Evaluation of Cluster Approach for Detecting Black Hole Attacks in Wireless Ad Hoc Networks using Deep Learning

The cluster approach consists of a huge level of significance as it can easily detect the black hole attacks on various networks such as “wireless ad hoc networks' ‘(WANET), MANET and many others. This research paper comprises a detailed introduction part where important definitions and clear ideas have been given on some key topics such as Cluster approach, black hole attack on various networks and a detailed view about WANET. The types of this network, some advantages and the usage of this network have been discussed thoroughly in this context. The literature review part also reflects the challenges as well as disadvantages of the proposed networking systems and various proposed mechanisms to detect black hole attacks in a short time. This literature review part has constructed as a critical manner and several mechanisms of identification of black hole precisely mentioned with providing clear as well as relevant pictures. The research methodology part clearly has expressed the overall process of concluding over the effectiveness of the clustering approach. After that, the discussion part clearly has delivered a transparent mechanism by following which black holes can be detected easily. It also supports the survey responses also. In the result portion, a detailed survey has occurred in the presence of 35 individuals and two direct questions have been asked to evaluate the effectiveness of the cluster approach for detecting WANET.