconvex Optimization. CoRR abs/1910.13659 (2019) - [i15]Peter Kairouz, H. Brendan McMahan, Brendan Avent, Aurélien Bellet, Mehdi Bennis, Arjun Nitin Bhagoji, Kallista A. Bonawitz, Zachary Charles, Graham Cormode, Rachel Cummings, Rafael G. L. D'Oliveira, Salim El Rouayheb, David Evans, Josh Gardner, Zachary Garrett, Adrià Gascón, Badih Ghazi, Phillip B. Gibbons, Marco Gruteser, Zaïd Harchaoui, Chaoyang He, Lie He, Zhouyuan Huo, Ben Hutchinson, Justin Hsu, Martin Jaggi, Tara Javidi, Gauri Joshi, Mikhail Khodak, Jakub Konecný, Aleksandra Korolova, Farinaz Koushanfar, Sanmi Koyejo, Tancrède Lepoint, Yang Liu, Prateek Mittal, Mehryar Mohri, Richard Nock, Ayfer Özgür, Rasmus Pagh, Mariana Raykova, Hang Qi, Daniel Ramage, Ramesh Raskar, Dawn Song, Weikang Song, Sebastian U. Stich, Ziteng Sun, Ananda Theertha Suresh, Florian Tramèr, Praneeth Vepakomma, Jianyu Wang, Li Xiong, Zheng Xu, Qiang Yang, Felix X. Yu, Han Yu, Sen Zhao:
Advances and Open Problems in Federated Learning. CoRR abs/1912.04977 (2019) - 2018
- [j12]David Evans, Vladimir Kolesnikov, Mike Rosulek:
A Pragmatic Introduction to Secure Multi-Party Computation. Found. Trends Priv. Secur. 2(2-3): 70-246 (2018) - [j11]Mohammad Etemad, Alptekin Küpçü, Charalampos Papamanthou, David Evans:
Efficient Dynamic Searchable Encryption with Forward Privacy. Proc. Priv. Enhancing Technol. 2018(1): 5-20 (2018) - [j10]Hussain M. J. Almohri, Layne T. Watson, David Evans:
Misery Digraphs: Delaying Intrusion Attacks in Obscure Clouds. IEEE Trans. Inf. Forensics Secur. 13(6): 1361-1375 (2018) - [c55]Hussain M. J. Almohri, David Evans:
Fidelius Charm: Isolating Unsafe Rust Code. CODASPY 2018: 248-255 - [c54]Homa Alemzadeh, Karthik Pattabiraman, David E. Evans:
DSML 2018 Introduction. DSN Workshops 2018: 187 - [c53]Weilin Xu, David Evans, Yanjun Qi:
Feature Squeezing: Detecting Adversarial Examples in Deep Neural Networks. NDSS 2018 - [c52]Bargav Jayaraman, Lingxiao Wang, David Evans, Quanquan Gu:
Distributed Learning without Distress: Privacy-Preserving Empirical Risk Minimization. NeurIPS 2018: 6346-6357 - [i14]Hyrum S. Anderson, Anant Kharkar, Bobby Filar, David Evans, Phil Roth:
Learning to Evade Static PE Machine Learning Malware Models via Reinforcement Learning. CoRR abs/1801.08917 (2018) - [i13]Xiao Zhang, David Evans:
Cost-Sensitive Robustness against Adversarial Examples. CoRR abs/1810.09225 (2018) - [i12]Mohammad Etemad, Mohammad Mahmoody, David Evans:
Optimizing Trees for Static Searchable Encryption. IACR Cryptol. ePrint Arch. 2018: 52 (2018) - 2017
- [j9]Adrià Gascón, Phillipp Schoppmann, Borja Balle, Mariana Raykova, Jack Doerner, Samee Zahur, David Evans:
Privacy-Preserving Distributed Linear Regression on High-Dimensional Data. Proc. Priv. Enhancing Technol. 2017(4): 345-364 (2017) - [e1]Bhavani Thuraisingham, David Evans, Tal Malkin, Dongyan Xu:
Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security, CCS 2017, Dallas, TX, USA, October 30 - November 03, 2017. ACM 2017, ISBN 978-1-4503-4946-8 [contents] - [i11]Weilin Xu, David Evans, Yanjun Qi:
Feature Squeezing: Detecting Adversarial Examples in Deep Neural Networks. CoRR abs/1704.01155 (2017) - [i10]Weilin Xu, David Evans, Yanjun Qi:
Feature Squeezing Mitigates and Detects Carlini/Wagner Adversarial Examples. CoRR abs/1705.10686 (2017) - [i9]Bargav Jayaraman, Hannah Li, David Evans:
Decentralized Certificate Authorities. CoRR abs/1706.03370 (2017) - [i8]Hannah Li, David Evans:
Horcrux: A Password Manager for Paranoids. CoRR abs/1706.05085 (2017) - [i7]Mohammad Etemad, Alptekin Küpçü, Charalampos Papamanthou, David Evans:
Efficient Dynamic Searchable Encryption with Forward Privacy. CoRR abs/1710.00208 (2017) - [i6]Fnu Suya, Yuan Tian, David Evans, Paolo Papotti:
Query-limited Black-box Attacks to Classifiers. CoRR abs/1712.08713 (2017) - 2016
- [c51]Jack Doerner, David Evans, Abhi Shelat:
Secure Stable Matching at Scale. CCS 2016: 1602-1613 - [c50]Weilin Xu, Yanjun Qi, David Evans:
