Hardware Trojans Detection Through RTL Features Extraction and Machine Learning-Reference-Cited by-同舟云学术

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Hardware Trojans Detection Through RTL Features Extraction and Machine Learning

Published:2021-12-16 Issue: Volume: Page:
ISSN:
Container-title:2021 Asian Hardware Oriented Security and Trust Symposium (AsianHOST)
language:
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Author:

Yang Jizhong¹,Zhang Ying¹,Hua Yifeng¹,Yao Jiaqi¹,Mao Zhiming¹,Chen Xin¹

Affiliation:

1. College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9698822/9699480/09699658.pdf?arnumber=9699658

Reference15 articles.

1. Proof-Carrying Hardware Intellectual Property: A Pathway to Trusted Module Acquisition

2. Efficient Control-Flow Subgraph Matching for Detecting Hardware Trojans in RTL Models

3. Detecting RTL Trojans using Artificial Immune Systems and High Level Behavior Classification

4. Blinding HT: Hiding Hardware Trojan Signals Traced Across Multiple Sequential Levels;zhang;IET Circuits Devices & Systems,2021

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Criticality Analysis of Ring Oscillators in FPGA Bitstreams ^*;2023 IEEE European Test Symposium (ETS);2023-05-22

2. Protecting Trojan Secured DSP cores against IP piracy using Facial Biometrics;2022 IEEE 19th India Council International Conference (INDICON);2022-11-24

3. Hardware Trojan Detection at LUT: Where Structural Features Meet Behavioral Characteristics;2022 IEEE International Symposium on Hardware Oriented Security and Trust (HOST);2022-06-27

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