{"title":"An exploration of user recognition on domestic networks using NetFlow records","authors":"Anthony Brown, R. Mortier, T. Rodden","doi":"10.1145/2638728.2641560","DOIUrl":null,"url":null,"abstract":"In this paper, we describe HomeNetViewer, a system for collecting, visualising and annotating domestic network NetFlow records from a domestic network gateway. HomeNetViewer is designed to collect ground truth data which, enables the linking of users to low level network traffic. We present our first annotated dataset from a real household in the UK and the results of our preliminary work to build a user identification system. Our initial classifier achieves a true-positive rate of 64% with false-positive rate of 28% when compared to the ground truth annotations. This work attempts to address the lack of transparency and accountability within the domestic network infrastructure by identifying the user behind the device.","PeriodicalId":20496,"journal":{"name":"Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct Publication","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2014-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct Publication","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2638728.2641560","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
Abstract
In this paper, we describe HomeNetViewer, a system for collecting, visualising and annotating domestic network NetFlow records from a domestic network gateway. HomeNetViewer is designed to collect ground truth data which, enables the linking of users to low level network traffic. We present our first annotated dataset from a real household in the UK and the results of our preliminary work to build a user identification system. Our initial classifier achieves a true-positive rate of 64% with false-positive rate of 28% when compared to the ground truth annotations. This work attempts to address the lack of transparency and accountability within the domestic network infrastructure by identifying the user behind the device.