Alphacodes: Usable, Secure Transactions with Untrusted Providers using Human Computable Puzzles. - Ashlesh Sharma; Varun Chandrasekaran; Fareeha Amjad; Dennis E. Shasha; Lakshminarayanan Subramanian (ACM DEV, 2016)

Secure Mobile Identities. - Varun Chandrasekaran; Fareeha Amjad; Ashlesh Sharma; Lakshminarayanan Subramanian (CoRR, 2016)

Traversing the Quagmire that is Privacy in your Smart Home. - Chuhan Gao; Varun Chandrasekaran; Kassem Fawaz; Suman Banerjee 001 (IoT S&P@SIGCOMM, 2018)

Model Extraction and Active Learning. - Varun Chandrasekaran; Kamalika Chaudhuri; Irene Giacomelli; Somesh Jha; Songbai Yan (CoRR, 2018)

Characterizing Privacy Perceptions of Voice Assistants: A Technology Probe Study. - Varun Chandrasekaran; Kassem Fawaz; Bilge Mutlu; Suman Banerjee 001 (CoRR, 2018)

A Framework for Analyzing Spectrum Characteristics in Large Spatio-temporal Scales. - Yijing Zeng; Varun Chandrasekaran; Suman Banerjee 001; Domenico Giustiniano (MobiCom, 2019)

Enhancing ML Robustness Using Physical-World Constraints. - Varun Chandrasekaran; Brian Tang; Varsha Pendyala; Kassem Fawaz; Somesh Jha; Xi Wu 001 (CoRR, 2019)

Generating Semantic Adversarial Examples with Differentiable Rendering. - Lakshya Jain; Wilson Wu; Steven Chen; Uyeong Jang; Varun Chandrasekaran; Sanjit A. Seshia; Somesh Jha (CoRR, 2019)

Third International Workshop on Dependable and Secure Machine Learning - DSML 2020. - Homa Alemzadeh; Rakesh Bobba; Varun Chandrasekaran; David E. Evans 001; Nicolas Papernot; Karthik Pattabiraman; Florian Tramèr (DSN Workshops, 2020)

Exploring Connections Between Active Learning and Model Extraction. - Varun Chandrasekaran; Kamalika Chaudhuri; Irene Giacomelli; Somesh Jha; Songbai Yan (USENIX Security Symposium, 2020)

On the Effectiveness of Mitigating Data Poisoning Attacks with Gradient Shaping. - Sanghyun Hong 001; Varun Chandrasekaran; Yigitcan Kaya; Tudor Dumitras; Nicolas Papernot (CoRR, 2020)

Face-Off: Adversarial Face Obfuscation. - Chuhan Gao; Varun Chandrasekaran; Kassem Fawaz; Somesh Jha (CoRR, 2020)

Detecting Anomalous Inputs to DNN Classifiers By Joint Statistical Testing at the Layers. - Jayaram Raghuram; Varun Chandrasekaran; Somesh Jha; Suman Banerjee 001 (CoRR, 2020)

Fourth International Workshop on Dependable and Secure Machine Learning - DSML 2021. - Hui Xu 009; Guanpeng Li; Homa Alemzadeh; Rakesh Bobba; Varun Chandrasekaran; David E. Evans 001; Nicolas Papernot; Karthik Pattabiraman; Florian Tramèr (DSN Workshops, 2021)

A General Framework For Detecting Anomalous Inputs to DNN Classifiers. - Jayaram Raghuram; Varun Chandrasekaran; Somesh Jha; Suman Banerjee 001 (ICML, 2021)

PowerCut and Obfuscator: An Exploration of the Design Space for Privacy-Preserving Interventions for Smart Speakers. - Varun Chandrasekaran; Suman Banerjee 001; Bilge Mutlu; Kassem Fawaz (SOUPS @ USENIX Security Symposium, 2021)

Machine Unlearning. - Lucas Bourtoule; Varun Chandrasekaran; Christopher A. Choquette-Choo; Hengrui Jia 001; Adelin Travers; Baiwu Zhang; David Lie; Nicolas Papernot (SP, 2021)

