隨著無線通訊技術日漸更新，頻譜資源的需求不斷地增加，感知無線電(cognitive radio, CR)技術被提出來提高頻譜資源的使用率，但隨著此技術的發展，相關的安全問題也隨之產生。其中最多人所研究的安全議題為模仿主要使用者攻擊(primary user emulation attacks, PUEA)。
文獻中已提出幾種方法辨識模仿主要使用者攻擊，我們提出使用通道階功率(channel-tap power)這種無線通道的特性來辨識。在無線環境下，不同傳送端與接收端之間的通道統計特性是獨一無二的，因此根據感知無線電的頻譜感知能力，利用無線通道獨特的統計特性在實體層直接辨識主要使用者和模仿主要使用者攻擊，進而提高偵測效率。
本篇研究根據2011年本實驗室曾俊霖學長所提出的論文「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」，以通道階功率的計算與偵測模仿主要使用者攻擊方法，在真實無線環境的實現與效能評估。據此，我們將電路與OFDM模組進行整合，並使用萊斯大學所開發的無線開放式研究平臺(Wireless Open-Access Research Platform, WARP)實現本研究之硬體架構，並在不同的環境假設下進行通道階功率的量測與效能評估。

With the rapid development of cognitive radio (CR), several security issues have drawn a lot of attentions. Among them, the detection of primary user emulation attacks (PUEA) is the most critical one. In this work, we proposed a method by using the characteristics of wireless channels, i.e., channel-tap power, to identify the PUEA. In order to verify the performance of our design, we implemented the proposed algorithm by the register-transfer-level (RTL) model, and verified it by the OFDM system on Wireless Open-Access Research Platform in real radio environments. We evaluate the effects of the distance, angle, and the line of sight propagation between the transceiver and receiver on the proposed channel-tap power signature. Also, the influences of SNR and the number of symbols on the detection probability are analyzed.

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