Contemporary Secure Mechanism Using Deep Belief Network (DBN) For Smart Environment in Wireless Sensor Networks

Abstract

In contemporary industry 5.0 demonstrates the impact of Robots and IOTs with sensor networks. It emphasis the humanoid machines, optimal balance in all aspects of Industry products and smartness of progress. IOTs are playing vital role for all kind industries, educational sectors, public domains and smart cities environments. Even though high usages of sensor devices in wireless mode or wired mode, security is the most crucial task for maneuvering the signals. In traditional systems are incorporating with securing algorithms for data or signal transmission. But those mechanisms are leading some less accuracy for high end process in wireless sensor network environments. Artificial Intelligence is one of the study of computer Science and train the systems in a rational way. Machine Learning algorithms are supporting for the automated process by learning parameters which are narrated with neuron vales. In such cases, ordinary ML is not adequate like non-linier functions or signals. So we go for deep learning for improving the efficiency in aspects with larger hidden layers for processing both structured and unstructured data. In this paper, we introduced Deep Belief Network for securing the signals in wireless sensor networks. We have to initiate with feature extraction and classifying with deep learning for secure our WSN signals while transmitting or processing.