Computational Intelligence such as Artificial Intelligence, Machine Learning, Deep Learning and Fuzzy System are providing good opportunities to researchers to work on security of IoT devices. IoT devices are sensor embedded devices that interact with environment and collect data and this data is used to control these devices but if this data is not managed properly with the service providers then it may become a big cause of security breach. In this proposed paper Computational Intelligence technique Machine Learning KNN, Naive Bayes and Decision Tree were used to detect attacks in an IoT data set IoT_Fridge. For easy access various IoT datasets like Edge-IIoTset, TONIoT, MQTT, Aposemat IoT, Bot-IoT, CTU-13 and MAWILab are also provided in this paper.Implementation and accuracy measurement of models performed on Jupyter Lab 2.1.5. Acurracy of KNN. Naive Baye and Decision Tree found 75%, 85% and 85% respectively. Finally, conclusion and future scope given at last of paper.