A machine-learning-based hardware-Trojan detection approach for chips in the Internet of Things
With the development of the Internet of Things, smart devices are widely used. Hardware security is one key issue in the security of the Internet of Things. As the core component of the hardware, the integrated circuit must be taken seriously with its security. The pre-silicon detection methods do n...
Saved in:
Main Authors: | Chen Dong, Jinghui Chen, Wenzhong Guo, Jian Zou |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2019-12-01
|
Series: | International Journal of Distributed Sensor Networks |
Online Access: | https://doi.org/10.1177/1550147719888098 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Hybrid multi‐level hardware Trojan detection platform for gate‐level netlists based on XGBoost
by: Ying Zhang, et al.
Published: (2022-03-01) -
Blinding HT: Hiding Hardware Trojan signals traced across multiple sequential levels
by: Ying Zhang, et al.
Published: (2022-01-01) -
A Smart Machine Learning Model for the Detection of Brain Hemorrhage Diagnosis Based Internet of Things in Smart Cities
by: Hang Chen, et al.
Published: (2020-01-01) -
Internet of things-driven approach integrated with explainable machine learning models for ship fuel consumption prediction
by: Van Nhanh Nguyen, et al.
Published: (2025-04-01) -
Machine learning–based automated image processing for quality management in industrial Internet of Things
by: Nematullo Rahmatov, et al.
Published: (2019-10-01)