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}
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.