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Exception Detection of Data Stream Based on Improved Maximal Frequent Itemsets Mining

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Trusted Computing and Information Security (CTCIS 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 704))

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Abstract

The security of data stream attracts more attention in daily life, the huge number of data stream makes it impossible to detect its exceptions, and the maximal frequent itemsets (MFIs) can perfectly imply data stream and the number is smaller, therefore, the time cost and memory usage are much more efficient. This paper proposes DMFI to detect the exceptions of data stream, an improved method called MRMFI and a pattern matching method called IM-Sunday and included in DMFI. MRMFI mines the MFIs from data stream and it uses two matrices to store the information, the frequent multiple-itemsets are generated by the extension of frequent 2-itemsets. Then, the exceptions are detected by using IM-Sunday algorithm to match the patterns in MFIs. Some experimental studies are conducted based on proposed method, the results show that the MRFIM method can mine MFIs in less time and DMFI can efficiently detect the exceptions of data stream.

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Acknowledgments

This work was supported by Scientific and technological key projects of Xinjiang Production & Construction Corps (Grant No. 2015AC023).

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Authors and Affiliations

  1. College of Information and Electrical Engineering, China Agricultural University, Beijing, China

    Saihua Cai, Ruizhi Sun & Chunming Cheng

  2. Secretary of Computer Science Department, Tarim University, Alar, China

    Gang Wu

Authors
  1. Saihua Cai
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  2. Ruizhi Sun
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  3. Chunming Cheng
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  4. Gang Wu
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Corresponding author

Correspondence to Ruizhi Sun .

Editor information

Editors and Affiliations

  1. National University of Defense Technology, Changsha, China

    Ming Xu

  2. Hunan University, Changsha, Hunan, China

    Zheng Qin

  3. Wuhan University, Wuhan, China

    Fei Yan

  4. National University of Defense Technology, Changsha, Hunan, China

    Shaojing Fu

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Cai, S., Sun, R., Cheng, C., Wu, G. (2017). Exception Detection of Data Stream Based on Improved Maximal Frequent Itemsets Mining. In: Xu, M., Qin, Z., Yan, F., Fu, S. (eds) Trusted Computing and Information Security. CTCIS 2017. Communications in Computer and Information Science, vol 704. Springer, Singapore. https://doi.org/10.1007/978-981-10-7080-8_10

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  • DOI: https://doi.org/10.1007/978-981-10-7080-8_10

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-7079-2

  • Online ISBN: 978-981-10-7080-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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