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The Internet is a communication network where two or more than two users communicate and exchange the data. Black hole attack is a security threat in which a malicious node drops some or all of the packets. The proposed framework implements a biometric authentication system into the communication network to verify the user and to save the user from any internal or external threat. The main objective is to integrate the biometric security with the communication network. The attack is supposed to be a Black hole which has been considered as a smart attack. Feature extraction of Fingerprint dataset will be done using minutiae extractor. This will extract ridge endings and ridge bifurcation from the thinned image. Genetic algorithm is usedto reduce the features to useful pool. If the user is authentic only then prevention mechanism against black hole is applied. Genetic Algorithm is used to find out black hole node based on the fitness function. Proposed model’s performance is evaluated using various metrics like delay, throughput, energy consumption and packet delivery ratio.

Internet of Things for the Prevention of Black Hole Using Fingerprint Authentication and Genetic Algorithm Optimization