Reza Shokri

ORCID

Publication Activity (10 Years)

Years Active: 2006-2024
Publications (10 Years): 75

Top Venues

Publications

Hongyan Chang, Hamed Hassani, Reza Shokri
Watermark Smoothing Attacks against Language Models. CoRR (2024)
Prakhar Ganesh, Cuong Tran, Reza Shokri, Ferdinando Fioretto
The Data Minimization Principle in Machine Learning. CoRR (2024)
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)
Jiayuan Ye, Anastasia Borovykh, Soufiane Hayou, Reza Shokri
Leave-one-out Distinguishability in Machine Learning. ICLR (2024)
Hongyan Chang, Brandon Edwards, Anindya S. Paul, Reza Shokri
Efficient Privacy Auditing in Federated Learning. USENIX Security Symposium (2024)
Reza Shokri, Daniele D. Caviglia, Orazio Aiello
Highly Linear, Digital OTA With Modified Input Stage. PRIME (2024)
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)
Hongyan Chang, Reza Shokri
Bias Propagation in Federated Learning. CoRR (2023)
Prakhar Ganesh, Hongyan Chang, Martin Strobel, Reza Shokri
On The Impact of Machine Learning Randomness on Group Fairness. CoRR (2023)
Jiayuan Ye, Anastasia Borovykh, Soufiane Hayou, Reza Shokri
Leave-one-out Distinguishability in Machine Learning. CoRR (2023)
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 (2023)
Sajjad Zarifzadeh, Philippe Liu, Reza Shokri
Low-Cost High-Power Membership Inference by Boosting Relativity. CoRR (2023)
Fatemehsadat Mireshghallah, Justus Mattern, Sicun Gao, Reza Shokri, Taylor Berg-Kirkpatrick
Smaller Language Models are Better Black-box Machine-Generated Text Detectors. CoRR (2023)
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)
Jiayuan Ye, Zhenyu Zhu, Fanghui Liu, Reza Shokri, Volkan Cevher
Initialization Matters: Privacy-Utility Analysis of Overparameterized Neural Networks. NeurIPS (2023)
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)
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 (2023)
Chendi Wang, Buxin Su, Jiayuan Ye, Reza Shokri, Weijie J. Su
Unified Enhancement of Privacy Bounds for Mixture Mechanisms via f-Differential Privacy. CoRR (2023)
Reza Shokri, Yarallah Koolivand, Omid Shoaei, Orazio Aiello, Daniele D. Caviglia
Multipolar Stimulator for DBS Application with Concurrent Imbalance Compensation. ICECS (2023)
Hongyan Chang, Reza Shokri
Bias Propagation in Federated Learning. ICLR (2023)
Prakhar Ganesh, Hongyan Chang, Martin Strobel, Reza Shokri
On The Impact of Machine Learning Randomness on Group Fairness. FAccT (2023)
Jiayuan Ye, Zhenyu Zhu, Fanghui Liu, Reza Shokri, Volkan Cevher
Initialization Matters: Privacy-Utility Analysis of Overparameterized Neural Networks. CoRR (2023)
Hannah Brown, Katherine Lee, Fatemehsadat Mireshghallah, Reza Shokri, Florian Tramèr
What Does it Mean for a Language Model to Preserve Privacy? FAccT (2022)
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)
Fatemehsadat Mireshghallah, Kartik Goyal, Archit Uniyal, Taylor Berg-Kirkpatrick, Reza Shokri
Quantifying Privacy Risks of Masked Language Models Using Membership Inference Attacks. EMNLP (2022)
Fatemehsadat Mireshghallah, Kartik Goyal, Archit Uniyal, Taylor Berg-Kirkpatrick, Reza Shokri
Quantifying Privacy Risks of Masked Language Models Using Membership Inference Attacks. CoRR (2022)
Hannah Brown, Katherine Lee, Fatemehsadat Mireshghallah, Reza Shokri, Florian Tramèr
What Does it Mean for a Language Model to Preserve Privacy? CoRR (2022)
Rishav Chourasia, Neil Shah, Reza Shokri
Forget Unlearning: Towards True Data-Deletion in Machine Learning. CoRR (2022)
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 (2022)
Martin Strobel, Reza Shokri
Data Privacy and Trustworthy Machine Learning. CoRR (2022)
Jiayuan Ye, Aadyaa Maddi, Sasi Kumar Murakonda, Vincent Bindschaedler, Reza Shokri
Enhanced Membership Inference Attacks against Machine Learning Models. CCS (2022)
Martin Strobel, Reza Shokri
Data Privacy and Trustworthy Machine Learning. IEEE Secur. Priv. 20 (5) (2022)
Jiayuan Ye, Reza Shokri
Differentially Private Learning Needs Hidden State (Or Much Faster Convergence). NeurIPS (2022)
Jiayuan Ye, Reza Shokri
