一级黄色片免费播放|中国黄色视频播放片|日本三级a|可以直接考播黄片影视免费一级毛片

高級(jí)搜索

留言板

尊敬的讀者、作者、審稿人, 關(guān)于本刊的投稿、審稿、編輯和出版的任何問(wèn)題, 您可以本頁(yè)添加留言。我們將盡快給您答復(fù)。謝謝您的支持!

姓名
郵箱
手機(jī)號(hào)碼
標(biāo)題
留言內(nèi)容
驗(yàn)證碼

基于抽樣流長(zhǎng)與完全抽樣閾值的異常流自適應(yīng)抽樣算法

伊鵬 錢坤 黃萬(wàn)偉 王晶 張震

伊鵬, 錢坤, 黃萬(wàn)偉, 王晶, 張震. 基于抽樣流長(zhǎng)與完全抽樣閾值的異常流自適應(yīng)抽樣算法[J]. 電子與信息學(xué)報(bào), 2015, 37(7): 1606-1611. doi: 10.11999/JEIT141379
引用本文: 伊鵬, 錢坤, 黃萬(wàn)偉, 王晶, 張震. 基于抽樣流長(zhǎng)與完全抽樣閾值的異常流自適應(yīng)抽樣算法[J]. 電子與信息學(xué)報(bào), 2015, 37(7): 1606-1611. doi: 10.11999/JEIT141379
Yi Peng, Qian Kun, Huang Wan-wei, Wang Jing, Zhang Zhen. Adaptive Flow Sampling Algorithm Based on Sampled Packets and Force Sampling Threshold S Towards Anomaly Detection[J]. Journal of Electronics & Information Technology, 2015, 37(7): 1606-1611. doi: 10.11999/JEIT141379
Citation: Yi Peng, Qian Kun, Huang Wan-wei, Wang Jing, Zhang Zhen. Adaptive Flow Sampling Algorithm Based on Sampled Packets and Force Sampling Threshold S Towards Anomaly Detection[J]. Journal of Electronics & Information Technology, 2015, 37(7): 1606-1611. doi: 10.11999/JEIT141379

基于抽樣流長(zhǎng)與完全抽樣閾值的異常流自適應(yīng)抽樣算法

doi: 10.11999/JEIT141379
基金項(xiàng)目: 

國(guó)家973計(jì)劃項(xiàng)目(2012CB315901, 2013CB329104)

Adaptive Flow Sampling Algorithm Based on Sampled Packets and Force Sampling Threshold S Towards Anomaly Detection

  • 摘要: 高速IP網(wǎng)絡(luò)的流量測(cè)量與異常檢測(cè)是網(wǎng)絡(luò)測(cè)量領(lǐng)域研究的熱點(diǎn)。針對(duì)目前網(wǎng)絡(luò)流量測(cè)量算法對(duì)小流估計(jì)精度偏低,對(duì)異常流量篩選能力較差的缺陷,該文提出一種基于業(yè)務(wù)流已抽樣長(zhǎng)度與完全抽樣閾值S的自適應(yīng)流抽樣算法(AFPT)。AFPT算法根據(jù)完全抽樣閾值S篩選對(duì)異常流量敏感相關(guān)的小流,同時(shí)根據(jù)業(yè)務(wù)流已抽樣長(zhǎng)度自適應(yīng)調(diào)整抽樣概率。仿真和實(shí)驗(yàn)結(jié)果表明,AFPT算法的估計(jì)誤差與理論上界相符,具有較強(qiáng)的異常流量篩選能力,能夠有效提高異常檢測(cè)算法的準(zhǔn)確率。
  • Zhou Ai-ping, Cheng Guang, and Guo Xiao-jun. High-speed network traffic measurement method[J]. Journal of Software, 2014, 25(1): 135-153.
    Peter Lieven and Bj?rnScheuermann. High-speed per-flow traffic measurement with probabilistic multiplicity counting [C]. Proceedings of the INFOCOM 2010, San Diego, CA, USA, 2010: 1-9.
    Cheng Guang and Tang Yong-ning. Estimation algorithms of the flow number from sampled packets on approximate approaches[J]. Journal of Software, 2013, 24(2): 255-265.
    Lee Y J, Yeh Y R, and Wang Y C F. Anomaly detection via online oversampling principal component analysis[J]. IEEE Transactions on Knowledge and Data Engineering, 2013, 25(7): 1460-1470.
    Pham D S, Venkatesh S, Lazarescu M, et al.. Anomaly detection in large-scale data stream networks[J]. Data Mining and Knowledge Discovery, 2014, 28(1): 145-189.
    Cai Yuan-jun, Wu Bin, Zhang Xin-wei, et al.. Flow identification and characteristics mining from internet traffic with hadoop[C]. Proceedings of the Computer Information and Telecommunication Systems (CITS), Jeju Island, Korea, 2014: 1-5.
    Brauckhoff D, Tellenbach B, Wagner A, et al.. Impact of packet sampling on anomaly detection metrics[C]. Proceedings. of the 6th ACM Sigcomm conference on Internet measurement, Rio de Janeiro, Brazil, 2006: 159-164.
    Mai Jian-ning, Chuah C N, Sridharan A, et al.. Is sampled data sufficient for anomaly detection?[C]. Proceedings of the 6th ACM Sigcomm Conference on Internet Measurement, Rio de Janeiro, Brazil, 2006: 165-176.
    Kumar A and Xu J. Sketch guided sampling using on-line estimates of flow size for adaptive data collection[C]. Proceedings of IEEE INFOCOM 2006, Barcelona, Spain, 2006: 1-11.
    Li Tao and Chen Shi-gang. Per-flow traffic measurement through randomized counter sharing[J]. IEEE ACM Transactions on Networking, 2012, 13(5): 325-336.
    王蘇南. 高速?gòu)?fù)雜網(wǎng)絡(luò)環(huán)境下異常流量檢測(cè)技術(shù)研究[D]. [博士論文], 信息工程大學(xué), 2012:38-49.
    Wang Su-nan. Research on anomaly detection technology in high-speed complex network environment[D]. [Ph.D. dissertation], The PLA Information Engineering University, 2012: 38-49.
    郭通. 基于自適應(yīng)流抽樣測(cè)量的網(wǎng)絡(luò)異常檢測(cè)技術(shù)研究[D]. [博士論文], 信息工程大學(xué), 2013: 38-49.
    Guo Tong. Research on network anomaly detection technology based on adaptive flow sampling measurement[D]. [Ph.D. dissertation], The PLA Information Engineering University, 2013: 38-49.
    Lakhina A, Crovella M, and Diot C. Mining anomalies using traffic feature distributions[C]. Proceedings of the 5th ACM Sigcomm Conference on Internet Measurement, Philadelphia, PA, USA, 2005: 217-228.
  • 加載中
計(jì)量
  • 文章訪問(wèn)數(shù):  1424
  • HTML全文瀏覽量:  183
  • PDF下載量:  1187
  • 被引次數(shù): 0
出版歷程
  • 收稿日期:  2014-10-29
  • 修回日期:  2015-01-13
  • 刊出日期:  2015-07-19

目錄

    /

    返回文章
    返回