78 citations · 91 across the 6 of their papers we have counts for
6 papers
Machine Learning Power Side-Channel Attack on SNOW-V
Deepak, Rahul Balout, Anupam Golder +3
This paper demonstrates a power analysis-based Side-Channel Analysis (SCA) attack on the SNOW-V encryption algorithm, which is a 5G mobile communication security standard candidate…
Leveraging ASIC AI Chips for Homomorphic Encryption
Jianming Tong, Tianhao Huang, Jingtian Dang +9
Homomorphic Encryption (HE) provides strong data privacy for cloud services but at the cost of prohibitive computational overhead. While GPUs have emerged as a practical platform f…
Accurate Low-Degree Polynomial Approximation of Non-polynomial Operators for Fast Private Inference in Homomorphic Encryption
Jianming Tong, Jingtian Dang, Anupam Golder +3
As machine learning (ML) permeates fields like healthcare, facial recognition, and blockchain, the need to protect sensitive data intensifies. Fully Homomorphic Encryption (FHE) al…
SNOW-SCA: ML-assisted Side-Channel Attack on SNOW-V
Harshit Saurabh, Anupam Golder, Samarth Shivakumar Titti +4
This paper presents SNOW-SCA, the first power side-channel analysis (SCA) attack of a 5G mobile communication security standard candidate, SNOW-V, running on a 32-bit ARM Cortex-M4…
EM-X-DL: Efficient Cross-Device Deep Learning Side-Channel Attack with Noisy EM Signatures
Josef Danial, Debayan Das, Anupam Golder +3
This work presents a Cross-device Deep-Learning based Electromagnetic (EM-X-DL) side-channel analysis (SCA), achieving >90% single-trace attack accuracy on AES-128, even in the pre…
Practical Approaches Towards Deep-Learning Based Cross-Device Power Side Channel Attack
Anupam Golder, Debayan Das, Josef Danial +3
Power side-channel analysis (SCA) has been of immense interest to most embedded designers to evaluate the physical security of the system. This work presents profiling-based cross-…