Implementation of Parallel Lanczos Method for Intrusion Detection with Cloud Technologies

Abstract:

The aim of dimensionality reduction is to construct a low-dimensional representation of high dimensional input data in such a way, that important parts of the structure of the input data are preserved. This paper proposes to apply the dimensionality reduction to intrusion detection data based on the parallel Lanczos-SVD (PLSVD) with the cloud technologies. The massive input data is stored on distribution files system, like HDFS. And the Map/Reduce method is used for the parallel analysis on many cluster nodes. Our experiment results show that, compared with the PCA algorithm, PLSVD algorithm has better scalability and flexibility.

• Periodical: Applied Mechanics and Materials (Volumes 303-306)
• Pages: 2412-2415
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.303-306.2412
• Online since: February 2013
• Authors: Bo Chen, Yu Le Deng, Tie Ming Chen
• Keywords: Cloud Computing, Dimensionality Reduction, Intrusion Detection

References

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DOI: 10.1145/2079327.2079334