Cognitive radio networks (CRNs) are vulnerable to spoofing attacks due to their wireless and cognitive nature. Since the traditional cryptographic authentication can hardly prevent such attacks in CRNs, the physical-layer authentication has been investigated for recent years. To achieve a light-weight physical-layer authentication, a rollout partially observable Markov decision process-based algorithm, named RoPOMDP, is proposed in this study. In general, RoPOMDP formulates the physical-layer authentication as a zero-sum game, based on which a hypothesis test upon channel vectors is developed. That allows us to design the gains for both spoofers and receivers based on Bayesian risks for the game, in which the spoofing attack probability is predicted by a non-linear function approximation utilising v-support vector regression. Then, a RoPOMDP is employed to estimate the optimal threshold for the test statistic such that spoofing attacks can be detected. The theoretical analysis and simulations indicate that: (i) RoPOMDP improves the spoofing detection accuracy; (ii) as a light-weight algorithm, the complexity of RoPOMDP is lower than contemporary ones.

中文翻译：

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认知无线电网络中轻量级物理层身份验证的推出算法

认知无线电网络（CRN）由于其无线和认知特性而容易受到欺骗攻击。由于传统的密码认证几乎无法阻止CRN中的此类攻击，因此近年来对物理层认证进行了研究。为了实现轻量级的物理层身份验证，本研究提出了一种基于部分可观察的基于马尔可夫决策过程的推出算法，称为RoPOMDP。通常，RoPOMDP将物理层身份验证表述为零和博弈，在此基础上开发了基于信道向量的假设检验。这使我们能够基于游戏的贝叶斯风险来设计欺骗者和接收者的收益，其中通过利用v支持向量回归的非线性函数逼近来预测欺骗攻击的概率。然后，使用RoPOMDP来估计测试统计信息的最佳阈值，以便可以检测到欺骗攻击。理论分析和仿真表明：（i）RoPOMDP提高了欺骗检测的准确性；（ii）作为一种轻量级算法，RoPOMDP的复杂度低于现代算法。