物理不可克隆功能
计算机科学
认证(法律)
身份验证协议
嵌入式系统
无线传感器网络
协议(科学)
现场可编程门阵列
计算机网络
轻量级可扩展身份验证协议
密码学
计算机安全
医学
替代医学
病理
作者
Sourav Roy,Dipnarayan Das,Bibhash Sen
出处
期刊:ACM Journal on Emerging Technologies in Computing Systems
[Association for Computing Machinery]
日期:2023-09-18
卷期号:20 (1): 1-17
被引量:3
摘要
The wireless sensor network (WSN) has been gaining popularity for automation and performance improvement in different IoT-based applications. The resource-constrained nature and operating environment of IoT make the devices highly vulnerable to different attacks. However, the Physically Unclonable Function (PUF) helps to implement secure and lightweight authentication protocols for IoT. In this context, few computation-intensive authentication protocols are found in the literature that have addressed secure IoT communication in WSN. Besides, these protocols depend on the local storage of PUF-CRP, which is susceptible to security attacks. This work proposes a lightweight and secure authentication protocol for the IoT devices in WSN. A PUF and its machine learning (ML)–based soft model is integrated to ensure secure authentication and lightweight computation in WSN. PUF prevents physical attacks while carrying much less hardware fingerprints, and the ML-based PUF provides the desired resiliency against PUF identity-based attacks by eliminating the requirement of CRP-based storage. The proposed mechanism delivers two-way authentication while nullifying the attacks on IoT. The proposed protocol is implemented on Xilinx Artix-7 FPGA and Raspberry Pi for testability and performance evaluation. Experiment results and analysis signify its low-cost computations and lightweight features desired for IoT.
科研通智能强力驱动
Strongly Powered by AbleSci AI