水声信道在假冒攻击下的有效容量研究
On the Effective Capacity of an Underwater Acoustic Channel under Impersonation Attack
摘要：
研究了认证对水声信道有效容量的影响。具体而言，UWA信道受到存在于合法节点对（Alice和Bob）附近的恶意节点（Eve）的冒充攻击; Eve试图通过使Bob相信她确实是Alice来将其恶意数据注入系统。为了阻止Eve的冒充攻击，Bob利用发送节点的距离作为特征/指纹，在物理层执行基于特征的认证。由于在Bob处的认证，由于在发送节点（Alice或Eve）处缺乏信道知识，并且由于基于阈值的解码误差模型，所考虑的系统的相关动态可以由马尔可夫链（MC）建模。因此，我们计算状态转移概率的MC，和时刻生成函数的服务过程对应于每个状态。这使我们能够得到一个封闭形式的表达EC的认证参数。此外，我们计算的最佳传输速率（在爱丽丝）通过梯度下降（GD）技术和人工神经网络（ANN）的方法。仿真结果表明，在严格的认证约束（即，更多的假警报和更多的传输由夏娃）。仿真结果还表明，（最佳传输速率）性能的人工神经网络技术是相当接近的GD方法。
英文摘要：
This paper investigates the impact of authentication on effective capacity (EC) of an underwater acoustic (UWA) channel. Specifically, the UWA channel is under impersonation attack by a malicious node (Eve) present in the close vicinity of the legitimate node pair (Alice and Bob); Eve tries to inject its malicious data into the system by making Bob believe that she is indeed Alice. To thwart the impersonation attack by Eve, Bob utilizes the distance of the transmit node as the feature/fingerprint to carry out feature-based authentication at the physical layer. Due to authentication at Bob, due to lack of channel knowledge at the transmit node (Alice or Eve), and due to the threshold-based decoding error model, the relevant dynamics of the considered system could be modelled by a Markov chain (MC). Thus, we compute the state-transition probabilities of the MC, and the moment generating function for the service process corresponding to each state. This enables us to derive a closed-form expression of the EC in terms of authentication parameters. Furthermore, we compute the optimal transmission rate (at Alice) through gradient-descent (GD) technique and artificial neural network (ANN) method. Simulation results show that the EC decreases under severe authentication constraints (i.e., more false alarms and more transmissions by Eve). Simulation results also reveal that the (optimal transmission rate) performance of the ANN technique is quite close to that of the GD method.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
