DDPM: Dynamic Deterministic Packet Marking for IP Traceback. - Reza Shokri; A. Varshovi; Hossein Mohammadi; Nasser Yazdani; B. Sadeghian (ICON, 2006)

Chain-Based Anonymous Routing for Wireless Ad Hoc Networks. - Reza Shokri; Nasser Yazdani; Ahmad Khonsari (CCNC, 2007)

Anonymous Routing in MANET Using Random Identifiers. - Reza Shokri; Maysam Yabandeh; Nasser Yazdani (ICN, 2007)

Efficient and Adjustable Recipient Anonymity in Mobile Ad Hoc Networks. - Reza Shokri; Amir Nayyeri; Nasser Yazdani; Panos Papadimitratos (MASS, 2007)

AntMig: A Novel Code Migration Method to Conserve Energy in Wireless Sensor Networks. - Foroogh Anoosha; Reza Shokri; Nasser Yazdani; Amir Nayyeri (WCNC, 2008)

On the Optimal Placement of Mix Zones. - Julien Freudiger; Reza Shokri; Jean-Pierre Hubaux (Privacy Enhancing Technologies, 2009)

Preserving privacy in collaborative filtering through distributed aggregation of offline profiles. - Reza Shokri; Pedram Pedarsani; George Theodorakopoulos 001; Jean-Pierre Hubaux (RecSys, 2009)

A practical secure neighbor verification protocol for wireless sensor networks. - Reza Shokri; Marcin Poturalski; Gael Ravot; Panos Papadimitratos; Jean-Pierre Hubaux (WISEC, 2009)

A distortion-based metric for location privacy. - Reza Shokri; Julien Freudiger; Murtuza Jadliwala; Jean-Pierre Hubaux (WPES, 2009)

On the tradeoff between trust and privacy in wireless ad hoc networks. - Maxim Raya; Reza Shokri; Jean-Pierre Hubaux (WISEC, 2010)

Unraveling an old cloak: k-anonymity for location privacy. - Reza Shokri; Carmela Troncoso; Claudia Díaz; Julien Freudiger; Jean-Pierre Hubaux (WPES, 2010)

Evaluating the Privacy Risk of Location-Based Services. - Julien Freudiger; Reza Shokri; Jean-Pierre Hubaux (Financial Cryptography, 2011)

Collaborative Location Privacy with Rational Users. - Francisco Santos; Mathias Humbert; Reza Shokri; Jean-Pierre Hubaux (GameSec, 2011)

Collaborative Location Privacy. - Reza Shokri; Panos Papadimitratos; George Theodorakopoulos 001; Jean-Pierre Hubaux (MASS, 2011)

Quantifying Location Privacy: The Case of Sporadic Location Exposure. - Reza Shokri; George Theodorakopoulos 001; George Danezis; Jean-Pierre Hubaux; Jean-Yves Le Boudec (PETS, 2011)

Quantifying Location Privacy. - Reza Shokri; George Theodorakopoulos 001; Jean-Yves Le Boudec; Jean-Pierre Hubaux (IEEE Symposium on Security and Privacy, 2011)

Protecting location privacy: optimal strategy against localization attacks. - Reza Shokri; George Theodorakopoulos 001; Carmela Troncoso; Jean-Pierre Hubaux; Jean-Yves Le Boudec (CCS, 2012)

Quantifizierung und Schutz von Location Privacy. - Reza Shokri (Ausgezeichnete Informatikdissertationen, 2013)

Quantifying and Protecting Location Privacy. - Reza Shokri (2013)

Quantifying Web-Search Privacy. - Arthur Gervais; Reza Shokri; Adish Singla; Srdjan Capkun; Vincent Lenders (CCS, 2014)

Quantifying the Effect of Co-location Information on Location Privacy. - Alexandra-Mihaela Olteanu; Kévin Huguenin; Reza Shokri; Jean-Pierre Hubaux (Privacy Enhancing Technologies, 2014)

Prolonging the Hide-and-Seek Game: Optimal Trajectory Privacy for Location-Based Services. - George Theodorakopoulos 001; Reza Shokri; Carmela Troncoso; Jean-Pierre Hubaux; Jean-Yves Le Boudec (WPES, 2014)

Privacy Games: Optimal Protection Mechanism Design for Bayesian and Differential Privacy. - Reza Shokri (CoRR, 2014)

Hiding in the Mobile Crowd: LocationPrivacy through Collaboration. - Reza Shokri; George Theodorakopoulos 001; Panos Papadimitratos; Ehsan Kazemi 001; Jean-Pierre Hubaux (IEEE Trans. Dependable Secur. Comput., 2014)

