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20172023
most citedGME: GPU-based Microarchitectural Extensions to Accelerate Homomorphic Encryption

45 citations · 82 across the 9 of their papers we have counts for

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8 papers · 1 filter

cs.CR2023★ 45 cited

GME: GPU-based Microarchitectural Extensions to Accelerate Homomorphic Encryption

Kaustubh Shivdikar, Yuhui Bao, Rashmi Agrawal +9

Fully Homomorphic Encryption (FHE) enables the processing of encrypted data without decrypting it. FHE has garnered significant attention over the past decade as it supports secure…

cs.CR2023★ 1 cited

RISE: RISC-V SoC for En/decryption Acceleration on the Edge for Homomorphic Encryption

Zahra Azad, Guowei Yang, Rashmi Agrawal +3

Today edge devices commonly connect to the cloud to use its storage and compute capabilities. This leads to security and privacy concerns about user data. Homomorphic Encryption (H…

cs.CR2022★ 2 cited

Accelerating Polynomial Multiplication for Homomorphic Encryption on GPUs

Kaustubh Shivdikar, Gilbert Jonatan, Evelio Mora +6

Homomorphic Encryption (HE) enables users to securely outsource both the storage and computation of sensitive data to untrusted servers. Not only does HE offer an attractive soluti…

cs.CR2022★ 8 cited

FAB: An FPGA-based Accelerator for Bootstrappable Fully Homomorphic Encryption

Rashmi Agrawal, Leo de Castro, Guowei Yang +5

FHE offers protection to private data on third-party cloud servers by allowing computations on the data in encrypted form. However, to support general-purpose encrypted computation…

cs.CR2021★ 25 cited

Does Fully Homomorphic Encryption Need Compute Acceleration?

Leo de Castro, Rashmi Agrawal, Rabia Yazicigil +4

Fully Homomorphic Encryption (FHE) allows arbitrarily complex computations on encrypted data without ever needing to decrypt it, thus enabling us to maintain data privacy on third-…

cs.CR2021

Efficient FPGA-based ECDSA Verification Engine for Permissioned Blockchains

Rashmi Agrawal, Ji Yang, Haris Javaid

As enterprises embrace blockchain technology, many real-world applications have been developed and deployed using permissioned blockchain platforms (access to network is controlled…

cs.CR2020

Fast Arithmetic Hardware Library For RLWE-Based Homomorphic Encryption

Rashmi Agrawal, Lake Bu, Alan Ehret +1

In this work, we propose an open-source, first-of-its-kind, arithmetic hardware library with a focus on accelerating the arithmetic operations involved in Ring Learning with Error…

cs.CR2019★ 1 cited

A Lightweight McEliece Cryptosystem Co-processor Design

Lake Bu, Rashmi Agrawal, Hai Cheng +1

Due to the rapid advances in the development of quantum computers and their susceptibility to errors, there is a renewed interest in error correction algorithms. In particular, err…