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20242026
most citedComet: Accelerating Private Inference for Large Language Model by Predicting Activation Sparsity

4 citations · 5 across the 8 of their papers we have counts for

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5 papers · 1 filter

cs.AR2024

Trinity: A General Purpose FHE Accelerator

Xianglong Deng, Shengyu Fan, Zhicheng Hu +9

In this paper, we present the first multi-modal FHE accelerator based on a unified architecture, which efficiently supports CKKS, TFHE, and their conversion scheme within a single…

cs.CR2024

Chameleon: An Efficient FHE Scheme Switching Acceleration on GPUs

Zhiwei Wang, Haoqi He, Lutan Zhao +4

Fully homomorphic encryption (FHE) enables direct computation on encrypted data, making it a crucial technology for privacy protection. However, FHE suffers from significant perfor…

cs.CR2024

The Early Bird Catches the Leak: Unveiling Timing Side Channels in LLM Serving Systems

Linke Song, Zixuan Pang, Wenhao Wang +7

The wide deployment of Large Language Models (LLMs) has given rise to strong demands for optimizing their inference performance. Today's techniques serving this purpose primarily f…

cs.CR2024

Taiyi: A high-performance CKKS accelerator for Practical Fully Homomorphic Encryption

Shengyu Fan, Xianglong Deng, Zhuoyu Tian +5

Fully Homomorphic Encryption (FHE), a novel cryptographic theory enabling computation directly on ciphertext data, offers significant security benefits but is hampered by substanti…

cs.CR2024★ 1 cited

The Road to Trust: Building Enclaves within Confidential VMs

Wenhao Wang, Linke Song, Benshan Mei +6

Integrity is critical for maintaining system security, as it ensures that only genuine software is loaded onto a machine. Although confidential virtual machines (CVMs) function wit…