汪鹏君^{1, 2,,},
李乐薇²,
郑雁公²,
李刚¹
1.温州大学电气与电子工程学院 温州 325035
2.宁波大学信息科学与工程学院 宁波 315211
基金项目:国家自然科学基金(61874078, 61871244)，国家重点研发计划(2018YFB2202100)，宁波市公益性计划(202002N3134)，宁波大学大学生科技创新项目(2021SRIP1327)

详细信息

作者简介:汪鹏君：男，1966年生，教授，研究方向为集成电路设计、信息安全等技术及其相关理论
李乐薇：女，1997年生，硕士生，研究方向为集成电路设计、信息安全等技术及其相关理论
郑雁公：男，1983年生，副教授，研究方向为气敏材料以及沸石相关理论
李刚：男，1988年生，讲师，研究方向为集成电路设计、信息安全等技术及其相关理论

通讯作者:汪鹏君　wangpengjun@wzu.edu.cn

中图分类号:TN919; TP212

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被引次数:0

出版历程

收稿日期:2020-12-31
修回日期:2021-04-12
网络出版日期:2021-04-21
刊出日期:2021-06-18

High Steady-state Physical Unclonable Function Generator Based on Gas Sensors

Pengjun WANG^{1, 2,,},
Lewei LI²,
Yangong ZHENG²,
Gang LI¹
1. College of Electrical and Electronic Engineering, Wenzhou University, Wenzhou 325035, China
2. Faculty of Electrical Engineering and Computer Science, Ningbo University, Ningbo 315211, China
Funds:The National Natural Science Foundation of China(61874078, 61871244), The National Key Research and Development Program of China(2018YFB2202100), The Ningbo Public Welfare Projects(202002N3134), The Science and Technology Innovation Project of Ningbo University(2021SRIP1327)


摘要
摘要:物联网(IoT)作为战略性新兴产业已经上升为国家发展重点，但在实际应用中也面临各种安全威胁。确保资源受限物联网系统数据传输、处理和存储的安全已成为研究热点。该文通过对物理不可克隆函数(PUF)和传感器制备工艺偏差的研究，提出一种基于气敏传感器的高稳态物理不可克隆函数发生器设计方案。该方案首先采用静电喷雾沉积(ESD)方式生成具有高比表面积特性的纳米材料，结合高温煅烧技术制备Pd-SnO₂气敏传感器；其次采集Pd-SnO₂气敏传感器在不同气体浓度、环境温度、加热电压条件下对甲醛气体的响应数据；然后利用随机阻值多位平衡算法比较不同簇气敏传感器响应的阻值，进而产生多位高稳态PUF数据；最后对所设计PUF发生器的安全性和可靠性进行评估。实验结果表明，该PUF发生器的随机性为97.03%、可靠性为97.85%、唯一性为49.04%，可广泛应用于物联网安全领域。
关键词:物理不可克隆函数/
气敏传感器/
物理不可克隆函数发生器/
物联网安全
Abstract:As a strategic emerging industry, the Internet of Things (IoT) has become a national development focus, but it also faces various security threats in practical applications. Ensuring the security of data transmission, processing and storage of resource-constrained IoT systems has become a research hotspot. In this paper, a high steady-state Physical Unclonable Function(PUF) generator scheme is proposed by studying PUF and the deviation of the sensor preparation process. Firstly, the Electrostatic Spray Deposition (ESD) is used to generate nanofibers with high specific surface area characteristics and high-temperature calcination technology is combined to prepare Pd-SnO₂ gas sensors. Secondly, the response data of gas sensors to formaldehyde gas is collected under different gas concentration, ambient temperature and heating voltage conditions. Then, a random resistance multi-bit balance algorithm is used to compare the response data of different clusters of gas sensors and then multiple high steady-state PUF data is generated. Finally, the safety and reliability of the designed PUF generator are evaluated. Experimental results show that the randomness of the PUF generator is 97.03%, the reliability is 97.85%, and the uniqueness is 49.04%, which can be widely used in IoT security field.
Key words:Physical Unclonable Function(PUF)/
Gas sensor/
Sensor PUF/
Internet of Things(IoT) security



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