Paper
7 December 2023 An intrusion detection method combining Bayesian optimization and LightGBM
Dongyuan Xu, Bin Hua
Author Affiliations +
Proceedings Volume 12941, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2023); 129413N (2023) https://doi.org/10.1117/12.3011542
Event: Third International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 203), 2023, Yinchuan, China
Abstract
Network is a double-edged sword, which brings great convenience and some risks at the same time. Then intrusion detection, as a proactive and defensive technical means, plays a very important role in protecting information systems. Traditional intrusion detection systems have the problems of low detection accuracy and poor real-time performance, while the existing network intrusion detection data is not balanced, so this paper proposes an adaptive synthesis algorithm (ADASYN) oversampling and class balancing data balancing algorithm and an intrusion detection method of LightGBM combined with Bayesian optimization algorithm, aiming to solve the above problems. First, data preprocessing we encode the data with labels as well as unique heat encoding to better pass into the model for processing, after that we increase a few classes of data by ADASYN oversampling to make the number of samples in each class relatively balanced, and finally the features are passed into LightGBM for learning and training, and finally validated in the NSL-KDD dataset for multi-class classification experiments, and the results show that compared with other traditional algorithms, all data are improved and show better performance.
(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Dongyuan Xu and Bin Hua "An intrusion detection method combining Bayesian optimization and LightGBM", Proc. SPIE 12941, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2023), 129413N (7 December 2023); https://doi.org/10.1117/12.3011542
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KEYWORDS
Computer intrusion detection

Education and training

Data modeling

Mathematical optimization

Performance modeling

Detection and tracking algorithms

Feature extraction

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