Volume 35 Issue 5
May  2010
Turn off MathJax
Article Contents
Abstract
Related Articles
KANG Jian, SONG Yuanzhang. Application KCFM to Detect New P2P Botnet Based on Multi-Observed Sequence[J]. Geomatics and Information Science of Wuhan University, 2010, 35(5): 520-523.
Citation: KANG Jian, SONG Yuanzhang. Application KCFM to Detect New P2P Botnet Based on Multi-Observed Sequence[J]. Geomatics and Information Science of Wuhan University, 2010, 35(5): 520-523.
shu

Application KCFM to Detect New P2P Botnet Based on Multi-Observed Sequence

  • 1Department of Computer Science & Technology,Jilin University,2699 Qianjin Street,Changchun 130012,China

Funds: 国家自然科学基金重大研究计划资助项目(90204014)；国家自然科学基金资助项目(60703023)；吉林省科技发展计划资助项目(20090110)
More Information
  • Received Date: March 14, 2010
  • Revised Date: July 08, 2013
  • Published Date: May 04, 2010
    Graphical Abstract
    • Abstract
  • We propose a novel real-time detecting model-KCFM(Kalman filter and multi-chart CUSUM fused model) based on multi-observed sequence,which consists of several extracted the new P2P botnet characteristic properties.The KCFM finds the abnormal traffic by the discrete Kalman filter,and improves the detection precision by using the Multi-chart CUSUM as an amplifier.The experiments show that our approach can detect new decentralized botnet with a relatively high precision.
    • FullText(HTML)
    • References (0)
    • Related Articles

  • Related Articles

    [1]ZHAO Yunpeng, SUN Qun, LIU Xingui, CHENG Mianmian, YU Tong, LI Yuanfu. Geographical Entity-Oriented Semantic Similarity Measurement Method and Its Application in Road Matching[J]. Geomatics and Information Science of Wuhan University, 2020, 45(5): 728-735. DOI: 10.13203/j.whugis20190039
    [2]XIN Rui, AI Tinghua, YAN Xiongfeng, YANG Min. Similarity Measurement-Based Outline Design of Metaphor Map[J]. Geomatics and Information Science of Wuhan University, 2019, 44(4): 625-632. DOI: 10.13203/j.whugis20170153
    [3]CHEN Zhanlong, WU Liang, XIE Zhong, ZHANG Dingwen. Similarity Measurement of Multi-holed Regions Using Constraint Satisfaction Problem[J]. Geomatics and Information Science of Wuhan University, 2018, 43(5): 745-751, 785. DOI: 10.13203/j.whugis20160191
    [4]ZHU Jin, HU Bin, SHAO Hua. Trajectory Similarity Measure Based on Multiple Movement Features[J]. Geomatics and Information Science of Wuhan University, 2017, 42(12): 1703-1710. DOI: 10.13203/j.whugis20150594
    [5]XU Qiuhui, SHE Jiangfeng, SONG Xiaoqun, XIAO Pengfeng. Matching Low Altitude RS Image with Harris-Laplace and SIFT Descriptor[J]. Geomatics and Information Science of Wuhan University, 2012, 37(12): 1443-1447.
    [6]XIE Mingxia, WANG Jiayao, GUO Jianzhong, CHEN Ke. Similarity Measurement in High Dimensional Space Based on Unequally Spaced Partition[J]. Geomatics and Information Science of Wuhan University, 2012, 37(7): 780-783.
    [7]AN Xiaoya, SUN Qun, YU Bohu. Feature Matching from Network Data at Different Scales Based on Similarity Measure[J]. Geomatics and Information Science of Wuhan University, 2012, 37(2): 224-228.
    [8]WAN Xue. Generalized Point Photogrammetry Feature Extraction Based on Harris Operator and Vectorization[J]. Geomatics and Information Science of Wuhan University, 2012, 37(2): 145-148.
    [9]MA Guorui, SUI Haigang, LI Pingxiang, QIN Qianqing. A Kernel-based Similarity Measures for Change Detection in RS Images[J]. Geomatics and Information Science of Wuhan University, 2009, 34(1): 19-23.
    [10]DU Peijun, TANG Hong, FANG Tao. Algorithms for Spectral Similarity Measure in Hyperspectral RS[J]. Geomatics and Information Science of Wuhan University, 2006, 31(2): 112-115.

Catalog

    Get Citation
    PDF
    XML
    Article views (935) PDF downloads (341) Cited by()
    Related

    Copyright © 2013 《武汉大学学报·信息科学版》编辑部

    Address：武汉大学文理学部本科生院楼北5楼Post Code：430072

    Tel：027-68778465,68788631E-mail:whuxxb@vip.163.com

    Submit Article

    Submission Guidelines

    e

    Contact Us

    Qrcode

    Supported by: Beijing Renhe Information Technology Co., Ltd.  Baidu Analytics

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return