{"title":"Unwanted traffic characterization on IP networks by low interactive honeypot","authors":"Alisson Puska, M. N. Lima, A. Santos","doi":"10.1109/CNSM.2014.7014175","DOIUrl":null,"url":null,"abstract":"The increasing amount of unwanted traffic on the Internet consumes the available bandwidth on any network connected to it. Despite efforts to address this issue, it is still a challenge to differentiate unwanted traffic. Due to lack of knowledge or investment, organizations fail to implement security policies, such as BCP 38, which helps blocking the flow of unwanted data. This paper presents a method based on lowinteraction honeypots and network telescopes for identification and classification of unwanted traffic on IP networks. Our method aims to be simple and support low cost of deployment. An evaluation employed traces of real environments to show the method effectiveness. Results offer useful information about unwanted traffic, reaching a private network in a simple manner and with the reduced cost to block it.","PeriodicalId":268334,"journal":{"name":"10th International Conference on Network and Service Management (CNSM) and Workshop","volume":"36 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"10th International Conference on Network and Service Management (CNSM) and Workshop","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CNSM.2014.7014175","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
The increasing amount of unwanted traffic on the Internet consumes the available bandwidth on any network connected to it. Despite efforts to address this issue, it is still a challenge to differentiate unwanted traffic. Due to lack of knowledge or investment, organizations fail to implement security policies, such as BCP 38, which helps blocking the flow of unwanted data. This paper presents a method based on lowinteraction honeypots and network telescopes for identification and classification of unwanted traffic on IP networks. Our method aims to be simple and support low cost of deployment. An evaluation employed traces of real environments to show the method effectiveness. Results offer useful information about unwanted traffic, reaching a private network in a simple manner and with the reduced cost to block it.