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Reza Shokri
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- affiliation: National University of Singapore
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2020 – today
- 2024
- [c54]Niloofar Mireshghallah, Justus Mattern, Sicun Gao, Reza Shokri, Taylor Berg-Kirkpatrick:
Smaller Language Models are Better Zero-shot Machine-Generated Text Detectors. EACL (2) 2024: 278-293 - [c53]Jiayuan Ye, Anastasia Borovykh, Soufiane Hayou, Reza Shokri:
Leave-one-out Distinguishability in Machine Learning. ICLR 2024 - [c52]Niloofar Mireshghallah, Hyunwoo Kim, Xuhui Zhou, Yulia Tsvetkov, Maarten Sap, Reza Shokri, Yejin Choi:
Can LLMs Keep a Secret? Testing Privacy Implications of Language Models via Contextual Integrity Theory. ICLR 2024 - [c51]Reza Shokri, Daniele D. Caviglia, Orazio Aiello:
Highly Linear, Digital OTA With Modified Input Stage. PRIME 2024: 1-4 - [c50]Hongyan Chang, Brandon Edwards, Anindya S. Paul, Reza Shokri:
Efficient Privacy Auditing in Federated Learning. USENIX Security Symposium 2024 - [i40]Prakhar Ganesh, Cuong Tran, Reza Shokri, Ferdinando Fioretto:
The Data Minimization Principle in Machine Learning. CoRR abs/2405.19471 (2024) - 2023
- [c49]Prakhar Ganesh
, Hongyan Chang
, Martin Strobel
, Reza Shokri
:
On The Impact of Machine Learning Randomness on Group Fairness. FAccT 2023: 1789-1800 - [c48]Reza Shokri, Yarallah Koolivand, Omid Shoaei, Orazio Aiello, Daniele D. Caviglia:
Multipolar Stimulator for DBS Application with Concurrent Imbalance Compensation. ICECS 2023: 1-4 - [c47]Hongyan Chang, Reza Shokri:
Bias Propagation in Federated Learning. ICLR 2023 - [c46]Zebang Shen, Jiayuan Ye, Anmin Kang, Hamed Hassani, Reza Shokri:
Share Your Representation Only: Guaranteed Improvement of the Privacy-Utility Tradeoff in Federated Learning. ICLR 2023 - [c45]Jiayuan Ye, Zhenyu Zhu, Fanghui Liu, Reza Shokri, Volkan Cevher:
Initialization Matters: Privacy-Utility Analysis of Overparameterized Neural Networks. NeurIPS 2023 - [c44]Chendi Wang, Buxin Su, Jiayuan Ye, Reza Shokri, Weijie J. Su:
Unified Enhancement of Privacy Bounds for Mixture Mechanisms via f-Differential Privacy. NeurIPS 2023 - [i39]Fatemehsadat Mireshghallah, Justus Mattern, Sicun Gao, Reza Shokri, Taylor Berg-Kirkpatrick:
Smaller Language Models are Better Black-box Machine-Generated Text Detectors. CoRR abs/2305.09859 (2023) - [i38]Prakhar Ganesh, Hongyan Chang, Martin Strobel, Reza Shokri:
On The Impact of Machine Learning Randomness on Group Fairness. CoRR abs/2307.04138 (2023) - [i37]Hongyan Chang, Reza Shokri:
Bias Propagation in Federated Learning. CoRR abs/2309.02160 (2023) - [i36]Zebang Shen, Jiayuan Ye, Anmin Kang, Hamed Hassani, Reza Shokri:
Share Your Representation Only: Guaranteed Improvement of the Privacy-Utility Tradeoff in Federated Learning. CoRR abs/2309.05505 (2023) - [i35]Jiayuan Ye, Anastasia Borovykh, Soufiane Hayou, Reza Shokri:
Leave-one-out Distinguishability in Machine Learning. CoRR abs/2309.17310 (2023) - [i34]Niloofar Mireshghallah, Hyunwoo Kim, Xuhui Zhou, Yulia Tsvetkov, Maarten Sap, Reza Shokri, Yejin Choi:
Can LLMs Keep a Secret? Testing Privacy Implications of Language Models via Contextual Integrity Theory. CoRR abs/2310.17884 (2023) - [i33]Chendi Wang, Buxin Su, Jiayuan Ye, Reza Shokri, Weijie J. Su:
Unified Enhancement of Privacy Bounds for Mixture Mechanisms via f-Differential Privacy. CoRR abs/2310.19973 (2023) - [i32]Jiayuan Ye, Zhenyu Zhu, Fanghui Liu, Reza Shokri, Volkan Cevher:
Initialization Matters: Privacy-Utility Analysis of Overparameterized Neural Networks. CoRR abs/2310.20579 (2023) - [i31]Sajjad Zarifzadeh, Philippe Liu, Reza Shokri:
Low-Cost High-Power Membership Inference by Boosting Relativity. CoRR abs/2312.03262 (2023) - 2022
- [j9]Martin Strobel
, Reza Shokri
:
Data Privacy and Trustworthy Machine Learning. IEEE Secur. Priv. 20(5): 44-49 (2022) - [c43]Florian Tramèr, Reza Shokri, Ayrton San Joaquin, Hoang Le, Matthew Jagielski, Sanghyun Hong, Nicholas Carlini:
Truth Serum: Poisoning Machine Learning Models to Reveal Their Secrets. CCS 2022: 2779-2792 - [c42]Jiayuan Ye, Aadyaa Maddi, Sasi Kumar Murakonda, Vincent Bindschaedler
, Reza Shokri:
Enhanced Membership Inference Attacks against Machine Learning Models. CCS 2022: 3093-3106 - [c41]Fatemehsadat Mireshghallah, Kartik Goyal, Archit Uniyal, Taylor Berg-Kirkpatrick
, Reza Shokri:
Quantifying Privacy Risks of Masked Language Models Using Membership Inference Attacks. EMNLP 2022: 8332-8347 - [c40]Neel Patel, Reza Shokri
, Yair Zick:
Model Explanations with Differential Privacy. FAccT 2022: 1895-1904 - [c39]Hannah Brown
, Katherine Lee, Fatemehsadat Mireshghallah, Reza Shokri
, Florian Tramèr
:
What Does it Mean for a Language Model to Preserve Privacy? FAccT 2022: 2280-2292 - [c38]Jiayuan Ye, Reza Shokri:
Differentially Private Learning Needs Hidden State (Or Much Faster Convergence). NeurIPS 2022 - [i30]Hannah Brown, Katherine Lee, Fatemehsadat Mireshghallah, Reza Shokri, Florian Tramèr:
What Does it Mean for a Language Model to Preserve Privacy? CoRR abs/2202.05520 (2022) - [i29]Fatemehsadat Mireshghallah, Kartik Goyal, Archit Uniyal, Taylor Berg-Kirkpatrick, Reza Shokri:
Quantifying Privacy Risks of Masked Language Models Using Membership Inference Attacks. CoRR abs/2203.03929 (2022) - [i28]Jiayuan Ye, Reza Shokri:
Differentially Private Learning Needs Hidden State (Or Much Faster Convergence). CoRR abs/2203.05363 (2022) - [i27]Florian Tramèr
, Reza Shokri, Ayrton San Joaquin, Hoang Le, Matthew Jagielski, Sanghyun Hong, Nicholas Carlini:
Truth Serum: Poisoning Machine Learning Models to Reveal Their Secrets. CoRR abs/2204.00032 (2022) - [i26]Martin Strobel, Reza Shokri:
Data Privacy and Trustworthy Machine Learning. CoRR abs/2209.06529 (2022) - [i25]Rishav Chourasia, Neil Shah, Reza Shokri:
Forget Unlearning: Towards True Data-Deletion in Machine Learning. CoRR abs/2210.08911 (2022) - 2021
- [c37]Reza Shokri
, Martin Strobel
, Yair Zick:
On the Privacy Risks of Model Explanations. AIES 2021: 231-241 - [c36]Sasi Kumar Murakonda, Reza Shokri, George Theodorakopoulos:
Quantifying the Privacy Risks of Learning High-Dimensional Graphical Models. AISTATS 2021: 2287-2295 - [c35]Hongyan Chang
, Reza Shokri:
On the Privacy Risks of Algorithmic Fairness. EuroS&P 2021: 292-303 - [c34]Rishav Chourasia, Jiayuan Ye, Reza Shokri:
Differential Privacy Dynamics of Langevin Diffusion and Noisy Gradient Descent. NeurIPS 2021: 14771-14781 - [i24]Rishav Chourasia, Jiayuan Ye, Reza Shokri:
Differential Privacy Dynamics of Langevin Diffusion and Noisy Gradient Descent. CoRR abs/2102.05855 (2021) - [i23]Jiayuan Ye, Aadyaa Maddi, Sasi Kumar Murakonda, Reza Shokri:
Enhanced Membership Inference Attacks against Machine Learning Models. CoRR abs/2111.09679 (2021) - 2020
- [j8]Ni Trieu, Kareem Shehata, Prateek Saxena, Reza Shokri, Dawn Song:
Epione: Lightweight Contact Tracing with Strong Privacy. IEEE Data Eng. Bull. 43(2): 95-107 (2020) - [c33]Congzheng Song, Reza Shokri
:
Membership Encoding for Deep Learning. AsiaCCS 2020: 344-356 - [c32]Te Juin Lester Tan, Reza Shokri
:
Bypassing Backdoor Detection Algorithms in Deep Learning. EuroS&P 2020: 175-183 - [i22]Ni Trieu, Kareem Shehata, Prateek Saxena, Reza Shokri, Dawn Song:
Epione: Lightweight Contact Tracing with Strong Privacy. CoRR abs/2004.13293 (2020) - [i21]Hongyan Chang, Ta Duy Nguyen, Sasi Kumar Murakonda, Ehsan Kazemi, Reza Shokri:
On Adversarial Bias and the Robustness of Fair Machine Learning. CoRR abs/2006.08669 (2020) - [i20]Neel Patel, Reza Shokri, Yair Zick:
Model Explanations with Differential Privacy. CoRR abs/2006.09129 (2020) - [i19]Sasi Kumar Murakonda, Reza Shokri:
ML Privacy Meter: Aiding Regulatory Compliance by Quantifying the Privacy Risks of Machine Learning. CoRR abs/2007.09339 (2020) - [i18]Milad Nasr, Reza Shokri, Amir Houmansadr:
Improving Deep Learning with Differential Privacy using Gradient Encoding and Denoising. CoRR abs/2007.11524 (2020) - [i17]Anshul Aggarwal, Trevor E. Carlson, Reza Shokri, Shruti Tople:
SOTERIA: In Search of Efficient Neural Networks for Private Inference. CoRR abs/2007.12934 (2020) - [i16]Hongyan Chang, Reza Shokri:
On the Privacy Risks of Algorithmic Fairness. CoRR abs/2011.03731 (2020)
2010 – 2019
- 2019
- [c31]Liwei Song, Reza Shokri
, Prateek Mittal:
Privacy Risks of Securing Machine Learning Models against Adversarial Examples. CCS 2019: 241-257 - [c30]Reza Shokri:
Trusting Machine Learning: Privacy, Robustness, and Transparency Challenges. IH&MMSec 2019: 150 - [c29]Liwei Song, Reza Shokri, Prateek Mittal:
Membership Inference Attacks Against Adversarially Robust Deep Learning Models. IEEE Symposium on Security and Privacy Workshops 2019: 50-56 - [c28]Milad Nasr, Reza Shokri
, Amir Houmansadr:
Comprehensive Privacy Analysis of Deep Learning: Passive and Active White-box Inference Attacks against Centralized and Federated Learning. IEEE Symposium on Security and Privacy 2019: 739-753 - [i15]Liwei Song, Reza Shokri, Prateek Mittal:
Privacy Risks of Securing Machine Learning Models against Adversarial Examples. CoRR abs/1905.10291 (2019) - [i14]Sasi Kumar Murakonda, Reza Shokri, George Theodorakopoulos:
Ultimate Power of Inference Attacks: Privacy Risks of High-Dimensional Models. CoRR abs/1905.12774 (2019) - [i13]Te Juin Lester Tan, Reza Shokri:
Bypassing Backdoor Detection Algorithms in Deep Learning. CoRR abs/1905.13409 (2019) - [i12]Reza Shokri, Martin Strobel, Yair Zick:
Privacy Risks of Explaining Machine Learning Models. CoRR abs/1907.00164 (2019) - [i11]Congzheng Song, Reza Shokri:
Membership Encoding for Deep Learning. CoRR abs/1909.12982 (2019) - [i10]Hongyan Chang, Virat Shejwalkar, Reza Shokri, Amir Houmansadr:
Cronus: Robust and Heterogeneous Collaborative Learning with Black-Box Knowledge Transfer. CoRR abs/1912.11279 (2019) - 2018
- [j7]Kévin Huguenin
, Igor Bilogrevic, Joana Soares Machado, Stefan Mihaila, Reza Shokri
, Italo Dacosta, Jean-Pierre Hubaux:
A Predictive Model for User Motivation and Utility Implications of Privacy-Protection Mechanisms in Location Check-Ins. IEEE Trans. Mob. Comput. 17(4): 760-774 (2018) - [c27]Milad Nasr, Reza Shokri
, Amir Houmansadr:
Machine Learning with Membership Privacy using Adversarial Regularization. CCS 2018: 634-646 - [c26]Kun Ouyang, Reza Shokri
, David S. Rosenblum, Wenzhuo Yang:
A Non-Parametric Generative Model for Human Trajectories. IJCAI 2018: 3812-3817 - [i9]Tyler Hunt, Congzheng Song, Reza Shokri, Vitaly Shmatikov, Emmett Witchel:
Chiron: Privacy-preserving Machine Learning as a Service. CoRR abs/1803.05961 (2018) - [i8]Milad Nasr, Reza Shokri, Amir Houmansadr:
Machine Learning with Membership Privacy using Adversarial Regularization. CoRR abs/1807.05852 (2018) - [i7]Milad Nasr, Reza Shokri, Amir Houmansadr:
Comprehensive Privacy Analysis of Deep Learning: Stand-alone and Federated Learning under Passive and Active White-box Inference Attacks. CoRR abs/1812.00910 (2018) - 2017
- [j6]Vincent Bindschaedler
, Reza Shokri
, Carl A. Gunter:
Plausible Deniability for Privacy-Preserving Data Synthesis. Proc. VLDB Endow. 10(5): 481-492 (2017) - [j5]Reza Shokri
, George Theodorakopoulos
, Carmela Troncoso:
Privacy Games Along Location Traces: A Game-Theoretic Framework for Optimizing Location Privacy. ACM Trans. Priv. Secur. 19(4): 11:1-11:31 (2017) - [j4]Alexandra-Mihaela Olteanu
, Kévin Huguenin
, Reza Shokri
, Mathias Humbert, Jean-Pierre Hubaux:
Quantifying Interdependent Privacy Risks with Location Data. IEEE Trans. Mob. Comput. 16(3): 829-842 (2017) - [c25]Reza Shokri
, Marco Stronati, Congzheng Song, Vitaly Shmatikov:
Membership Inference Attacks Against Machine Learning Models. IEEE Symposium on Security and Privacy 2017: 3-18 - [i6]Vincent Bindschaedler, Reza Shokri, Carl A. Gunter:
Plausible Deniability for Privacy-Preserving Data Synthesis. CoRR abs/1708.07975 (2017) - 2016
- [c24]Vincent Bindschaedler
, Reza Shokri
:
Synthesizing Plausible Privacy-Preserving Location Traces. IEEE Symposium on Security and Privacy 2016: 546-563 - [i5]Richard McPherson, Reza Shokri, Vitaly Shmatikov:
Defeating Image Obfuscation with Deep Learning. CoRR abs/1609.00408 (2016) - [i4]Reza Shokri, Marco Stronati, Vitaly Shmatikov:
Membership Inference Attacks against Machine Learning Models. CoRR abs/1610.05820 (2016) - 2015
- [j3]Reza Shokri:
Quantifying and protecting location privacy. it Inf. Technol. 57(4): 257-263 (2015) - [j2]Reza Shokri
:
Privacy Games: Optimal User-Centric Data Obfuscation. Proc. Priv. Enhancing Technol. 2015(2): 299-315 (2015) - [c23]Reza Shokri, Vitaly Shmatikov:
Privacy-preserving deep learning. Allerton 2015: 909-910 - [c22]Reza Shokri
, Vitaly Shmatikov:
Privacy-Preserving Deep Learning. CCS 2015: 1310-1321 - [c21]Igor Bilogrevic, Kévin Huguenin
, Stefan Mihaila, Reza Shokri
, Jean-Pierre Hubaux:
Predicting Users' Motivations behind Location Check-Ins and Utility Implications of Privacy Protection Mechanisms. NDSS 2015 - [i3]Vincent Bindschaedler, Reza Shokri:
Privacy through Fake yet Semantically Real Traces. CoRR abs/1505.07499 (2015) - 2014
- [j1]Reza Shokri, George Theodorakopoulos
, Panos Papadimitratos, Ehsan Kazemi
, Jean-Pierre Hubaux:
Hiding in the Mobile Crowd: LocationPrivacy through Collaboration. IEEE Trans. Dependable Secur. Comput. 11(3): 266-279 (2014) - [c20]Arthur Gervais, Reza Shokri, Adish Singla
, Srdjan Capkun, Vincent Lenders
:
Quantifying Web-Search Privacy. CCS 2014: 966-977 - [c19]Alexandra-Mihaela Olteanu, Kévin Huguenin
, Reza Shokri, Jean-Pierre Hubaux:
Quantifying the Effect of Co-location Information on Location Privacy. Privacy Enhancing Technologies 2014: 184-203 - [c18]George Theodorakopoulos
, Reza Shokri, Carmela Troncoso, Jean-Pierre Hubaux, Jean-Yves Le Boudec:
Prolonging the Hide-and-Seek Game: Optimal Trajectory Privacy for Location-Based Services. WPES 2014: 73-82 - [i2]Reza Shokri:
