Ashish Hooda

According to our database, Ashish Hooda authored at least 24 papers between 2021 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

Agent Security is a Systems Problem.

Mihai Christodorescu, Earlence Fernandes, Ashish Hooda, Somesh Jha, Johann Rehberger, Kamalika Chaudhuri, Xiaohan Fu, Khawaja Shams, Guy Amir, Jihye Choi, Sarthak Choudhary, Nils Palumbo, Andrey Labunets, Nishit V. Pandya

CoRR, May, 2026

Undetectable Backdoors in Model Parameters: Hiding Sparse Secrets in High Dimensions.

Sarthak Choudhary, Atharv Singh Patlan, Nils Palumbo, Ashish Hooda, Kassem Fawaz, Somesh Jha

CoRR, May, 2026

CounterFace: A Synthetic Face Dataset for Fine-Grained Counterfactual Evaluation of Face Recognition Systems.

Guruprasad Viswanathan Ramesh, Ashish Hooda, Shimaa Ahmed, Harrison J. Rosenberg, Ramya Korlakai Vinayak, Kassem Fawaz

Proceedings of the 2026 ACM Conference on Fairness, Accountability, and Transparency, 2026

2025

Auto-SPT: Automating Semantic Preserving Transformations for Code.

Ashish Hooda, Mihai Christodorescu, Chuangang Ren, Aaron Wilson, Kassem Fawaz, Somesh Jha

CoRR, December, 2025

Through the Stealth Lens: Rethinking Attacks and Defenses in RAG.

Sarthak Choudhary, Nils Palumbo, Ashish Hooda, Krishnamurthy Dj Dvijotham, Somesh Jha

CoRR, June, 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, January, 2025

Systems Security Foundations for Agentic Computing.

Mihai Christodorescu, Earlence Fernandes, Ashish Hooda, Somesh Jha, Johann Rehberger, Khawaja Shams

IACR Cryptol. ePrint Arch., 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

Proceedings of the IEEE Symposium on Security and Privacy, 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, Amrita Roy Chowdhury

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

Functional Homotopy: Smoothing Discrete Optimization via Continuous Parameters for LLM Jailbreak Attacks.

Zi Wang, Divyam Anshumaan, Ashish Hooda, Yudong Chen, Somesh Jha

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

PolicyLR: A Logic Representation For Privacy Policies.

Ashish Hooda, Rishabh Khandelwal, Prasad Chalasani, Kassem Fawaz, Somesh Jha

CoRR, 2024

Synthetic Counterfactual Faces.

Guruprasad V. Ramesh, Harrison Rosenberg, Ashish Hooda, Shimaa Ahmed, Kassem Fawaz

CoRR, 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

D4: Detection of Adversarial Diffusion Deepfakes Using Disjoint Ensembles.

Ashish Hooda, Neal Mangaokar, Ryan Feng, Kassem Fawaz, Somesh Jha, Atul Prakash

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

Experimental Analyses of the Physical Surveillance Risks in Client-Side Content Scanning.

Ashish Hooda, Andrey Labunets, Tadayoshi Kohno, Earlence Fernandes

Proceedings of the 31st Annual Network and Distributed System Security Symposium, 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

Proceedings of the Forty-first International Conference on Machine Learning, 2024

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

Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

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

CoRR, 2023

Investigating Stateful Defenses Against Black-Box Adversarial Examples.

Ryan Feng, Ashish Hooda, Neal Mangaokar, Kassem Fawaz, Somesh Jha, Atul Prakash

CoRR, 2023

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

Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security, 2023

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

Re-purposing Perceptual Hashing based Client Side Scanning for Physical Surveillance.

Ashish Hooda, Andrey Labunets, Tadayoshi Kohno, Earlence Fernandes

CoRR, 2022

Towards Adversarially Robust Deepfake Detection: An Ensemble Approach.

Ashish Hooda, Neal Mangaokar, Ryan Feng, Kassem Fawaz, Somesh Jha, Atul Prakash

CoRR, 2022

2021

Invisible Perturbations: Physical Adversarial Examples Exploiting the Rolling Shutter Effect.

Athena Sayles, Ashish Hooda, Mohit Gupta, Rahul Chatterjee, Earlence Fernandes

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021