Author

Anadi Goyal

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Nov 2026

Secure Hardware Accelerator for Resilience Against Adversarial Attacks in ViTs

Vision Transformers (ViTs) have demonstrated exceptional performance across various computer vision tasks. However, their susceptibility to adversarial white-box attacks poses a significant risk, especially in safety-critical applications. These attacks, with full model access, pose severe threat by drastically reducin...

Deepraj Majumdar, Anadi Goyal, Sparsh Mittal et al. · IEEE transactions on compute... · 0 citations

Preprint Aug 2026

MOAT: Model-Agnostic Randomized Transformations for preventing Efficiency Degradation Attacks on ViTs

MOAT is proposed, a model-agnostic pre-processing defense pipeline that applies a combination of input transformations to protect efficient ViT implementations against adversarial efficiency attacks.

Anadi Goyal, Nandish Chattopadhyay, C. Karfa et al. · 0 citations

Review Aug 2026

A Survey of Adversarial Efficiency Degradation for Vision Transformer by Exploiting Input-adaptive Optimization

This survey examines a recent class of adversarial efficiency degradation attacks that target these mechanisms to increase computation without necessarily degrading accuracy, and unify and compare two representative attacks across three popular token-pruning frameworks.

Anadi Goyal, Nandish Chattopadhyay, Anupam Chattopadhyay et al. · 0 citations