An Efficient Algorithm to Enhance Confidentiality, Security and Quality of Service(QoS) for Internet of Things(IoT) Communication Network

Abstract

The communication between physical devices and Internet environment provides a flexible and more secure by Internet of Things(IoT) enable Cyber Physical Systems. The cyber physical systems are providing a bridge between physical systems platform to virtual system platform for better usage of communication technology. The IoT devices are less battery life, less processing capability and small in size. These sensor devices are constrained devices are suitable for constrained network where network is un-reliable and require low bandwidth. It is essential to provide security for these sensor devices for securely data transfer is a challenging task. To solve this task as well as to fulfill various performance metrics like minimum time consumption, enhance secure communication between these IoT devices, memory usage, confidentiality rate etc. The proposed paper applying a Cryptography based Secure Encrypted & Decryption Algorithm(CSEDA) algorithm to provide security and also to minimize attacks for IoT device in a secure network communication. In the first step, the IoT sensor devices are sensed and collected real-time analog data from outer environment. This collected data will be analyzed in hidden layer with jackknife regression function. In the second step, these classified data to be forward to further hidden layer to encrypt the data will be perform by Schmidt Samoa (SS) Encryption Algorithm after that the data will transform to cloud for store & further process. In the third step, The decryption is performed by Schmidt Samo (SS) Decryption Algorithm. In the cloud the finally the original data is stored in the database for further processing. This method is providing the security of data communication and processing with less time. The real-time data is being sensed and collected by sensor devices and perform classification, processing time and memory usage. The proposed CSEDA method providing high confidentiality of the data and minimize processing time and well utility of memory space when compare with existing algorithms GRBFNN, Deep learning model, JRSSC-DASL.