基于流式计算的DDoS实时检测方法
TP393.08; 随着大数据时代的到来,DDoS攻击也愈发更具威胁性.近年来,随着以Spark-streaming、Storm为代表的流式计算系统的出现,让DDoS攻击检测不仅可以保持较高的精度,也更加具有实时性.选取三种比较具有代表性的DDoS攻击进行危险建模,构建以Spark-streaming为处理内核、朴素贝叶斯算法为处理算法的实时系统.采用对比实验,验证了本系统具有较高的实时性和准确度....
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| Published in | 计算机应用研究 Vol. 34; no. 3; pp. 892 - 896 |
|---|---|
| Main Author | |
| Format | Journal Article |
| Language | Chinese |
| Published |
南京邮电大学计算机学院,南京,210046%中兴通讯股份有限公司,南京,210012
2017
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1001-3695 |
| DOI | 10.3969/j.issn.1001-3695.2017.03.059 |
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| Abstract | TP393.08; 随着大数据时代的到来,DDoS攻击也愈发更具威胁性.近年来,随着以Spark-streaming、Storm为代表的流式计算系统的出现,让DDoS攻击检测不仅可以保持较高的精度,也更加具有实时性.选取三种比较具有代表性的DDoS攻击进行危险建模,构建以Spark-streaming为处理内核、朴素贝叶斯算法为处理算法的实时系统.采用对比实验,验证了本系统具有较高的实时性和准确度. |
|---|---|
| AbstractList | TP393.08; 随着大数据时代的到来,DDoS攻击也愈发更具威胁性.近年来,随着以Spark-streaming、Storm为代表的流式计算系统的出现,让DDoS攻击检测不仅可以保持较高的精度,也更加具有实时性.选取三种比较具有代表性的DDoS攻击进行危险建模,构建以Spark-streaming为处理内核、朴素贝叶斯算法为处理算法的实时系统.采用对比实验,验证了本系统具有较高的实时性和准确度. 随着大数据时代的到来,DDo S攻击也愈发更具威胁性。近年来,随着以Spark-streaming、Storm为代表的流式计算系统的出现,让DDo S攻击检测不仅可以保持较高的精度,也更加具有实时性。选取三种比较具有代表性的DDo S攻击进行危险建模,构建以Spark-streaming为处理内核、朴素贝叶斯算法为处理算法的实时系统。采用对比实验,验证了本系统具有较高的实时性和准确度。 |
| Abstract_FL | With the era of big data have arrived,DDoS attack becomes more dangerous.In recent years,streaming calculation system,such as Spark-streaming and Storm etc,have been used in the industry.If this technology can be used to DDoS attack detection.It may be the huge increasing for that.This paper selected three representative ways of DDoS attack as risk modeling,and built a real-time system with Spark-streaming as its processor core and Naive Bayesian as its algorithm.Finally it did the contrast experiments to verify its high real-time performance and high accuracy of this system. |
| Author | 许承启 何利文 王延松 呼学理 牛小兵 |
| AuthorAffiliation | 南京邮电大学计算机学院,南京210046 中兴通讯股份有限公司,南京210012 |
| AuthorAffiliation_xml | – name: 南京邮电大学计算机学院,南京,210046%中兴通讯股份有限公司,南京,210012 |
| Author_FL | Xu Chengqi He Liwen Hu Xueli Wang Yansong Niu Xiaobing |
| Author_FL_xml | – sequence: 1 fullname: Xu Chengqi – sequence: 2 fullname: He Liwen – sequence: 3 fullname: Wang Yansong – sequence: 4 fullname: Hu Xueli – sequence: 5 fullname: Niu Xiaobing |
| Author_xml | – sequence: 1 fullname: 许承启 何利文 王延松 呼学理 牛小兵 |
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| ClassificationCodes | TP393.08 |
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| Copyright | Copyright © Wanfang Data Co. Ltd. All Rights Reserved. |
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| DOI | 10.3969/j.issn.1001-3695.2017.03.059 |
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| DocumentTitleAlternate | Method of real-time detect DDoS based on streaming calculation |
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| Keywords | DDoS attack real-time 朴素贝叶斯算法 naive Bayes 实时性 DDoS攻击 流计算 Spark-streaming Streaming calculation |
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| Notes | 51-1196/TP DDoS attack; Streaming calculation; Spark-streaming; naive Bayes; real-time With the era of big data have arrived,DDoS attack becomes more dangerous. In recent years,streaming calculation system,such as Spark-streaming and Storm etc,have been used in the industry. If this technology can be used to DDoS attack detection. It may be the huge increasing for that. This paper selected three representative ways of DDoS attack as risk modeling,and built a real-time system with Spark-streaming as its processor core and Naive Bayesian as its algorithm. Finally it did the contrast experiments to verify its high real-time performance and high accuracy of this system. Xu Chengqi1, He Liwen1, Wang Yansong2, Hu Xueli2, Niu Xiaobing2 （1. School of Computer Science ＆ Technology, Nanjing University of Posts ＆ Telecommunications, Nanjing 210046, China; 2. Zhongxing Telecommunication Equipment Corporation, Nanjing 210012, China） |
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| Publisher | 南京邮电大学计算机学院,南京,210046%中兴通讯股份有限公司,南京,210012 |
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| Snippet | 随着大数据时代的到来,DDo S攻击也愈发更具威胁性。近年来,随着以Spark-streaming、Storm为代表的流式计算系统的出现,让DDo S攻击检测不仅可以保持较高的精度,也更加具有实... TP393.08; 随着大数据时代的到来,DDoS攻击也愈发更具威胁性.近年来,随着以Spark-streaming、Storm为代表的流式计算系统的出现,让DDoS攻击检测不仅可以保持较高的精度,也更... |
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| SubjectTerms | DDoS攻击 Spark-streaming 实时性 朴素贝叶斯算法 流计算 |
| Title | 基于流式计算的DDoS实时检测方法 |
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