Proof-of-Learning: Definitions and Practice. - Hengrui Jia 001; Mohammad Yaghini; Christopher A. Choquette-Choo; Natalie Dullerud; Anvith Thudi; Varun Chandrasekaran; Nicolas Papernot (SP, 2021)

Entangled Watermarks as a Defense against Model Extraction. - Hengrui Jia 001; Christopher A. Choquette-Choo; Varun Chandrasekaran; Nicolas Papernot (USENIX Security Symposium, 2021)

Causally Constrained Data Synthesis for Private Data Release. - Varun Chandrasekaran; Darren Edge; Somesh Jha; Amit Sharma 007; Cheng Zhang 005; Shruti Tople (CoRR, 2021)

On the Exploitability of Audio Machine Learning Pipelines to Surreptitious Adversarial Examples. - Adelin Travers; Lorna Licollari; Guanghan Wang; Varun Chandrasekaran; Adam Dziedzic; David Lie; Nicolas Papernot (CoRR, 2021)

SoK: Machine Learning Governance. - Varun Chandrasekaran; Hengrui Jia 001; Anvith Thudi; Adelin Travers; Mohammad Yaghini; Nicolas Papernot (CoRR, 2021)

Face-Off: Adversarial Face Obfuscation. - Varun Chandrasekaran; Chuhan Gao; Brian Tang; Kassem Fawaz; Somesh Jha; Suman Banerjee 001 (Proc. Priv. Enhancing Technol., 2021)

Unrolling SGD: Understanding Factors Influencing Machine Unlearning. - Anvith Thudi; Gabriel Deza; Varun Chandrasekaran; Nicolas Papernot (EuroS&P, 2022)

CONFIDANT: A Privacy Controller for Social Robots. - Brian Tang; Dakota Sullivan; Bengisu Cagiltay; Varun Chandrasekaran; Kassem Fawaz; Bilge Mutlu (HRI, 2022)

Generative Extraction of Audio Classifiers for Speaker Identification. - Tejumade Afonja; Lucas Bourtoule; Varun Chandrasekaran; Sageev Oore; Nicolas Papernot (CoRR, 2022)

On the Fundamental Limits of Formally (Dis)Proving Robustness in Proof-of-Learning. - Congyu Fang; Hengrui Jia 001; Anvith Thudi; Mohammad Yaghini; Christopher A. Choquette-Choo; Natalie Dullerud; Varun Chandrasekaran; Nicolas Papernot (CoRR, 2022)

Proof-of-Learning is Currently More Broken Than You Think. - Congyu Fang; Hengrui Jia 001; Anvith Thudi; Mohammad Yaghini; Christopher A. Choquette-Choo; Natalie Dullerud; Varun Chandrasekaran; Nicolas Papernot (EuroS&P, 2023)

Sparks of Artificial General Intelligence: Early experiments with GPT-4. - Sébastien Bubeck; Varun Chandrasekaran; Ronen Eldan; Johannes Gehrke; Eric Horvitz; Ece Kamar; Peter Lee; Yin Tat Lee; Yuanzhi Li; Scott M. Lundberg; Harsha Nori; Hamid Palangi; et al. (CoRR, 2023)

Diversity of Thought Improves Reasoning Abilities of Large Language Models. - Ranjita Naik; Varun Chandrasekaran; Mert Yüksekgönül; Hamid Palangi; Besmira Nushi (CoRR, 2023)

Why Train More? Effective and Efficient Membership Inference via Memorization. - Jihye Choi; Shruti Tople; Varun Chandrasekaran; Somesh Jha (CoRR, 2023)

Bypassing LLM Watermarks with Color-Aware Substitutions. - Qilong Wu 002; Varun Chandrasekaran (ACL (1), 2024)

Designing Informative Metrics for Few-Shot Example Selection. - Rishabh Adiga; Lakshmi Subramanian; Varun Chandrasekaran (ACL (Findings), 2024)

