摘要
通过分析无线设备的通信信号来提取设备的射频指纹进行设备识别是一种保护通信系统安全的物理层方法.射频指纹是无线通信设备的物理层本质特征,很难被篡改.就像不同的人有不同的指纹,不同的无线设备也拥有不同的射频指纹,可用于无线设备的身份识别和接入认证.本文主要回顾了过去二十年国内外射频指纹技术的研究进展.根据射频指纹提取与识别的典型流程,首先分析了射频指纹的产生机理及众多可识别的设备类型,反应出射频指纹拥有广阔的应用前景.然后,本文将可识别信号主要分成了瞬态信号和稳态信号两类,并简述了检测和截取可识别信号的方法.随后,本文对射频指纹特征做了简单分类,归纳分析了射频指纹应该具备的五大特点,即通用性、唯一性、短时不变性、独立性以及稳健性.本文还从瞬态信号射频指纹技术和稳态信号射频指纹技术两个方面总结了该领域的研究现状.此外,本文对于如何评估射频指纹系统的性能也做了一定的论述.最后,本文指出了该领域进一步的研究方向和可能面临的技术难题.
Wireless device identification via radio frequency (RF) fingerprinting extracted from communication signals is a physical layer approach for communication system security. In physical layer, RF fingerprinting is an inherent characteristic of wireless communication devices themselves, which can hardly be tampered. Just as people have unique fingerprints, different wireless devices exhibit different RF fingerprints which can be used for identification and authentication. This paper mainly provides a review of the research and development in RF fingerprinting extraction and identification in the past twenty years. According to the procedure of RF fingerprinting extraction and identification, we first analyze the generation mechanism of RF fingerprinting and the corresponding identification devices, which reflect the broad applications of the RF fingerprinting. Then, the identification signals are divided into transient signal and steady-state signal, and a method to detect and extract such signals are described. This paper further classifies the RF fingerprinting and summaries their five features, i.e., universality, uniqueness, short-time invariance, independence and robustness. This paper also summarizes the state of art on the procedure of transient and steady-state based techniques. It also describes how to evaluate the performance of RF fingerprinting identification systems. Finally, some potential research directions and challenges in this area are pointed out.
出处
《密码学报》
CSCD
2016年第5期-,共14页
Journal of Cryptologic Research
基金
国家重点基础研究发展项目(973计划)(2013CB338003)
国家自然科学基金项目(61571110)
江苏省六大人才高峰项目
航天CALT基金项目
关键词
射频指纹
设备识别
物理层安全
特征提取
Radio frequency (RF) fingerprinting
device identification
physical layer security
feature extraction