Differentially Private Learning Needs Hidden State (Or Much Faster Convergence). CoRR (2022)
Neel Patel, Reza Shokri, Yair Zick
Model Explanations with Differential Privacy. FAccT (2022)
Hongyan Chang, Reza Shokri
On the Privacy Risks of Algorithmic Fairness. EuroS&P (2021)
Rishav Chourasia, Jiayuan Ye, Reza Shokri
Differential Privacy Dynamics of Langevin Diffusion and Noisy Gradient Descent. NeurIPS (2021)
Sasi Kumar Murakonda, Reza Shokri, George Theodorakopoulos
Quantifying the Privacy Risks of Learning High-Dimensional Graphical Models. AISTATS (2021)
Jiayuan Ye, Aadyaa Maddi, Sasi Kumar Murakonda, Reza Shokri
Enhanced Membership Inference Attacks against Machine Learning Models. CoRR (2021)
Rishav Chourasia, Jiayuan Ye, Reza Shokri
Differential Privacy Dynamics of Langevin Diffusion and Noisy Gradient Descent. CoRR (2021)
Reza Shokri, Martin Strobel, Yair Zick
On the Privacy Risks of Model Explanations. AIES (2021)
Milad Nasr, Reza Shokri, Amir Houmansadr
Improving Deep Learning with Differential Privacy using Gradient Encoding and Denoising. CoRR (2020)
Ni Trieu, Kareem Shehata, Prateek Saxena, Reza Shokri, Dawn Song
Epione: Lightweight Contact Tracing with Strong Privacy. IEEE Data Eng. Bull. 43 (2) (2020)
Sasi Kumar Murakonda, Reza Shokri
ML Privacy Meter: Aiding Regulatory Compliance by Quantifying the Privacy Risks of Machine Learning. CoRR (2020)
Anshul Aggarwal, Trevor E. Carlson, Reza Shokri, Shruti Tople
SOTERIA: In Search of Efficient Neural Networks for Private Inference. CoRR (2020)
Hongyan Chang, Ta Duy Nguyen, Sasi Kumar Murakonda, Ehsan Kazemi, Reza Shokri
On Adversarial Bias and the Robustness of Fair Machine Learning. CoRR (2020)
Neel Patel, Reza Shokri, Yair Zick
Model Explanations with Differential Privacy. CoRR (2020)
Te Juin Lester Tan, Reza Shokri
Bypassing Backdoor Detection Algorithms in Deep Learning. EuroS&P (2020)
Congzheng Song, Reza Shokri
Membership Encoding for Deep Learning. AsiaCCS (2020)
Hongyan Chang, Reza Shokri
On the Privacy Risks of Algorithmic Fairness. CoRR (2020)
Ni Trieu, Kareem Shehata, Prateek Saxena, Reza Shokri, Dawn Song
Epione: Lightweight Contact Tracing with Strong Privacy. CoRR (2020)
Liwei Song, Reza Shokri, Prateek Mittal
Privacy Risks of Securing Machine Learning Models against Adversarial Examples. CoRR (2019)
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)
Liwei Song, Reza Shokri, Prateek Mittal
Privacy Risks of Securing Machine Learning Models against Adversarial Examples. CCS (2019)
Sasi Kumar Murakonda, Reza Shokri, George Theodorakopoulos
Ultimate Power of Inference Attacks: Privacy Risks of High-Dimensional Models. CoRR (2019)
Reza Shokri
Trusting Machine Learning: Privacy, Robustness, and Transparency Challenges. IH&MMSec (2019)
Hongyan Chang, Virat Shejwalkar, Reza Shokri, Amir Houmansadr
Cronus: Robust and Heterogeneous Collaborative Learning with Black-Box Knowledge Transfer. CoRR (2019)
Reza Shokri, Martin Strobel, Yair Zick
Privacy Risks of Explaining Machine Learning Models. CoRR (2019)
Liwei Song, Reza Shokri, Prateek Mittal
Membership Inference Attacks Against Adversarially Robust Deep Learning Models. IEEE Symposium on Security and Privacy Workshops (2019)
Congzheng Song, Reza Shokri
Membership Encoding for Deep Learning. CoRR (2019)
Te Juin Lester Tan, Reza Shokri
Bypassing Backdoor Detection Algorithms in Deep Learning. CoRR (2019)
Milad Nasr, Reza Shokri, Amir Houmansadr
Machine Learning with Membership Privacy using Adversarial Regularization. CCS (2018)
Milad Nasr, Reza Shokri, Amir Houmansadr
Machine Learning with Membership Privacy using Adversarial Regularization. CoRR (2018)
Tyler Hunt, Congzheng Song, Reza Shokri, Vitaly Shmatikov, Emmett Witchel
Chiron: Privacy-preserving Machine Learning as a Service. CoRR (2018)
Kun Ouyang, Reza Shokri, David S. Rosenblum, Wenzhuo Yang
A Non-Parametric Generative Model for Human Trajectories. IJCAI (2018)
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 (2018)
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) (2018)
