Detection and Analysis of Botnet Attacks Using Machine Learning Techniques
Supriya Raheja · 2024
The Internet of Things ( IoT ) allows connections between billions of devices to store different types of data using sensors. This data can be reused for multiple purposes like for monitoring and controlling organizational functions. However, the technology faces one major challenge that is security threat as data is moving through networks. To solve this challenge, machine learning ( ML ) plays an important role and even opened many new research areas. ML may be used in detection of threats and attacks when intelligent devices are communicating over the network. This study implements five different classifiers namely logistic regression, decision tree, random forest ( RF ), Naïve Bayes, and K -nearest neighbor for identifying the botnet attacks in the IoT environment. Results prove the RF classifier gives the best accuracy among the five classifiers.