本篇論文所探討的議題為感知無線電(cognitive radio, CR)如何在高速移動、受到多路徑干擾影響的惡意環境中辨識出攻擊者的存在。隨著感知無線電的迅速法展，衍生出許多值得我們探討的安全問題，其中模仿主要使用者攻擊(primary user emulation attacks, PUEA)較廣受討論，而本篇提出利用接收訊號的相關特性對模仿主要使用者攻擊做辨識。
在高速移動的無線通訊中，接收端收到不同移動速度之訊號傳送者的訊號，其接收訊號的相關特性具獨特性，我們利用此特性來做使用者之辨識。首先利用最大概似估測(maximum likelihood estimation, MLE)估測出接收訊號之相關值向量，並算出其平均值(mean)及共變異數矩陣(covariance)，再使用概似比試驗(likelihood ratio test, LRT)和對數概似比試驗(log likelihood ratio test, LLRT)設計偵測器，進行模仿主要使用者攻擊之辨識。本篇論文所提出之演算法相較於「以通道階能量為基礎偵測模仿主要使用者攻擊」[1]有較良好的偵測效能，且不受多路徑的影響，並能在高速環境下做偵測。在最後小節裡，我們亦使用模擬之方式，結合本實驗室提出的頻譜偵測演算法[2]及本篇的使用者辨識演算法，觀察和討論其整體效能。

The topic of this paper is to identify the attacker’s presence in cognitive radio (CR) in high speed mobile environments which affected by multipath interference. With the rapid development of cognitive radio, several security issues have raised. Among these issues, the primary user emulation attack (PUEA) is widely discussed. In this work, we propose a method by using the correlation characteristics of received signal to identify the PUEA.
In high speed mobile wireless communication, the correlation characteristics of received signal that received from different speed of transmitters are unique. We use this feature to identify the PUEA. First, the maximum likelihood estimation (MLE) is used to estimate the correlation vector of the received signal and calculate its mean and covariance matrix. Then we use likelihood ratio test (LRT) and log likelihood ratio test (LLRT) to design a detector that used to identify the PUEA. The algorithm proposed in this paper has a better detection performance than the algorithm based on channel tap power and its detection performance isn’t affected by multipath.

[1] 曾俊霖(2011)。在感知無線電中以通道特徵為基礎偵測模仿主要使用者攻擊。國立成功大學工程科學系碩士論文。
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