A Highly Secured Cyber Security Threat Detection and Prevention System for IoT Using He-DNN

The Internet of Things (IoT) is a modern age technology, designed with the vision to connect and also interconnect all the objects everywhere. A technological progression provides businesses with many comforts as well as helps the attackers and intruders to crack the IoT networks' security. Hence, the paper proposes a novel cyber security detection and prevention system using He-CNN. Initially, the packet data is pre-processed. Following this, most important packet features are selected and the selected features are given into the trained He-DNN model which classifies whether the packet data is normal or attacked. Finally, the proposed model is compared with the existing methodology. Thus, the experimental results demonstrate that the proposed methodology attains 100% accuracy, 100% precision, 100% recall, 100% sensitivity, 100% specificity, and 100% f1-score with 100% security level.