{"title":"基于主机/网络IDS警报深度归一化的攻击路径可视化","authors":"Amir Azodi, Feng Cheng, C. Meinel","doi":"10.1109/AINA.2016.129","DOIUrl":null,"url":null,"abstract":"Mitigation techniques employed by attackers has meant that traditional Network Intrusion Detection Systems (NIDS) are no longer able to reliably protect a network in the face of ever more sophisticated attacks. Security Information and Event Management (SIEM) systems monitor network systems by analyzing the logs they produce. In this paper, we propose a method of visualizing attacks by aggregating, normalizing and analyzing alerts raised by SIEM-based IDS (SIDS) systems as well as NIDS systems in real-time. We present the results of our proposed visualization technique when applied to different attack scenarios. In many cases, our approach allows for the path an attacker takes during their attack to be visualized.","PeriodicalId":438655,"journal":{"name":"2016 IEEE 30th International Conference on Advanced Information Networking and Applications (AINA)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Towards Better Attack Path Visualizations Based on Deep Normalization of Host/Network IDS Alerts\",\"authors\":\"Amir Azodi, Feng Cheng, C. Meinel\",\"doi\":\"10.1109/AINA.2016.129\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Mitigation techniques employed by attackers has meant that traditional Network Intrusion Detection Systems (NIDS) are no longer able to reliably protect a network in the face of ever more sophisticated attacks. Security Information and Event Management (SIEM) systems monitor network systems by analyzing the logs they produce. In this paper, we propose a method of visualizing attacks by aggregating, normalizing and analyzing alerts raised by SIEM-based IDS (SIDS) systems as well as NIDS systems in real-time. We present the results of our proposed visualization technique when applied to different attack scenarios. In many cases, our approach allows for the path an attacker takes during their attack to be visualized.\",\"PeriodicalId\":438655,\"journal\":{\"name\":\"2016 IEEE 30th International Conference on Advanced Information Networking and Applications (AINA)\",\"volume\":\"10 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-03-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE 30th International Conference on Advanced Information Networking and Applications (AINA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/AINA.2016.129\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE 30th International Conference on Advanced Information Networking and Applications (AINA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AINA.2016.129","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Towards Better Attack Path Visualizations Based on Deep Normalization of Host/Network IDS Alerts
Mitigation techniques employed by attackers has meant that traditional Network Intrusion Detection Systems (NIDS) are no longer able to reliably protect a network in the face of ever more sophisticated attacks. Security Information and Event Management (SIEM) systems monitor network systems by analyzing the logs they produce. In this paper, we propose a method of visualizing attacks by aggregating, normalizing and analyzing alerts raised by SIEM-based IDS (SIDS) systems as well as NIDS systems in real-time. We present the results of our proposed visualization technique when applied to different attack scenarios. In many cases, our approach allows for the path an attacker takes during their attack to be visualized.