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

Kannan, Balaji and Sakthivanitha, M. and Jayashree, S. and Maruthi, R. (2024) Prediction of Cyber Attacks Utilizing Deep Learning Model using Network/Web Traffic Data. In: 2024 3rd International Conference on Applied Artificial Intelligence and Computing (ICAAIC), Salem, India.

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Abstract

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.

Item Type: Conference or Workshop Item (Paper)
Subjects: Computer Science Engineering > Deep Learning
Divisions: Computer Science
Depositing User: Mr IR Admin
Date Deposited: 06 Oct 2024 12:12
Last Modified: 06 Oct 2024 12:12
URI: https://ir.vistas.ac.in/id/eprint/9217

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