Privacy-Preserving Deep Learning. - Reza Shokri; Vitaly Shmatikov (CCS, 2015)

Predicting Users' Motivations behind Location Check-Ins and Utility Implications of Privacy Protection Mechanisms. - Igor Bilogrevic; Kévin Huguenin; Stefan Mihaila; Reza Shokri; Jean-Pierre Hubaux (NDSS, 2015)

Privacy through Fake yet Semantically Real Traces. - Vincent Bindschaedler; Reza Shokri (CoRR, 2015)

Quantifying and protecting location privacy. - Reza Shokri (it Inf. Technol., 2015)

Privacy Games: Optimal User-Centric Data Obfuscation. - Reza Shokri (Proc. Priv. Enhancing Technol., 2015)

Synthesizing Plausible Privacy-Preserving Location Traces. - Vincent Bindschaedler; Reza Shokri (IEEE Symposium on Security and Privacy, 2016)

Defeating Image Obfuscation with Deep Learning. - Richard McPherson; Reza Shokri; Vitaly Shmatikov (CoRR, 2016)

Membership Inference Attacks against Machine Learning Models. - Reza Shokri; Marco Stronati; Vitaly Shmatikov (CoRR, 2016)

Membership Inference Attacks Against Machine Learning Models. - Reza Shokri; Marco Stronati; Congzheng Song; Vitaly Shmatikov (IEEE Symposium on Security and Privacy, 2017)

Plausible Deniability for Privacy-Preserving Data Synthesis. - Vincent Bindschaedler; Reza Shokri; Carl A. Gunter (Proc. VLDB Endow., 2017)

Privacy Games Along Location Traces: A Game-Theoretic Framework for Optimizing Location Privacy. - Reza Shokri; George Theodorakopoulos 001; Carmela Troncoso (ACM Trans. Priv. Secur., 2017)

Quantifying Interdependent Privacy Risks with Location Data. - Alexandra-Mihaela Olteanu; Kévin Huguenin; Reza Shokri; Mathias Humbert; Jean-Pierre Hubaux (IEEE Trans. Mob. Comput., 2017)

Machine Learning with Membership Privacy using Adversarial Regularization. - Milad Nasr; Reza Shokri; Amir Houmansadr (CCS, 2018)

A Non-Parametric Generative Model for Human Trajectories. - Kun Ouyang; Reza Shokri; David S. Rosenblum; Wenzhuo Yang (IJCAI, 2018)

Chiron: Privacy-preserving Machine Learning as a Service. - Tyler Hunt; Congzheng Song; Reza Shokri; Vitaly Shmatikov; Emmett Witchel (CoRR, 2018)

Comprehensive Privacy Analysis of Deep Learning: Stand-alone and Federated Learning under Passive and Active White-box Inference Attacks. - Milad Nasr; Reza Shokri; Amir Houmansadr (CoRR, 2018)

A Predictive Model for User Motivation and Utility Implications of Privacy-Protection Mechanisms in Location Check-Ins. - Kévin Huguenin; Igor Bilogrevic; Joana Soares Machado; Stefan Mihaila; Reza Shokri; Italo Dacosta; Jean-Pierre Hubaux (IEEE Trans. Mob. Comput., 2018)

Privacy Risks of Securing Machine Learning Models against Adversarial Examples. - Liwei Song; Reza Shokri; Prateek Mittal (CCS, 2019)

Trusting Machine Learning: Privacy, Robustness, and Transparency Challenges. - Reza Shokri (IH&MMSec, 2019)

Comprehensive Privacy Analysis of Deep Learning: Passive and Active White-box Inference Attacks against Centralized and Federated Learning. - Milad Nasr; Reza Shokri; Amir Houmansadr (IEEE Symposium on Security and Privacy, 2019)

Membership Inference Attacks Against Adversarially Robust Deep Learning Models. - Liwei Song; Reza Shokri; Prateek Mittal (IEEE Symposium on Security and Privacy Workshops, 2019)

Ultimate Power of Inference Attacks: Privacy Risks of High-Dimensional Models. - Sasi Kumar Murakonda; Reza Shokri; George Theodorakopoulos 001 (CoRR, 2019)

Privacy Risks of Explaining Machine Learning Models. - Reza Shokri; Martin Strobel 001; Yair Zick (CoRR, 2019)

Cronus: Robust and Heterogeneous Collaborative Learning with Black-Box Knowledge Transfer. - Hongyan Chang; Virat Shejwalkar; Reza Shokri; Amir Houmansadr (CoRR, 2019)

Membership Encoding for Deep Learning. - Congzheng Song; Reza Shokri (AsiaCCS, 2020)

