Abstract
Cyber security in the networked systems is the most challenging and risky aspects of the modern digital world. Due to the availability of computational resources, the area of deep learning is extensively used in many fields. In this proposal, we use IDS using convolutional neural network. Intrusion detection system with convolutional neural networks helps us to detect, analyze, and categorize the incoming or outgoing traffic into normal or attack. In this paper, we implemented IDS with CNN for binary classification and multiclass classification on given traffic data. The results proved that the proposed IDS using CNN is better than the other existing IDS models using machine learning.
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Maheshwar Reddy, V., Ravi Prakash Reddy, I., Adi Narayana Reddy, K. (2020). An Efficient Intrusion Detection System with Convolutional Neural Network. In: Chillarige, R., Distefano, S., Rawat, S. (eds) Advances in Computational Intelligence and Informatics. ICACII 2019. Lecture Notes in Networks and Systems, vol 119. Springer, Singapore. https://doi.org/10.1007/978-981-15-3338-9_22
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DOI: https://doi.org/10.1007/978-981-15-3338-9_22
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