Machine Learning based Man-in-the-Middle Attack Prediction
K. Venkateswara Rao, B. Akshaya, G. Gershon Satvik, B. Rohith, G. Lahari · 2024
In today’s digital world, people are using networks and communication channels. With this increase, there’s also a rise in different kinds of attacks aimed at online users. One of the most notable threats is the man-in-the-middle attack. Detecting this type of attack is tough because the attacker tries to stay hidden. They aim to intercept important user information without being noticed. The proposed system uses machine learning techniques and provides a solution by predicting when man-in-the-middle attacks might happen. Here, the prediction is done by analyzing data from both general and wireless network monitoring tools. Additionally, this study makes it easier to understand the data by presenting it in different formats and enabling a thorough risk analysis.