PROTECTION AND SECURITY INTELLIGENCE IN CONTEMPORARY RPL USING IOT TECHNIQUES FOR PRIVACY PROTECTION AND INTRUSION DETECTION

Author (s) : V.MEENA, K.AMBIKA, B.S.SANGEETHA, .M.RADHA

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Abstract :
In the past few years, the Internet has grown swiftly, bringing with it various applications in numerous sectors, like transportation, education, entertainment, etc. Numerous items were created during this time, including businesses, television programs, and the still significant Internet. The best-in-class era of this general association is the Internet of Things (IoT), in which a sizable number of "Things" are necessary for the Internet to provide new opportunities and issues. Data uplink and downlink using RPMA (Random Phase Multiple Access) ensure that the information is perceived. It integrates the hyper-accessibility correspondence to the common by using LTE 5G (Long Term Evolution in 5G), which is used to assemble the usefulness and performance that seemed differently about the present. It helps to make things more secure. Due to MUX/DEMUX. The invasion is discovered using DT (Decision Trees), KNN (K-Means Nearest Neighborhood), and EMANN (Ensemble Methods of Artificial Neural Networks). These three methods are utilized to halt the intrusion and improve LTE-5 IoT processing efficiency. By enhancing the constituent methods' predictive capacities with EMANN, RPL (Routing Protocol with Low-Power) reduction helps to improve IPV6's detection and prediction processing.

Keywords : LTE 5G (Long Term Evolution in 5G), RPMA (Random Phase Multiple Access), DT (Decision Trees), KNN (K-Means nearest Neighborhood), EMANN (Ensemble Methods of Artificial Neural Networks)

Conference Date : 30/08/2019

Pages : 211

Paper ID : 19202