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Authors: Guanyao Du ; Chun Long ; Jianjun Yu ; Wei Wan ; Jing Zhao and Jinxia Wei

Affiliation: Computer Network Information Center, Chinese Academy of Sciences, 4 Zhongguancun Nansijie, Haidian District Beijing 100190 and China

ISBN: 978-989-758-372-8

Keyword(s): Network Security Situation Monitoring, Big Data, Real Time Computation, Visualization.

Abstract: In this paper, we provide a real-time calculation and visualization framework for network security situation monitoring based on big data technology, and it mainly realizes the real-time massive multi-dimensional network attack dynamic display with Data-Driven Documents (D3). Firstly, we propose an integration and storage management mechanism of massive heterogeneous multi-source data for the network security data fusion. Then, we provide a general real time data computation and visualization framework for massive network security data. Based on the framework, we use the real security data of the network security cloud service platform of Chinese Academy of Sciences (CAS) to realize the visualization monitoring of network security dynamic attacks nationwide and worldwide, respectively. Experiment results are given to analyze the performance of our proposed framework on the efficiency of the data integration and computation stages.

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Paper citation in several formats:
Du, G.; Long, C.; Yu, J.; Wan, W.; Zhao, J. and Wei, J. (2019). A Real-time Big Data Framework for Network Security Situation Monitoring.In Proceedings of the 21st International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-758-372-8, pages 167-175. DOI: 10.5220/0007708301670175

@conference{iceis19,
author={Guanyao Du. and Chun Long. and Jianjun Yu. and Wei Wan. and Jing Zhao. and Jinxia Wei.},
title={A Real-time Big Data Framework for Network Security Situation Monitoring},
booktitle={Proceedings of the 21st International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2019},
pages={167-175},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007708301670175},
isbn={978-989-758-372-8},
}

TY - CONF

JO - Proceedings of the 21st International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - A Real-time Big Data Framework for Network Security Situation Monitoring
SN - 978-989-758-372-8
AU - Du, G.
AU - Long, C.
AU - Yu, J.
AU - Wan, W.
AU - Zhao, J.
AU - Wei, J.
PY - 2019
SP - 167
EP - 175
DO - 10.5220/0007708301670175

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