Bypassing Backdoor Detection Algorithms in Deep Learning. - Te Juin Lester Tan; Reza Shokri (EuroS&P, 2020)

On Adversarial Bias and the Robustness of Fair Machine Learning. - Hongyan Chang; Ta Duy Nguyen; Sasi Kumar Murakonda; Ehsan Kazemi 001; Reza Shokri (CoRR, 2020)

ML Privacy Meter: Aiding Regulatory Compliance by Quantifying the Privacy Risks of Machine Learning. - Sasi Kumar Murakonda; Reza Shokri (CoRR, 2020)

Improving Deep Learning with Differential Privacy using Gradient Encoding and Denoising. - Milad Nasr; Reza Shokri; Amir Houmansadr (CoRR, 2020)

SOTERIA: In Search of Efficient Neural Networks for Private Inference. - Anshul Aggarwal; Trevor E. Carlson; Reza Shokri; Shruti Tople (CoRR, 2020)

Epione: Lightweight Contact Tracing with Strong Privacy. - Ni Trieu; Kareem Shehata; Prateek Saxena; Reza Shokri; Dawn Song (IEEE Data Eng. Bull., 2020)

On the Privacy Risks of Model Explanations. - Reza Shokri; Martin Strobel 001; Yair Zick (AIES, 2021)

Quantifying the Privacy Risks of Learning High-Dimensional Graphical Models. - Sasi Kumar Murakonda; Reza Shokri; George Theodorakopoulos 001 (AISTATS, 2021)

On the Privacy Risks of Algorithmic Fairness. - Hongyan Chang; Reza Shokri (EuroS&P, 2021)

Differential Privacy Dynamics of Langevin Diffusion and Noisy Gradient Descent. - Rishav Chourasia; Jiayuan Ye 001; Reza Shokri (NeurIPS, 2021)

Enhanced Membership Inference Attacks against Machine Learning Models. - Jiayuan Ye 001; Aadyaa Maddi; Sasi Kumar Murakonda; Reza Shokri (CoRR, 2021)

Enhanced Membership Inference Attacks against Machine Learning Models. - Jiayuan Ye 001; Aadyaa Maddi; Sasi Kumar Murakonda; Vincent Bindschaedler; Reza Shokri (CCS, 2022)

Truth Serum: Poisoning Machine Learning Models to Reveal Their Secrets. - Florian Tramèr; Reza Shokri; Ayrton San Joaquin; Hoang Le; Matthew Jagielski; Sanghyun Hong 001; Nicholas Carlini (CCS, 2022)

Quantifying Privacy Risks of Masked Language Models Using Membership Inference Attacks. - Fatemehsadat Mireshghallah; Kartik Goyal; Archit Uniyal; Taylor Berg-Kirkpatrick; Reza Shokri (EMNLP, 2022)

What Does it Mean for a Language Model to Preserve Privacy? - Hannah Brown; Katherine Lee; Fatemehsadat Mireshghallah; Reza Shokri; Florian Tramèr (FAccT, 2022)

Model Explanations with Differential Privacy. - Neel Patel; Reza Shokri; Yair Zick (FAccT, 2022)

Differentially Private Learning Needs Hidden State (Or Much Faster Convergence). - Jiayuan Ye 001; Reza Shokri (NeurIPS, 2022)

Forget Unlearning: Towards True Data-Deletion in Machine Learning. - Rishav Chourasia; Neil Shah; Reza Shokri (CoRR, 2022)

Data Privacy and Trustworthy Machine Learning. - Martin Strobel 001; Reza Shokri (IEEE Secur. Priv., 2022)

On The Impact of Machine Learning Randomness on Group Fairness. - Prakhar Ganesh; Hongyan Chang; Martin Strobel 001; Reza Shokri (FAccT, 2023)

Multipolar Stimulator for DBS Application with Concurrent Imbalance Compensation. - Reza Shokri; Yarallah Koolivand; Omid Shoaei; Orazio Aiello; Daniele D. Caviglia (ICECS, 2023)

Bias Propagation in Federated Learning. - Hongyan Chang; Reza Shokri (ICLR, 2023)

Share Your Representation Only: Guaranteed Improvement of the Privacy-Utility Tradeoff in Federated Learning. - Zebang Shen; Jiayuan Ye 001; Anmin Kang; Hamed Hassani; Reza Shokri (ICLR, 2023)

Initialization Matters: Privacy-Utility Analysis of Overparameterized Neural Networks. - Jiayuan Ye 001; Zhenyu Zhu; Fanghui Liu 001; Reza Shokri; Volkan Cevher (NeurIPS, 2023)