Privacy Games: Optimal Protection Mechanism Design for Bayesian and Differential Privacy. CoRR abs/1402.3426 (2014) - [i1]George Theodorakopoulos, Reza Shokri, Carmela Troncoso, Jean-Pierre Hubaux, Jean-Yves Le Boudec:
Prolonging the Hide-and-Seek Game: Optimal Trajectory Privacy for Location-Based Services. CoRR abs/1409.1716 (2014) - 2013
- [b1]Reza Shokri:
Quantifying and Protecting Location Privacy. EPFL, Switzerland, 2013 - [p1]Reza Shokri:
Quantifizierung und Schutz von Location Privacy. Ausgezeichnete Informatikdissertationen 2013: 231-240 - 2012
- [c17]Reza Shokri, George Theodorakopoulos
, Carmela Troncoso, Jean-Pierre Hubaux, Jean-Yves Le Boudec:
Protecting location privacy: optimal strategy against localization attacks. CCS 2012: 617-627 - 2011
- [c16]Julien Freudiger, Reza Shokri, Jean-Pierre Hubaux:
Evaluating the Privacy Risk of Location-Based Services. Financial Cryptography 2011: 31-46 - [c15]Francisco Santos, Mathias Humbert, Reza Shokri, Jean-Pierre Hubaux:
Collaborative Location Privacy with Rational Users. GameSec 2011: 163-181 - [c14]Reza Shokri, Panos Papadimitratos
, George Theodorakopoulos
, Jean-Pierre Hubaux:
Collaborative Location Privacy. MASS 2011: 500-509 - [c13]Reza Shokri, George Theodorakopoulos
, George Danezis, Jean-Pierre Hubaux, Jean-Yves Le Boudec:
Quantifying Location Privacy: The Case of Sporadic Location Exposure. PETS 2011: 57-76 - [c12]Reza Shokri, George Theodorakopoulos
, Jean-Yves Le Boudec, Jean-Pierre Hubaux:
Quantifying Location Privacy. IEEE Symposium on Security and Privacy 2011: 247-262 - 2010
- [c11]Maxim Raya, Reza Shokri, Jean-Pierre Hubaux:
On the tradeoff between trust and privacy in wireless ad hoc networks. WISEC 2010: 75-80 - [c10]Reza Shokri, Carmela Troncoso
, Claudia Díaz, Julien Freudiger, Jean-Pierre Hubaux:
Unraveling an old cloak: k-anonymity for location privacy. WPES 2010: 115-118
2000 – 2009
- 2009
- [c9]Julien Freudiger, Reza Shokri, Jean-Pierre Hubaux:
On the Optimal Placement of Mix Zones. Privacy Enhancing Technologies 2009: 216-234 - [c8]Reza Shokri, Pedram Pedarsani, George Theodorakopoulos
, Jean-Pierre Hubaux:
Preserving privacy in collaborative filtering through distributed aggregation of offline profiles. RecSys 2009: 157-164 - [c7]Reza Shokri, Marcin Poturalski, Gael Ravot, Panos Papadimitratos
, Jean-Pierre Hubaux:
A practical secure neighbor verification protocol for wireless sensor networks. WISEC 2009: 193-200 - [c6]Reza Shokri, Julien Freudiger, Murtuza Jadliwala, Jean-Pierre Hubaux:
A distortion-based metric for location privacy. WPES 2009: 21-30 - 2008
- [c5]Foroogh Anoosha, Reza Shokri, Nasser Yazdani, Amir Nayyeri:
AntMig: A Novel Code Migration Method to Conserve Energy in Wireless Sensor Networks. WCNC 2008: 2123-2128 - 2007
- [c4]Reza Shokri, Nasser Yazdani, Ahmad Khonsari
:
Chain-Based Anonymous Routing for Wireless Ad Hoc Networks. CCNC 2007: 297-302 - [c3]Reza Shokri, Maysam Yabandeh, Nasser Yazdani:
Anonymous Routing in MANET Using Random Identifiers. ICN 2007: 2 - [c2]Reza Shokri, Amir Nayyeri, Nasser Yazdani, Panos Papadimitratos
:
Efficient and Adjustable Recipient Anonymity in Mobile Ad Hoc Networks. MASS 2007: 1-3 - 2006
- [c1]Reza Shokri, A. Varshovi, Hossein Mohammadi, Nasser Yazdani, B. Sadeghian:
DDPM: Dynamic Deterministic Packet Marking for IP Traceback. ICON 2006: 1-6
Coauthor Index
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