Back propagation neural network approach to Intrusion Detection System

Indraneel Mukhopadhyay; Mohuya Chakraborty; Satyajit Chakrabarti; Tamojit Chatterjee

doi:10.1109/retis.2011.6146886

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JOURNAL ARTICLE

Back propagation neural network approach to Intrusion Detection System

Indraneel Mukhopadhyay Mohuya Chakraborty Satyajit Chakrabarti Tamojit Chatterjee

Year: 2011 Vol: 10 Pages: 303-308

DOI: 10.1109/retis.2011.6146886

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Abstract

As the Internet is growing - so is the vulnerability of the network. Companies now days are spending huge amount of money to protect their sensitive data from different attacks that they face. In this paper, we propose a new methodology towards developing an Intrusion Detection System (IDS) based on Back-Propagation Neural Network (BPN) model. The proposed system was simulated using Matlab2010a utilizing benchmark intrusion KDDCUP'99 dataset to verify its feasibility and effectiveness.

Keywords:

Intrusion detection system Computer science Benchmark (surveying) Vulnerability (computing) Backpropagation Artificial neural network The Internet Intrusion Artificial intelligence Data mining Machine learning Face (sociological concept) Real-time computing Computer security World Wide Web

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Topics

Network Security and Intrusion Detection

Physical Sciences → Computer Science → Computer Networks and Communications

Advanced Malware Detection Techniques

Physical Sciences → Computer Science → Signal Processing

Internet Traffic Analysis and Secure E-voting

Physical Sciences → Computer Science → Artificial Intelligence

Back propagation neural network approach to Intrusion Detection System

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