Convolutional Neural Networks for Real-Time Intrusion Detection in Network  Security Architectures

Sridhar Sriharsha Rachakonda ,Ramesh Lakshmikanth

Convolutional Neural Networks for Real-Time Intrusion Detection in Network Security Architectures

Authors

Sridhar Sriharsha Rachakonda ,Ramesh Lakshmikanth

Keywords:

Convolutional neural networks, Network security, Intrusion detection, Packet analysis, Machine learning

Abstract

Intrusion detection remains one of the mostcritical challenges in safeguarding modern network infrastructures, particularly as cyberattacks continue to evolvein scale and sophistication. Conventional approaches

References

Vinayakumar, R., Soman, K. P., & Poornachandran, P. (2017, September). Applying convolutional neural network for network

intrusion detection. In 2017 International conference on advances in computing, communications and informatics (ICACCI) (pp. 12221228). IEEE.

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Published

2026-01-31

How to Cite

Sridhar Sriharsha Rachakonda ,Ramesh Lakshmikanth. (2026). Convolutional Neural Networks for Real-Time Intrusion Detection in Network Security Architectures. Journal of Computational Analysis and Applications (JoCAAA), 35(1), 1131–1138. Retrieved from https://www.eudoxuspress.com/index.php/pub/article/view/4846