What is it about?
Intrusion Detection System (IDS) can reduce the losses caused by intrusion behaviors and protect users' information secu-rity. The effectiveness of IDS depends on the performance of the algorithm used in identifying intrusions. And traditional machine learning algorithms are limited to deal with the intrusion data with the characteristics of high-dimensionality, nonlinearity and imbalance. Therefore, this paper proposes an intrusion detection algorithm based on image enhanced convolutional neural network.
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Why is it important?
With the development of network technology, the rapid growth of the network scale brings not only convenience to people but also risks and challenges. Issues such as the theft of private data and the in-fringement of server resources have caused great distress to people. In order to solve the problems, intrusion detection technology came into being.
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This page is a summary of: Intrusion detection algorithm based on image enhanced convolutional neural network, Journal of Intelligent & Fuzzy Systems, August 2021, IOS Press, DOI: 10.3233/jifs-210863.
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