Network intrusion detection system using ML

Abstract

In today's fast-paced technological landscape, advancements are happening at the speed of light. Every aspect of the surroundings is intricately linked to development and technology. AI, cloud computing, and the IoT reign supreme in the realm of technology. In the realm of cyberspace, everything is interconnected through computers and networking devices. With the increasing reliance on computers and the internet, ensuring safety becomes ever more critical. Safeguarding network architecture and the proper use of networking devices and tools play a vital role in cybersecurity. This study has developed a system called Network Intrusion Detection System using ML, which is suitable for home network environments. This paper has created an application that makes a significant impact on real-time network environments by providing security for a particular home network. Leveraging ML in networks has improved the results by providing accuracy and efficiency. The algorithm of Logistic Regression is used to demonstrate network behavior and classify network traffic as either in an "Attack" or "Benign" state. This helps in detecting suspicious activities across the network and can prevent them at a later stage.