Abstract
The traditional intrusion detection as one of the network security defense technology, plays an important role in the field of network security. But in a cloud environment application there response speed, data size, and many other restrictions, unable to meet the demand of real time validity, etc. Therefore, to build an intrusion detection system in cloud computing environment is an important subject. This paper aims at the design requirements of intrusion detection in cloud environment, through the research of the intrusion detection algorithm, proposed the use of Extreme Learning Machine (ELM) algorithm as an intrusion detection classification algorithm and the rationality verification using extreme learning machine algorithm. At the same time for massive high-dimensional intrusion detection data redundancy and noise influences the efficiency of detection by principal component analysis PCA algorithm for feature extraction, dimensionality reduction to improve the detection efficiency, reduces the detection time. Experiment results show that the algorithm is effective.
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Sang, Y. (2019). Research on Intrusion Detection Algorithm in Cloud Computing. In: Hung, J., Yen, N., Hui, L. (eds) Frontier Computing. FC 2018. Lecture Notes in Electrical Engineering, vol 542. Springer, Singapore. https://doi.org/10.1007/978-981-13-3648-5_205
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DOI: https://doi.org/10.1007/978-981-13-3648-5_205
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