activity
20212025
most citedDeepStrike: Remotely-Guided Fault Injection Attacks on DNN Accelerator in Cloud-FPGA

43 citations · 53 across the 13 of their papers we have counts for

collaborators

13 papers

cs.CR2025

ShuffleV: A Microarchitectural Defense Strategy against Electromagnetic Side-Channel Attacks in Microprocessors

Nuntipat Narkthong, Yukui Luo, Xiaolin Xu

The run-time electromagnetic (EM) emanation of microprocessors presents a side-channel that leaks the confidentiality of the applications running on them. Many recent works have de…

cs.LG2024★ 1 cited

AdaPI: Facilitating DNN Model Adaptivity for Efficient Private Inference in Edge Computing

Tong Zhou, Jiahui Zhao, Yukui Luo +4

Private inference (PI) has emerged as a promising solution to execute computations on encrypted data, safeguarding user privacy and model parameters in edge computing. However, exi…

cs.CR2024

SSNet: A Lightweight Multi-Party Computation Scheme for Practical Privacy-Preserving Machine Learning Service in the Cloud

Shijin Duan, Chenghong Wang, Hongwu Peng +4

As privacy-preserving becomes a pivotal aspect of deep learning (DL) development, multi-party computation (MPC) has gained prominence for its efficiency and strong security. Howeve…

cs.CR2024

TBNet: A Neural Architectural Defense Framework Facilitating DNN Model Protection in Trusted Execution Environments

Ziyu Liu, Tong Zhou, Yukui Luo +1

Trusted Execution Environments (TEEs) have become a promising solution to secure DNN models on edge devices. However, the existing solutions either provide inadequate protection or…

cs.CR2024

SPECIAL: Synopsis Assisted Secure Collaborative Analytics

Chenghong Wang, Lina Qiu, Johes Bater +1

Secure collaborative analytics (SCA) enable the processing of analytical SQL queries across multiple owners' data, even when direct data sharing is not feasible. Although essential…

cs.CR2023★ 1 cited

MirrorNet: A TEE-Friendly Framework for Secure On-device DNN Inference

Ziyu Liu, Yukui Luo, Shijin Duan +2

Deep neural network (DNN) models have become prevalent in edge devices for real-time inference. However, they are vulnerable to model extraction attacks and require protection. Exi…

cs.CR2023★ 1 cited

AutoReP: Automatic ReLU Replacement for Fast Private Network Inference

Hongwu Peng, Shaoyi Huang, Tong Zhou +11

The growth of the Machine-Learning-As-A-Service (MLaaS) market has highlighted clients' data privacy and security issues. Private inference (PI) techniques using cryptographic prim…

cs.CR2023

PASNet: Polynomial Architecture Search Framework for Two-party Computation-based Secure Neural Network Deployment

Hongwu Peng, Shanglin Zhou, Yukui Luo +9

Two-party computation (2PC) is promising to enable privacy-preserving deep learning (DL). However, the 2PC-based privacy-preserving DL implementation comes with high comparison pro…

cs.LG2023★ 1 cited

NNSplitter: An Active Defense Solution for DNN Model via Automated Weight Obfuscation

Tong Zhou, Yukui Luo, Shaolei Ren +1

As a type of valuable intellectual property (IP), deep neural network (DNN) models have been protected by techniques like watermarking. However, such passive model protection canno…

cs.CR2023★ 5 cited

RRNet: Towards ReLU-Reduced Neural Network for Two-party Computation Based Private Inference

Hongwu Peng, Shanglin Zhou, Yukui Luo +11

The proliferation of deep learning (DL) has led to the emergence of privacy and security concerns. To address these issues, secure Two-party computation (2PC) has been proposed as…

cs.CR2022★ 1 cited

PolyMPCNet: Towards ReLU-free Neural Architecture Search in Two-party Computation Based Private Inference

Hongwu Peng, Shanglin Zhou, Yukui Luo +10

The rapid growth and deployment of deep learning (DL) has witnessed emerging privacy and security concerns. To mitigate these issues, secure multi-party computation (MPC) has been…

cs.CR2022

NNReArch: A Tensor Program Scheduling Framework Against Neural Network Architecture Reverse Engineering

Yukui Luo, Shijin Duan, Cheng Gongye +2

Architecture reverse engineering has become an emerging attack against deep neural network (DNN) implementations. Several prior works have utilized side-channel leakage to recover…

cs.CR2021★ 43 cited

DeepStrike: Remotely-Guided Fault Injection Attacks on DNN Accelerator in Cloud-FPGA

Yukui Luo, Cheng Gongye, Yunsi Fei +1

As Field-programmable gate arrays (FPGAs) are widely adopted in clouds to accelerate Deep Neural Networks (DNN), such virtualization environments have posed many new security issue…