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) (2017)
Vincent Bindschaedler, Reza Shokri, Carl A. Gunter
Plausible Deniability for Privacy-Preserving Data Synthesis. CoRR (2017)
Vincent Bindschaedler, Reza Shokri, Carl A. Gunter
Plausible Deniability for Privacy-Preserving Data Synthesis. Proc. VLDB Endow. 10 (5) (2017)
Reza Shokri, Marco Stronati, Congzheng Song, Vitaly Shmatikov
Membership Inference Attacks Against Machine Learning Models. IEEE Symposium on Security and Privacy (2017)
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) (2017)
Vincent Bindschaedler, Reza Shokri
Synthesizing Plausible Privacy-Preserving Location Traces. IEEE Symposium on Security and Privacy (2016)
Reza Shokri, Marco Stronati, Vitaly Shmatikov
Membership Inference Attacks against Machine Learning Models. CoRR (2016)
Richard McPherson, Reza Shokri, Vitaly Shmatikov
Defeating Image Obfuscation with Deep Learning. CoRR (2016)
Reza Shokri, Vitaly Shmatikov
Privacy-Preserving Deep Learning. CCS (2015)
Reza Shokri
Privacy Games: Optimal User-Centric Data Obfuscation. Proc. Priv. Enhancing Technol. 2015 (2) (2015)
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)
Reza Shokri, Vitaly Shmatikov
Privacy-preserving deep learning. Allerton (2015)
Reza Shokri
Quantifying and protecting location privacy. it Inf. Technol. 57 (4) (2015)
Vincent Bindschaedler, Reza Shokri
Privacy through Fake yet Semantically Real Traces. CoRR (2015)
Reza Shokri
Privacy Games: Optimal Protection Mechanism Design for Bayesian and Differential Privacy. CoRR (2014)
Alexandra-Mihaela Olteanu, Kévin Huguenin, Reza Shokri, Jean-Pierre Hubaux
Quantifying the Effect of Co-location Information on Location Privacy. Privacy Enhancing Technologies (2014)
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) (2014)
Arthur Gervais, Reza Shokri, Adish Singla, Srdjan Capkun, Vincent Lenders
Quantifying Web-Search Privacy. CCS (2014)
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 (2014)
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)
Reza Shokri
Quantifizierung und Schutz von Location Privacy. Ausgezeichnete Informatikdissertationen (2013)
Reza Shokri, George Theodorakopoulos, Carmela Troncoso, Jean-Pierre Hubaux, Jean-Yves Le Boudec
Protecting location privacy: optimal strategy against localization attacks. CCS (2012)
Reza Shokri, George Theodorakopoulos, George Danezis, Jean-Pierre Hubaux, Jean-Yves Le Boudec
Quantifying Location Privacy: The Case of Sporadic Location Exposure. PETS (2011)
Reza Shokri, Panos Papadimitratos, George Theodorakopoulos, Jean-Pierre Hubaux
Collaborative Location Privacy. MASS (2011)
Reza Shokri, George Theodorakopoulos, Jean-Yves Le Boudec, Jean-Pierre Hubaux
Quantifying Location Privacy. IEEE Symposium on Security and Privacy (2011)
Julien Freudiger, Reza Shokri, Jean-Pierre Hubaux
Evaluating the Privacy Risk of Location-Based Services. Financial Cryptography (2011)
Francisco Santos, Mathias Humbert, Reza Shokri, Jean-Pierre Hubaux
Collaborative Location Privacy with Rational Users. GameSec (2011)
Maxim Raya, Reza Shokri, Jean-Pierre Hubaux
On the tradeoff between trust and privacy in wireless ad hoc networks. WISEC (2010)
Reza Shokri, Carmela Troncoso, Claudia Díaz, Julien Freudiger, Jean-Pierre Hubaux
Unraveling an old cloak: k-anonymity for location privacy. WPES (2010)
Reza Shokri, Pedram Pedarsani, George Theodorakopoulos, Jean-Pierre Hubaux
Preserving privacy in collaborative filtering through distributed aggregation of offline profiles. RecSys (2009)
Reza Shokri, Marcin Poturalski, Gael Ravot, Panos Papadimitratos, Jean-Pierre Hubaux
A practical secure neighbor verification protocol for wireless sensor networks. WISEC (2009)
Julien Freudiger, Reza Shokri, Jean-Pierre Hubaux
On the Optimal Placement of Mix Zones. Privacy Enhancing Technologies (2009)
Reza Shokri, Julien Freudiger, Murtuza Jadliwala, Jean-Pierre Hubaux
A distortion-based metric for location privacy. WPES (2009)

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Publication Activity (10 Years)

Top Topics

Top Venues

Reza Shokri