Automatically Evading Classifiers: A Case Study on PDF Malware Classifiers. NDSS 2016 - [c49]Samee Zahur, Xiao Wang, Mariana Raykova, Adrià Gascón, Jack Doerner, David Evans, Jonathan Katz:
Revisiting Square-Root ORAM: Efficient Random Access in Multi-party Computation. IEEE Symposium on Security and Privacy 2016: 218-234 - [i5]Jack Doerner, David Evans, Abhi Shelat:
Secure Stable Matching at Scale. IACR Cryptol. ePrint Arch. 2016: 861 (2016) - [i4]Adrià Gascón, Phillipp Schoppmann, Borja Balle, Mariana Raykova, Jack Doerner, Samee Zahur, David Evans:
Secure Linear Regression on Vertically Partitioned Datasets. IACR Cryptol. ePrint Arch. 2016: 892 (2016) - 2015
- [c48]Samee Zahur, Mike Rosulek, David Evans:
Two Halves Make a Whole - Reducing Data Transfer in Garbled Circuits Using Half Gates. EUROCRYPT (2) 2015: 220-250 - [c47]Yuchen Zhou, David Evans:
Understanding and Monitoring Embedded Web Scripts. IEEE Symposium on Security and Privacy 2015: 850-865 - [i3]Samee Zahur, David Evans:
Obliv-C: A Language for Extensible Data-Oblivious Computation. IACR Cryptol. ePrint Arch. 2015: 1153 (2015) - 2014
- [c46]Yuchen Zhou, David Evans:
SSOScan: Automated Testing of Web Applications for Single Sign-On Vulnerabilities. USENIX Security Symposium 2014: 495-510 - [i2]Samee Zahur, Mike Rosulek, David Evans:
Two Halves Make a Whole: Reducing Data Transfer in Garbled Circuits using Half Gates. IACR Cryptol. ePrint Arch. 2014: 756 (2014) - 2013
- [c45]Yan Huang, Jonathan Katz, David Evans:
Efficient Secure Two-Party Computation Using Symmetric Cut-and-Choose. CRYPTO (2) 2013: 18-35 - [c44]Samee Zahur, David Evans:
Circuit Structures for Improving Efficiency of Security and Privacy Tools. IEEE Symposium on Security and Privacy 2013: 493-507 - [c43]Rui Wang, Yuchen Zhou, Shuo Chen, Shaz Qadeer, David Evans, Yuri Gurevich:
Explicating SDKs: Uncovering Assumptions Underlying Secure Authentication and Authorization. USENIX Security Symposium 2013: 399-314 - [i1]Yan Huang, Jonathan Katz, David Evans:
Efficient Secure Two-Party Computation Using Symmetric Cut-and-Choose. IACR Cryptol. ePrint Arch. 2013: 81 (2013) - 2012
- [c42]Yan Huang, David Evans, Jonathan Katz:
Private Set Intersection: Are Garbled Circuits Better than Custom Protocols? NDSS 2012 - [c41]Yan Huang, Jonathan Katz, David Evans:
Quid-Pro-Quo-tocols: Strengthening Semi-honest Protocols with Dual Execution. IEEE Symposium on Security and Privacy 2012: 272-284 - 2011
- [j8]David Evans, Salvatore J. Stolfo:
Guest Editors' Introduction: The Science of Security. IEEE Secur. Priv. 9(3): 16-17 (2011) - [j7]Salvatore J. Stolfo, Steven M. Bellovin, David Evans:
Measuring Security. IEEE Secur. Priv. 9(3): 60-65 (2011) - [c40]Peter Chapman, David Evans:
Automated black-box detection of side-channel vulnerabilities in web applications. CCS 2011: 263-274 - [c39]Yuchen Zhou, David Evans:
Protecting Private Web Content from Embedded Scripts. ESORICS 2011: 60-79 - [c38]Yan Huang, David Evans:
Private Editing Using Untrusted Cloud Services. ICDCS Workshops 2011: 263-272 - [c37]Yan Huang, Chih-Hao Shen, David Evans, Jonathan Katz, Abhi Shelat:
Efficient Secure Computation with Garbled Circuits. ICISS 2011: 28-48 - [c36]Yan Huang, Lior Malka, David Evans, Jonathan Katz:
Efficient Privacy-Preserving Biometric Identification. NDSS 2011 - [c35]Yikan Chen, David Evans:
Auditing Information Leakage for Distance Metrics. SocialCom/PASSAT 2011: 1131-1140 - [c34]Yan Huang, Peter Chapman, David Evans:
Privacy-Preserving Applications on Smartphones. HotSec 2011 - [c33]Yan Huang, David Evans, Jonathan Katz, Lior Malka:
Faster Secure Two-Party Computation Using Garbled Circuits. USENIX Security Symposium 2011 - [c32]Jonathan Burket, Patrick Mutchler, Michael Weaver, Muzzammil Zaveri, David Evans:
GuardRails: A Data-Centric Web Application Security Framework. WebApps 2011 - [p1]David Evans, Anh Nguyen-Tuong, John C. Knight:
Effectiveness of Moving Target Defenses. Moving Target Defense 2011: 29-48
2000 – 2009
- 2009
- [c31]