Unified Enhancement of Privacy Bounds for Mixture Mechanisms via f-Differential Privacy. - Chendi Wang; Buxin Su; Jiayuan Ye 001; Reza Shokri; Weijie J. Su (NeurIPS, 2023)

Smaller Language Models are Better Black-box Machine-Generated Text Detectors. - Fatemehsadat Mireshghallah; Justus Mattern; Sicun Gao; Reza Shokri; Taylor Berg-Kirkpatrick (CoRR, 2023)

Low-Cost High-Power Membership Inference by Boosting Relativity. - Sajjad Zarifzadeh; Philippe Liu; Reza Shokri (CoRR, 2023)

Smaller Language Models are Better Zero-shot Machine-Generated Text Detectors. - Niloofar Mireshghallah; Justus Mattern; Sicun Gao; Reza Shokri; Taylor Berg-Kirkpatrick (EACL (2), 2024)

Leave-one-out Distinguishability in Machine Learning. - Jiayuan Ye 001; Anastasia Borovykh; Soufiane Hayou; Reza Shokri (ICLR, 2024)

Can LLMs Keep a Secret? Testing Privacy Implications of Language Models via Contextual Integrity Theory. - Niloofar Mireshghallah; Hyunwoo Kim 002; Xuhui Zhou; Yulia Tsvetkov; Maarten Sap; Reza Shokri; Yejin Choi 001 (ICLR, 2024)

Low-Cost High-Power Membership Inference Attacks. - Sajjad Zarifzadeh; Philippe Liu; Reza Shokri (ICML, 2024)

Highly Linear, Digital OTA With Modified Input Stage. - Reza Shokri; Daniele D. Caviglia; Orazio Aiello (PRIME, 2024)

Efficient Privacy Auditing in Federated Learning. - Hongyan Chang; Brandon Edwards; Anindya S. Paul; Reza Shokri (USENIX Security Symposium, 2024)

Watermark Smoothing Attacks against Language Models. - Hongyan Chang; Hamed Hassani; Reza Shokri (CoRR, 2024)

Context-Aware Membership Inference Attacks against Pre-trained Large Language Models. - Hongyan Chang; Ali Shahin Shamsabadi; Kleomenis Katevas; Hamed Haddadi; Reza Shokri (CoRR, 2024)

A Reconfigurable, Nonlinear, Low-Power, VCO-Based ADC for Neural Recording Applications. - Reza Shokri; Yarallah Koolivand; Omid Shoaei; Daniele D. Caviglia; Orazio Aiello (Sensors, 2024)

The Data Minimization Principle in Machine Learning. - Prakhar Ganesh; Cuong Tran 007; Reza Shokri; Ferdinando Fioretto (FAccT, 2025)

How much of my dataset did you use? Quantitative Data Usage Inference in Machine Learning. - Yao Tong; Jiayuan Ye 001; Sajjad Zarifzadeh; Reza Shokri (ICLR, 2025)

Sub-10nW, 73dB Gain, Inverter-Based Digital OTA with C-Muller Input Stage and Novel CMFB for Enhanced Performance in IoT Applications. - Riccardo Della Sala; Reza Shokri; Orazio Aiello; Daniele D. Caviglia; Giuseppe Scotti (NewCAS, 2025)

Range Membership Inference Attacks. - Jiashu Tao; Reza Shokri (SaTML, 2025)

Multipolar Stimulator for Deep Brain Stimulation With Suppression of Stimulation-Induced Common-Mode Artifacts. - Reza Shokri; Yarallah Koolivand; Omid Shoaei; Daniele D. Caviglia; Orazio Aiello (IEEE Access, 2025)

Firewalls to Secure Dynamic LLM Agentic Networks. - Sahar Abdelnabi; Amr Gomaa; Eugene Bagdasarian; Per Ola Kristensson; Reza Shokri (CoRR, 2025)

Minerva: A Programmable Memory Test Benchmark for Language Models. - Menglin Xia; Victor Rühle; Saravan Rajmohan; Reza Shokri (CoRR, 2025)

The Canary's Echo: Auditing Privacy Risks of LLM-Generated Synthetic Text. - Matthieu Meeus; Lukas Wutschitz; Santiago Zanella-Béguelin; Shruti Tople; Reza Shokri (CoRR, 2025)

Contextual Integrity in LLMs via Reasoning and Reinforcement Learning. - Guangchen Lan; Huseyin A. Inan; Sahar Abdelnabi; Janardhan Kulkarni; Lukas Wutschitz; Reza Shokri; Christopher G. Brinton; Robert Sim (CoRR, 2025)

Machine Learning from Explanations. - Jiashu Tao; Reza Shokri (CoRR, 2025)