Cheng Gongye

Orcid: 0000-0002-6423-0871

According to our database1, Cheng Gongye authored at least 14 papers between 2019 and 2023.

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Bibliography

2023
An Energy-Efficient Neural Network Accelerator with Improved Protections Against Fault-Attacks.
Proceedings of the 49th IEEE European Solid State Circuits Conference, 2023

HammerDodger: A Lightweight Defense Framework against RowHammer Attack on DNNs.
Proceedings of the 60th ACM/IEEE Design Automation Conference, 2023

EMShepherd: Detecting Adversarial Samples via Side-channel Leakage.
Proceedings of the 2023 ACM Asia Conference on Computer and Communications Security, 2023

2022
Ran$Net: An Anti-Ransomware Methodology based on Cache Monitoring and Deep Learning.
Proceedings of the GLSVLSI '22: Great Lakes Symposium on VLSI 2022, Irvine CA USA, June 6, 2022

Protected ECC Still Leaks: A Novel Differential-Bit Side-channel Power Attack on ECDH and Countermeasures.
Proceedings of the GLSVLSI '22: Great Lakes Symposium on VLSI 2022, Irvine CA USA, June 6, 2022

NNReArch: A Tensor Program Scheduling Framework Against Neural Network Architecture Reverse Engineering.
Proceedings of the 30th IEEE Annual International Symposium on Field-Programmable Custom Computing Machines, 2022

A Cross-Platform Cache Timing Attack Framework via Deep Learning.
Proceedings of the 2022 Design, Automation & Test in Europe Conference & Exhibition, 2022

2021
DeepStrike: Remotely-Guided Fault Injection Attacks on DNN Accelerator in Cloud-FPGA.
Proceedings of the 58th ACM/IEEE Design Automation Conference, 2021

2020
Correlation Power Analysis and Higher-order Masking Implementation of WAGE.
IACR Cryptol. ePrint Arch., 2020

Stealthy-Shutdown: Practical Remote Power Attacks in Multi - Tenant FPGAs.
Proceedings of the 38th IEEE International Conference on Computer Design, 2020

New Passive and Active Attacks on Deep Neural Networks in Medical Applications.
Proceedings of the IEEE/ACM International Conference On Computer Aided Design, 2020

Reverse-Engineering Deep Neural Networks Using Floating-Point Timing Side-Channels.
Proceedings of the 57th ACM/IEEE Design Automation Conference, 2020

2019
Evaluating Fault Resiliency of Compressed Deep Neural Networks.
Proceedings of the 15th IEEE International Conference on Embedded Software and Systems, 2019

Fault Sneaking Attack: a Stealthy Framework for Misleading Deep Neural Networks.
Proceedings of the 56th Annual Design Automation Conference 2019, 2019


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