Published Paper Details:

IoT, Internet of Things is now becoming an inevitable part of everyone's life. IoT connects many devices, sensors, applications via wireless or mobile networks to fulfill the required tasks. IoT invests interest in various fields like agriculture, healthcare, smart cities, homes, cars, transportation, etc. Today IoT is being used extensively to lessen the burden of humans. Even though IoT eases human life but also opens to different security challenges. Security must be a priority while across the value chain from the device manufacturers, IoT Service providers, Retailers and consumers. Adopting IoT in a sensitive environment is really a challenging task because of subtle data. This may cause hazards for the nourishment of IoT in the coming days. In light of this, we try to examine the various factors that contribute to the challenges of IoT security. Intrusion Detection System can be used for the security of data as well as devices over the internet. In recent years Machine Learning techniques are applied in the detection of threats in IDS. This research, therefore, focuses on Machine Learning Techniques applied in Internet-of-Things and Intrusion Detection for IoT security. Denial of Service (DoS) is one of the most catastrophic attacks against IoT. In this paper, we investigate the prospects of using machine learning algorithms for securing IoT against DoS attacks.