Machine Learning-based Vulnerability Study of Interpose PUFs as Security Primitives for IoT Networks
2021 IEEE International Conference on Networking, Architecture and Storage (NAS)(2021)
摘要
Security is of importance for communication networks, and many network nodes, like sensors and IoT devices, are resource-constrained. Physical Unclonable Functions (PUFs) leverage physical variations of the integrated circuits to produce responses unique to individual circuits and have the potential for delivering security for low-cost networks. But before a PUF can be adopted for security applica...
更多查看译文
关键词
Training,Neural networks,Machine learning,Network security,Physical unclonable function,Nonhomogeneous media,Reliability engineering
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要