Blockchain Agreement for Self-identification of Online Test Cheating: Improvement of Algorithm Performance

Due to the recent Coronavirus (COVID-19) outbreak, it is not easy for all schools to catch students’ irregularities during online classes. Research is conducted based on a transparent Blockchain that prevents such irregularities. We also want to verify the nodes participating in the test using the latest neuron engine and Blockchain technology. Nodes participating in the network for testing are reinforced using safe algorithms. This study also presents these research models and implements the test environment through the cloud environment of AWS (Amazon Web Service), a network environment. Nodes take the P2P environment and serve as online nodes during more real-time testing. The result data are also derived. These experimental environments later validate more node data. In addition, the experiment showed that the similarity and distribution levels were very good, close to "0," and the performance of the Blockchain was about 4,000 TPS, so the actual testable study was conducted. In this paper, we propose artificial intelligence neurons and verification Blockchain consensus algorithms to verify the evaluation of these online environments. In addition, proposals are made to study verification and performance data over a neural network. In the future, many diseases, etc. are expected to cause a paradigm shift in universities and educational institutions.