基于K-means算法的聚类拒绝服务攻击可视化

N. A. Putri, D. Stiawan, Ahmad Heryanto, T. W. Septian, L. Siregar, R. Budiarto
{"title":"基于K-means算法的聚类拒绝服务攻击可视化","authors":"N. A. Putri, D. Stiawan, Ahmad Heryanto, T. W. Septian, L. Siregar, R. Budiarto","doi":"10.1109/ICECOS.2017.8167129","DOIUrl":null,"url":null,"abstract":"Visualization became one of the solutions in showing the attack on the network. With Visualize the attack, it would be easier in recognizing and conclude the pattern from the complex image visual. The target of DoS attacks can be addressed to the various parts of the network, it can be routing, web, electronic mail or DNS servers (Domain Name System). The purpose of the DoS attacks create a server shutdown, reboot, crashes or not responding. The pattern of DoS attacks on the dataset ISCX form a pattern where much of his host's IP just to exploit to a single server. Snort detects a DoS attack on testbed ISCX dataset as much as 42 alert HttpDoS attack. Percentage accuracy of the clustering algorithm using k-means of 97,83%, to its rate of detection 98,63%, and the false alarm of the programme amounting to 0.02%. Meanwhile, the value of the percentage accuracy of the clustering algorithm using k-means with tool WEKA of 99,69%, the detection rate of 99.01% and false alarms of 3.70%. The difference in accuracy between value and clustering tool WEKA caused the value of the centroid is used in mneg-cluster data packets randomly selected from a data value pack.","PeriodicalId":6528,"journal":{"name":"2017 International Conference on Electrical Engineering and Computer Science (ICECOS)","volume":"12 1","pages":"177-183"},"PeriodicalIF":0.0000,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Denial of service attack visualization with clustering using K-means algorithm\",\"authors\":\"N. A. Putri, D. Stiawan, Ahmad Heryanto, T. W. Septian, L. Siregar, R. Budiarto\",\"doi\":\"10.1109/ICECOS.2017.8167129\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Visualization became one of the solutions in showing the attack on the network. With Visualize the attack, it would be easier in recognizing and conclude the pattern from the complex image visual. The target of DoS attacks can be addressed to the various parts of the network, it can be routing, web, electronic mail or DNS servers (Domain Name System). The purpose of the DoS attacks create a server shutdown, reboot, crashes or not responding. The pattern of DoS attacks on the dataset ISCX form a pattern where much of his host's IP just to exploit to a single server. Snort detects a DoS attack on testbed ISCX dataset as much as 42 alert HttpDoS attack. Percentage accuracy of the clustering algorithm using k-means of 97,83%, to its rate of detection 98,63%, and the false alarm of the programme amounting to 0.02%. Meanwhile, the value of the percentage accuracy of the clustering algorithm using k-means with tool WEKA of 99,69%, the detection rate of 99.01% and false alarms of 3.70%. The difference in accuracy between value and clustering tool WEKA caused the value of the centroid is used in mneg-cluster data packets randomly selected from a data value pack.\",\"PeriodicalId\":6528,\"journal\":{\"name\":\"2017 International Conference on Electrical Engineering and Computer Science (ICECOS)\",\"volume\":\"12 1\",\"pages\":\"177-183\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 International Conference on Electrical Engineering and Computer Science (ICECOS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICECOS.2017.8167129\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Conference on Electrical Engineering and Computer Science (ICECOS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICECOS.2017.8167129","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6

摘要

可视化成为显示网络攻击的解决方案之一。使用可视化攻击,可以更容易地从复杂的图像视觉中识别和总结模式。DoS攻击的目标可以是网络的各个部分,可以是路由、web、电子邮件或DNS服务器(域名系统)。DoS攻击的目的是造成服务器关闭、重新启动、崩溃或无响应。对数据集ISCX的DoS攻击模式形成了一种模式,其中大部分主机的IP只是为了利用到单个服务器。Snort检测到对试验台ISCX数据集的DoS攻击,多达42次警告HttpDoS攻击。使用k-means的聚类算法的准确率为97.83%,其检测率为98.63%,程序的虚警率为0.02%。同时,使用WEKA工具的k-means聚类算法的百分比准确率值为99.69%,检出率为99.01%,虚警率为3.70%。利用从数据值包中随机选取的多聚类数据包,利用聚类工具WEKA和质心值之间的精度差异。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Denial of service attack visualization with clustering using K-means algorithm
Visualization became one of the solutions in showing the attack on the network. With Visualize the attack, it would be easier in recognizing and conclude the pattern from the complex image visual. The target of DoS attacks can be addressed to the various parts of the network, it can be routing, web, electronic mail or DNS servers (Domain Name System). The purpose of the DoS attacks create a server shutdown, reboot, crashes or not responding. The pattern of DoS attacks on the dataset ISCX form a pattern where much of his host's IP just to exploit to a single server. Snort detects a DoS attack on testbed ISCX dataset as much as 42 alert HttpDoS attack. Percentage accuracy of the clustering algorithm using k-means of 97,83%, to its rate of detection 98,63%, and the false alarm of the programme amounting to 0.02%. Meanwhile, the value of the percentage accuracy of the clustering algorithm using k-means with tool WEKA of 99,69%, the detection rate of 99.01% and false alarms of 3.70%. The difference in accuracy between value and clustering tool WEKA caused the value of the centroid is used in mneg-cluster data packets randomly selected from a data value pack.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信