Classification of IoT based DDoS Attack using Machine Learning Techniques

Recently, (IoT) the internet of things and other internet-connected devices have witnessed mushroom growth. This has resulted in an infinite and continuous growth of ever- increasing data. The interconnection of sensor networks, bluetooth, WiFi, GSM, LTE, Sigfix networks incur multiplied security challenges as compared to their individual issues. Countering security-related limitations is an increasingly hot research area. One of these problems is DDoS(Distributed denial of service) attacks incur a large number of bots to bottleneck the bandwidth of a server. The intention of this paper is to classify normal and DDoS traffic in the IoT network using existing machine learning techniques.