Invisible Perturbations: Physical Adversarial Examples Exploiting the Rolling Shutter Effect. - Athena Sayles; Ashish Hooda; Mohit Gupta 001; Rahul Chatterjee 001; Earlence Fernandes (CVPR, 2021)

Towards Adversarially Robust Deepfake Detection: An Ensemble Approach. - Ashish Hooda; Neal Mangaokar; Ryan Feng; Kassem Fawaz; Somesh Jha; Atul Prakash 001 (CoRR, 2022)

Re-purposing Perceptual Hashing based Client Side Scanning for Physical Surveillance. - Ashish Hooda; Andrey Labunets; Tadayoshi Kohno; Earlence Fernandes (CoRR, 2022)

SkillFence: A Systems Approach to Practically Mitigating Voice-Based Confusion Attacks. - Ashish Hooda; Matthew Wallace; Kushal Jhunjhunwalla; Earlence Fernandes; Kassem Fawaz (Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2022)

Stateful Defenses for Machine Learning Models Are Not Yet Secure Against Black-box Attacks. - Ryan Feng; Ashish Hooda; Neal Mangaokar; Kassem Fawaz; Somesh Jha; Atul Prakash 001 (CCS, 2023)

Investigating Stateful Defenses Against Black-Box Adversarial Examples. - Ryan Feng; Ashish Hooda; Neal Mangaokar; Kassem Fawaz; Somesh Jha; Atul Prakash 001 (CoRR, 2023)

Theoretically Principled Trade-off for Stateful Defenses against Query-Based Black-Box Attacks. - Ashish Hooda; Neal Mangaokar; Ryan Feng; Kassem Fawaz; Somesh Jha; Atul Prakash 001 (CoRR, 2023)

PRP: Propagating Universal Perturbations to Attack Large Language Model Guard-Rails. - Neal Mangaokar; Ashish Hooda; Jihye Choi; Shreyas Chandrashekaran; Kassem Fawaz; Somesh Jha; Atul Prakash 001 (ACL (1), 2024)

Do Large Code Models Understand Programming Concepts? Counterfactual Analysis for Code Predicates. - Ashish Hooda; Mihai Christodorescu; Miltiadis Allamanis; Aaron Wilson; Kassem Fawaz; Somesh Jha (ICML, 2024)

Experimental Analyses of the Physical Surveillance Risks in Client-Side Content Scanning. - Ashish Hooda; Andrey Labunets; Tadayoshi Kohno; Earlence Fernandes (NDSS, 2024)

D4: Detection of Adversarial Diffusion Deepfakes Using Disjoint Ensembles. - Ashish Hooda; Neal Mangaokar; Ryan Feng; Kassem Fawaz; Somesh Jha; Atul Prakash 001 (WACV, 2024)

Do Large Code Models Understand Programming Concepts? A Black-box Approach. - Ashish Hooda; Mihai Christodorescu; Miltiadis Allamanis; Aaron Wilson; Kassem Fawaz; Somesh Jha (CoRR, 2024)

Synthetic Counterfactual Faces. - Guruprasad V. Ramesh; Harrison Rosenberg; Ashish Hooda; Shimaa Ahmed; Kassem Fawaz (CoRR, 2024)

PolicyLR: A Logic Representation For Privacy Policies. - Ashish Hooda; Rishabh Khandelwal; Prasad Chalasani; Kassem Fawaz; Somesh Jha (CoRR, 2024)

Functional Homotopy: Smoothing Discrete Optimization via Continuous Parameters for LLM Jailbreak Attacks. - Zi Wang; Divyam Anshumaan; Ashish Hooda; Yudong Chen; Somesh Jha (ICLR, 2025)

Fun-tuning: Characterizing the Vulnerability of Proprietary LLMs to Optimization-Based Prompt Injection Attacks via the Fine-Tuning Interface. - Andrey Labunets; Nishit V. Pandya; Ashish Hooda; Xiaohan Fu; Earlence Fernandes (SP, 2025)

Computing Optimization-Based Prompt Injections Against Closed-Weights Models By Misusing a Fine-Tuning API. - Andrey Labunets; Nishit V. Pandya; Ashish Hooda; Xiaohan Fu; Earlence Fernandes (CoRR, 2025)

Through the Stealth Lens: Rethinking Attacks and Defenses in RAG. - Sarthak Choudhary; Nils Palumbo; Ashish Hooda; Krishnamurthy Dj Dvijotham; Somesh Jha (CoRR, 2025)

What Really is a Member? Discrediting Membership Inference via Poisoning. - Neal Mangaokar; Ashish Hooda; Zhuohang Li; Bradley A. Malin; Kassem Fawaz; Somesh Jha; Atul Prakash 001; Amrita Roy Chowdhury 001 (CoRR, 2025)