AVX2 Implementation Did Not Fully Reduce Intermediate Values

The AVX2 implementation of ML-DSA did not fully reduce intermediate inputs to the inverse NTT, which leads to a testable difference in panic behaviour of internal functions compared to the portable implementation. Impact We are not aware of inputs to the public key generation, signing or...

DRAMatic Speedup: Accelerating HE Operations on a Processing-In-Memory System

Homomorphic encryption HE is a promising technology for confidential cloud computing, as it allows computations on encrypted data. However, HE is computationally expensive and often memory-bound on conventional computer architectures. Processing-in-Memory PIM is an alternative hardware architectu...

Lightweight Fault Detection Architecture for NTT on FPGA

Post-Quantum Cryptographic PQC algorithms are mathematically secure and resistant to quantum attacks but can still leak sensitive information in hardware implementations due to natural faults or intentional fault injections. The intent fault injection in side-channel attacks reduces the reliabili...

Characterizing the Sensitivity to Individual Bit Flips in Client-Side Operations of the CKKS Scheme

Homomorphic Encryption HE enables computation on encrypted data without decryption, making it a cornerstone of privacy-preserving computation in untrusted environments. As HE sees growing adoption in sensitive applications such as secure machine learning and confidential data analysis ensuring it...

SecONNds: Secure Outsourced Neural Network Inference on ImageNet

The widespread adoption of outsourced neural network inference presents significant privacy challenges, as sensitive user data is processed on untrusted remote servers. Secure inference offers a privacy-preserving solution, but existing frameworks suffer from high computational overhead and...

Understanding the Error Sensitivity of Privacy-Aware Computing

Homomorphic Encryption HE enables secure computation on encrypted data without decryption, allowing a great opportunity for privacy-preserving computation. In particular, domains such as healthcare, finance, and government, where data privacy and security are of utmost importance, can benefit fro...

GDNTT: an Area-Efficient Parallel NTT Accelerator Using Glitch-Driven Near-Memory Computing and Reconfigurable 10T SRAM

With the rapid advancement of quantum computing technology, post-quantum cryptography PQC has emerged as a pivotal direction for next-generation encryption standards. Among these, lattice-based cryptographic schemes rely heavily on the fast Number Theoretic Transform NTT over polynomial rings,...

A Unified Hardware Accelerator for Fast Fourier Transform and Number Theoretic Transform

The Number Theoretic Transform NTT is an indispensable tool for computing efficient polynomial multiplications in post-quantum lattice-based cryptography. It has strong resemblance with the Fast Fourier Transform FFT, which is the most widely used algorithm in digital signal processing. In this...

Enough Polynomials and Linear Algebra to Implement Kyber

I was once talking with a mathematician and trying to explain elliptic curve cryptography. Eventually, something clicked and they went "oh, that! I think there was a chapter about it in the book. You made a whole field out of it?" Yes, in cryptography we end up focusing on a very narrow slice of...