Hierarchical Federated Learning with Privacy. - Varun Chandrasekaran; Suman Banerjee 001; Diego Perino; Nicolas Kourtellis (IEEE Big Data, 2024)

KITAB: Evaluating LLMs on Constraint Satisfaction for Information Retrieval. - Marah I Abdin; Suriya Gunasekar; Varun Chandrasekaran; Jerry Li; Mert Yüksekgönül; Rahee Ghosh Peshawaria; Ranjita Naik; Besmira Nushi (ICLR, 2024)

Teaching Language Models to Hallucinate Less with Synthetic Tasks. - Erik Jones; Hamid Palangi; Clarisse Simões; Varun Chandrasekaran; Subhabrata Mukherjee; Arindam Mitra; Ahmed Hassan Awadallah; Ece Kamar (ICLR, 2024)

Privately Aligning Language Models with Reinforcement Learning. - Fan Wu; Huseyin A. Inan; Arturs Backurs; Varun Chandrasekaran; Janardhan Kulkarni; Robert Sim (ICLR, 2024)

Attention Satisfies: A Constraint-Satisfaction Lens on Factual Errors of Language Models. - Mert Yüksekgönül; Varun Chandrasekaran; Erik Jones; Suriya Gunasekar; Ranjita Naik; Hamid Palangi; Ece Kamar; Besmira Nushi (ICLR, 2024)

LOTOS: Layer-wise Orthogonalization for Training Robust Ensembles. - Ali Ebrahimpour Boroojeny; Hari Sundaram; Varun Chandrasekaran (CoRR, 2024)

BENCHAGENTS: Automated Benchmark Creation with Agent Interaction. - Natasha Butt; Varun Chandrasekaran; Neel Joshi; Besmira Nushi; Vidhisha Balachandran (CoRR, 2024)

The Efficacy of Transfer-based No-box Attacks on Image Watermarking: A Pragmatic Analysis. - Qilong Wu 002; Varun Chandrasekaran (CoRR, 2024)

Attention Speaks Volumes: Localizing and Mitigating Bias in Language Models. - Rishabh Adiga; Besmira Nushi; Varun Chandrasekaran (ACL (1), 2025)

Training Robust Ensembles Requires Rethinking Lipschitz Continuity. - Ali Ebrahimpour Boroojeny; Hari Sundaram; Varun Chandrasekaran (ICLR, 2025)

Unearthing Skill-level Insights for Understanding Trade-offs of Foundation Models. - Mazda Moayeri; Vidhisha Balachandran; Varun Chandrasekaran; Safoora Yousefi; Thomas Fel; Soheil Feizi; Besmira Nushi; Neel Joshi; Vibhav Vineet (ICLR, 2025)

Generative Monoculture in Large Language Models. - Fan Wu; Emily Black; Varun Chandrasekaran (ICLR, 2025)

Verifiable and Provably Secure Machine Unlearning. - Thorsten Eisenhofer; Doreen Riepel; Varun Chandrasekaran; Esha Ghosh; Olga Ohrimenko; Nicolas Papernot (SaTML, 2025)

MM-GEN: Enhancing Task Performance Through Targeted Multimodal Data Curation. - Siddharth Joshi 004; Besmira Nushi; Vidhisha Balachandran; Varun Chandrasekaran; Vibhav Vineet; Neel Joshi; Baharan Mirzasoleiman (CoRR, 2025)

AMUN: Adversarial Machine UNlearning. - Ali Ebrahimpour Boroojeny; Hari Sundaram; Varun Chandrasekaran (CoRR, 2025)

LLM-Driven Multi-step Translation from C to Rust using Static Analysis. - Tianyang Zhou; Haowen Lin; Somesh Jha; Mihai Christodorescu; Kirill Levchenko; Varun Chandrasekaran (CoRR, 2025)

Analyzing Security and Privacy Challenges in Generative AI Usage Guidelines for Higher Education. - Bei Yi Ng; Jiarui Li; Xinyuan Tong; Kevin Ye; Gauthami Yenne; Varun Chandrasekaran; Jingjie Li (CoRR, 2025)