DETECTION OF THREATS IN INTERNET OF THING NETWORKS USING DEEP NEURAL NETWORKS

In many industrial industries, including medical, tracking, smart cities and vehicles, the internet of things (IoT) is still a very early day. It is therefore vulnerable to a series of major intrusion attacks as a paradigm. A vulnerability overview of IoT is presented in this paper and the Artificial Neural Network (ANN) are used to fight these attacks. The DNN, a sort of monitored ANN, is trained using internet packet traces and is then tested on its ability to thwart DDoS attacks. The ANN process is validated using an IoT network simulate. The experimental results show 99.4% precision and can detect DDoS attacks successfully.