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Nowadays, there is a growing demand for information security and security rules all across the world. Intrusion detection (ID) is a critical technique for detecting dangers in a network during data transmission. Artificial Intelligence (AI) methods support the Internet of Things (IoT) and smart cities by creating gadgets replicating intelligent behavior and enabling decision making with little or no human intervention. This research proposes novel technique for secure data transmission and detecting an intruder in a biometric authentication system by feature extraction with classification. Here, an intruder is detected by collecting the biometric database of the smart building based on the IoT. These biometric data are processed for noise removal, smoothening, and normalization. The processed data features are extracted using the kernel-based principal component analysis (KPCA). Then, the processed features are classified using the convolutional VGG−16 Net architecture. Then, the entire network is secured using a deterministic trust transfer protocol (DTTP). The suggested technique’s performance was calculated utilizing several measures, such as the accuracy, f-score, precision, recall, and RMSE. The simulation results revealed that the proposed method provides better intrusion detection outcomes.

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In this correspondence, we consider the performance of Multi-Input Multi-Output (MIMO) assisted multi-carrier (MC) modulated system for the transmission of the acoustic signal in underwater communications. In underwater communications, acoustic interference and ambient noise are the two major channel impairments. In our work, we consider turbo code as channel encoder and at the receiver, we employ iterative decoding algorithm to alleviate the effects of ambient noise and acoustic interference. We implement IFFT block at the transmitter and FFT block at the receiver to realize multi-carrier modulation. Particularly, we investigate the effects of eleven tap delay pertaining to shallow water model in the context of coded MIMO-OFDM system. At the receiver, we realize non-linear detector based on zero-forcing (ZF) algorithm. It is shown through simulation results that MIMO-OFDM system with ZF algorithm provides achievable bit error rate with less signal-to noise ratio using iterative decoding algorithm ..