4 papers · 1 filter
A Survey of Adversarial Efficiency Degradation for Vision Transformer by Exploiting Input-adaptive Optimization
Anadi Goyal, Nandish Chattopadhyay, Anupam Chattopadhyay +1
Vision Transformers (ViTs) increasingly rely on input-adaptive inference, such as token pruning and early halting, to meet energy and latency budgets. This survey examines a recent…
MOAT: Model-Agnostic Randomized Transformations for preventing Efficiency Degradation Attacks on ViTs
Anadi Goyal, Nandish Chattopadhyay, Chandan Karfa +2
To adopt the Vision Transformers (ViTs) in resource-constrained environment, token pruning is widely used to reduce computational cost without impacting accuracy. However, adversar…
Controller Datapath Aware Verification of Masked Hardware Generated via High Level Synthesis
Nilotpola Sarma, Vaishali Ghanshyam Chaudhuri, Chandan Karfa
Masking is a countermeasure against Power Side Channel Attacks (PSCAs) in both software and hardware implementations of cryptographic algorithms. Compared to software masking, impl…
MaskedHLS: Domain-Specific High-Level Synthesis of Masked Cryptographic Designs
Nilotpola Sarma, Anuj Singh Thakur, Chandan Karfa
The design and synthesis of masked cryptographic hardware implementations that are secure against power side-channel attacks (PSCAs) in the presence of glitches is a challenging ta…