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A Real-Time and Ubiquitous Network Attack Detection Based on Deep Belief Network and Support Vector Machine

Hao Zhang Yongdan Li Zhihan Lv Arun Kumar Sangaiah Tao Huang

自动化学报（英文版）2020，Vol.7Issue(3)：790-799,10.
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自动化学报（英文版）2020，Vol.7Issue(3)：790-799,10.DOI:10.1109/JAS.2020.1003099

A Real-Time and Ubiquitous Network Attack Detection Based on Deep Belief Network and Support Vector Machine

A Real-Time and Ubiquitous Network Attack Detection Based on Deep Belief Network and Support Vector Machine

Hao Zhang 1Yongdan Li 2Zhihan Lv 3Arun Kumar Sangaiah 4Tao Huang1

作者信息

  • 1. National Engineering Laboratory for Educational Big Data,Central China Normal University,Wuhan 430072,China
  • 2. Lanzhou Central Sub-branch of The People's Bank of China,Lanzhou 730000,China
  • 3. School of Data Science and Software Engineering,Qingdao University,Qingdao 266071,China
  • 4. School of Computing Science and Engin-eering,Vellore Institute of Technology University,Tamil Nadu 632014,India
  • 折叠

摘要

关键词

Deep belief network (DBN)/flow calculation/fre-quent pattern/intrusion detection/sliding window/support vector machine (SVM)

Key words

Deep belief network (DBN)/flow calculation/fre-quent pattern/intrusion detection/sliding window/support vector machine (SVM)

引用本文复制引用

Hao Zhang,Yongdan Li,Zhihan Lv,Arun Kumar Sangaiah,Tao Huang..A Real-Time and Ubiquitous Network Attack Detection Based on Deep Belief Network and Support Vector Machine[J].自动化学报（英文版）,2020,7(3):790-799,10.

基金项目

This work was supported by the National Key Research and Development Program of China (2017YFB1401300,2017YFB1401304),the National Natural Science Foundation of China (61702211,L1724007,61902203),Hubei Provincial Science and Technology Program of China (2017AKA191),the Self-Determined Research Funds of Central China Nor-mal University (CCNU) from the Colleges' Basic Research (CCNU17QD00 04,CCNU17GF0002),the Natural Science Foundation of Shandong Province (ZR2017QF015),and the Key Research and Development Plan-Major Sci-entific and Technological Innovation Projects of Shandong Province (2019JZZY020101). （2017YFB1401300,2017YFB1401304）

自动化学报（英文版）

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2329-9266

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