Electrical Engineering Department, Information Technology University, Lahore 54000, Pakistan.
Department of Electronics and Nano Engineering, University of Glasgow, Glasgow G12 8QQ, UK.
Sensors (Basel). 2021 May 19;21(10):3534. doi: 10.3390/s21103534.
This manuscript presents a novel mechanism (at the physical layer) for authentication and transmitter identification in a body-centric nanoscale communication system operating in the terahertz (THz) band. The unique characteristics of the propagation medium in the THz band renders the existing techniques (say for impersonation detection in cellular networks) not applicable. In this work, we considered a body-centric network with multiple on-body nano-senor nodes (of which some nano-sensors have been compromised) who communicate their sensed data to a nearby gateway node. We proposed to protect the transmissions on the link between the legitimate nano-sensor nodes and the gateway by exploiting the path loss of the THz propagation medium as the fingerprint/feature of the sender node to carry out authentication at the gateway. Specifically, we proposed a two-step hypothesis testing mechanism at the gateway to counter the impersonation (false data injection) attacks by malicious nano-sensors. To this end, we computed the path loss of the THz link under consideration using the high-resolution transmission molecular absorption (HITRAN) database. Furthermore, to refine the outcome of the two-step hypothesis testing device, we modeled the impersonation attack detection problem as a hidden Markov model (HMM), which was then solved by the classical Viterbi algorithm. As a bye-product of the authentication problem, we performed transmitter identification (when the two-step hypothesis testing device decides no impersonation) using (i) the maximum likelihood (ML) method and (ii) the Gaussian mixture model (GMM), whose parameters are learned via the expectation-maximization algorithm. Our simulation results showed that the two error probabilities (missed detection and false alarm) were decreasing functions of the signal-to-noise ratio (SNR). Specifically, at an SNR of 10 dB with a pre-specified false alarm rate of 0.2, the probability of correct detection was almost one. We further noticed that the HMM method outperformed the two-step hypothesis testing method at low SNRs (e.g., a 10% increase in accuracy was recorded at SNR = -5 dB), as expected. Finally, it was observed that the GMM method was useful when the ground truths (the true path loss values for all the legitimate THz links) were noisy.
这篇手稿提出了一种新的机制（在物理层），用于在工作在太赫兹（THz）频段的体域网纳米通信系统中进行认证和发送方识别。THz 波段传播介质的独特特性使得现有的技术（例如在蜂窝网络中进行仿冒检测）不适用。在这项工作中，我们考虑了一个具有多个体上纳米传感器节点的体域网（其中一些纳米传感器已被攻破），这些节点将其感测到的数据传输到附近的网关节点。我们建议利用 THz 传播介质的路径损耗作为发送方节点的指纹/特征，通过在合法纳米传感器节点和网关之间的链路中进行保护传输，来实现网关的认证。具体来说，我们在网关中提出了一种两步假设检验机制，以抵御恶意纳米传感器的仿冒（虚假数据注入）攻击。为此，我们使用高分辨率传输分子吸收（HITRAN）数据库计算了所考虑的 THz 链路的路径损耗。此外，为了细化两步假设检验设备的结果，我们将仿冒攻击检测问题建模为隐马尔可夫模型（HMM），然后通过经典的维特比算法对其进行求解。作为认证问题的副产品，我们使用（i）最大似然（ML）方法和（ii）高斯混合模型（GMM）进行发送方识别（当两步假设检验设备决定不存在仿冒时），其参数通过期望最大化算法学习。我们的仿真结果表明，两个错误概率（漏检和虚警）是信噪比（SNR）的递减函数。具体来说，在指定的虚警率为 0.2 且 SNR 为 10dB 的情况下，正确检测的概率几乎为 1。我们还注意到，与两步假设检验方法相比，HMM 方法在低 SNR 下表现更好（例如，在 SNR = -5dB 时记录到准确率提高了 10%），这是意料之中的。最后，当地面真相（所有合法 THz 链路的真实路径损耗值）存在噪声时，GMM 方法很有用。
