| 基于Ni-SnO2纳米颗粒的GS-PUF设计 |
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| 引用本文： | 李乐薇 汪鹏君 张跃军.基于Ni-SnO2纳米颗粒的GS-PUF设计[J].宁波大学学报(理工版),2021,0(6):61-66. |
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| 作者姓名： | 李乐薇 汪鹏君 张跃军 |
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| 作者单位： | 1.宁波大学 信息科学与工程学院, 浙江 宁波 315211; 2.温州大学 电气与电子工程学院, 浙江 温州 325035 |
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| 摘 要： | 气敏传感器具有气体识别、探测和监测等功能, 广泛应用于工业生产等领域, 但在泄漏预警时缺乏迅速识别和定位等功能. 本文基于传感器制备工艺偏差分析, 通过对传感器气敏机制的研究, 提出一种基于Ni-SnO2纳米颗粒的气敏传感器物理不可克隆函数(Gas Sensor-Physical Unclonable Function, GS-PUF)设计方案. 该方案利用掺杂Ni元素的方法, 结合静电喷雾沉积技术制备Ni-SnO2气敏传感器, 以获取更加稳定可靠的物理特征值, 然后采集气敏传感器对不同浓度下气体的响应数据, 最后利用随机阻值多位平衡算法比较不同组气敏传感器响应电信号值, 实现PUF数据输出. 制备每组样本可产生128位二进制数据的多组PUF样本, 进行对比实验. 结果表明, 所设计的GS-PUF具有气体泄漏源头识别定位的功能, 且随机性提升至99%, 唯一性达49.80%.
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| 关 键 词： | Ni-SnO2纳米颗粒 物理不可克隆函数 气敏传感器 静电喷雾沉积 |
Gas sensor physical unclonable function based on Ni-SnO2 nanoparticles |
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| LI Lewei ,WANG Pengjun,ZHANG Yuejun.Gas sensor physical unclonable function based on Ni-SnO2 nanoparticles[J].Journal of Ningbo University(Natural Science and Engineering Edition),2021,0(6):61-66. |
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| Authors: | LI Lewei WANG Pengjun ZHANG Yuejun |
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| Affiliation: | 1.Factual of Electrical Engineering and Computer Science, Ningbo University, Ningbo 315211, China; 2.College of Electrical and Electronic Engineering, Wenzhou University, Wenzhou 325035, China |
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| Abstract: | Gas sensors are widely used in industry and other fields with the functions of identification, detection, and monitoring, but they lack the functions of rapid identification and positioning in the early warning of leakage. In this paper, a GS-PUF (Gas Sensor-Physical Unclonable Function) design scheme is proposed. The method of doping heavy Ni elements is adopted to prepare Ni-SnO2 gas sensor with electrostatic spray deposition technique to obtain more stable and reliable physical characteristics. Then the response data of gas sensors to different concentrations of gas are collected. Finally, the random resistance multi-bit balance algorithm is used to compare the response electrical signal values of different groups of gas sensors to achieve PUF data output. Multiple groups which can generate 128 bit binary data of PUF samples are implemented for comparison experiment. The results show that the designed GS-PUF has the function of identifying and locating the source of gas leakage, and the randomness is increased to 99%, and the uniqueness is 49.80%. |
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| Keywords: | Ni-SnO2 nanoparticles physical unclonable function gas sensor electrostatic spray deposition |
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