E. Cambiaso, M. Aiello, M. Mongelli, Gianluca Papaleo
{"title":"基于特征变换和互信息的DNS隧道分析","authors":"E. Cambiaso, M. Aiello, M. Mongelli, Gianluca Papaleo","doi":"10.1109/ICUFN.2016.7536939","DOIUrl":null,"url":null,"abstract":"Tunneling attacks are executed to bypass security policies or leak sensitive data outside of a network. In this paper, we propose an innovative algorithm to profile DNS tunnels. Our approach combines Principal Component Analysis and Mutual Information. The proposed algorithm is validated on a live network. Results show that, under specific conditions, anomalies are correctly characterized through the proposed method. Other cases require instead further investigation.","PeriodicalId":403815,"journal":{"name":"2016 Eighth International Conference on Ubiquitous and Future Networks (ICUFN)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":"{\"title\":\"Feature transformation and Mutual Information for DNS tunneling analysis\",\"authors\":\"E. Cambiaso, M. Aiello, M. Mongelli, Gianluca Papaleo\",\"doi\":\"10.1109/ICUFN.2016.7536939\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Tunneling attacks are executed to bypass security policies or leak sensitive data outside of a network. In this paper, we propose an innovative algorithm to profile DNS tunnels. Our approach combines Principal Component Analysis and Mutual Information. The proposed algorithm is validated on a live network. Results show that, under specific conditions, anomalies are correctly characterized through the proposed method. Other cases require instead further investigation.\",\"PeriodicalId\":403815,\"journal\":{\"name\":\"2016 Eighth International Conference on Ubiquitous and Future Networks (ICUFN)\",\"volume\":\"66 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-07-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 Eighth International Conference on Ubiquitous and Future Networks (ICUFN)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICUFN.2016.7536939\",\"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 Eighth International Conference on Ubiquitous and Future Networks (ICUFN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICUFN.2016.7536939","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Feature transformation and Mutual Information for DNS tunneling analysis
Tunneling attacks are executed to bypass security policies or leak sensitive data outside of a network. In this paper, we propose an innovative algorithm to profile DNS tunnels. Our approach combines Principal Component Analysis and Mutual Information. The proposed algorithm is validated on a live network. Results show that, under specific conditions, anomalies are correctly characterized through the proposed method. Other cases require instead further investigation.