Self-Adaptive Framework for Rectification and Detection of Black Hole and Wormhole Attacks in 6LoWPAN

Abstract

Internet network communication protocol version 6 low-power wireless personal area networks (6LoWPAN) is supposed to assist the gadgets with low-power wireless sensor network (WSN) and it furnishes the top model layer of the data transmission system. The 6LoWPAN is prone to the diversified attacks such as wormhole and black hole attacks, which might be very difficult to become aware of and defend. In a wormhole attack, the attacker listens to the facts over the networks, and in a black hole attack, the intruder reprograms the nodes to dam the data transmission. As an end result, any data datagram that enters the attacked region will end result in transmission failure with low flow network rate and excessive one-way delay. To come across and heal the attack, a self-adaptive framework is brought into the networks and the procedure of data transmission is enriched. In this work, the affected region is measured and rectified with the aid of using the proposed self-adaptive framework for Ad Hoc On-Demand Distance Vector (AODV) routing protocol network communication protocol. The overall performance of the network healing technique is investigated with the aid of using simulation and its miles diagnosed that the proposed framework suggests promising overall performance with the aid of using accomplishing excessive flow network rate and minimum delay