伪RFID标签信号的谱熵特征提取与选择

Spectral entropy feature extraction and selection of pseudo RFID tag signals

为解决RFID通信安全问题,本文提出一种新的物理层标签防伪技术,该技术对原始信号进行信号分离得到期望、噪音和标准化信号,然后对3种信号的谱熵特征进行特征提取,最后利用特征选择实现真伪标签分类。另外,本文还提出了一种新的交叉验证来客观测试物理层方法的性能。结果表明,本文方法准确率比传统方法提升近4%,在新交叉验证下,物理层方法的分类准确率会下降8%~10%,由此本文得到重要结论,在物理层识别方法中利用谱熵特征实现标签防伪有着重要意义。

In order to solve the problem of RFID communication security,this paper proposes a new physical layer tag anti-counterfeiting technology.This technology separates the original signal to obtain the expected,noise and normalized signals,and extracts the spectral entropy features of the three signals.Finally,feature selection is used to achieve true and false label classification.In addition,this paper proposes a new cross-validation to objectively test the performance of the physical layer method.The results show that the accuracy of the method in this paper is nearly 4%higher than that of the traditional method.Under the new cross-validation,the classification accuracy of the physical layer method will drop by 8~10 percentage points.From this,we get an important conclusion,it is of great significance to use the spectral entropy feature in the physical layer identification method to realize the label anti-counterfeiting.