Autoencoders Based Optimized Deep Learning Model for the Detection of Cyber Attack in IoT Environment
Brij Bhooshan Gupta, Akshat Gaurav, Kwok Tai Chui, Varsha Arya, Chang Choi · 2024
The Internet of Things (IoTs) are a smart devices that connect the cyber and physical worlds. Nowadays, IoT has applications in many domains. However, various threats could disrupt IoT activities. In order to identify cyber attacks in an IoT environment, this study introduced a deep learning and autoencoder-based model. The performance of the prospered approach is calculated by accuracy, recall, and f1 score. Our prospered approach is 90% accuracy in detecting malicious traffic.