Abstract:
This project aims to help enhance the management of network traffic using advanced technologies, specifically focusing on Artificial Intelligence (AI) and Machine Learning (ML) techniques. With the exponential increase in data transmission over networks, it has become important to deploy intelligent systems that can efficiently analyze and categorize this data. This project proposes the utilization of the classification technique to effectively organize internet traffic. Despite the existence of various machine learning methods developed by researchers, achieving a system with high accuracy in network traffic detection remains a challenge. Classification is particularly suitable for this task due to its efficacy in distinguishing between distinct categories of network traffic, such as UDP and TCP at the transport layer. The system aims to help improve the efficiency of network traffic management by providing accurate and reliable classification and insights about the data, which is crucial for maintaining optimal network performance. This project will involve the design, implementation, and evaluation of a classification model, with a focus on enhancing its accuracy and reliability for real-world scenarios. The successful deployment of this model could significantly contribute to the field of network traffic management, offering a robust solution to the ongoing challenges in data analysis and traffic categorization
