Prediction of Cyber Attacks Utilizing Deep Learning Model using Network/Web Traffic Data

Balaji Kannan, M. Sakthivanitha, S. Jayashree, R. Maruthi · 2024

Nowadays, cyber-attacks are growing predominantly due to the development of technologies. It will lead to financial losses to a company and the other problems related to attacks. It is very important to predict such attacks from outsiders to safeguard our networking systems to provide effective security. The Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning (DL) techniques leverage enormous amounts of data to identify the cyber attacks. These learning approaches are used to identify a broad range of cyber-attacks by analyzing the web traffic or network traffic to identify potential threats such as malware, network intrusions and other types of attacks. The study demonstrates the various deep learning methods to predict the anomalies and other potential threats with more accuracy in real time.

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