David Brosset, Camille Cavelier, Benjamin Costé, Y. Kermarrec, Joffrey Lartigaud, Pedro Merino Laso
{"title":"Cr@ck3n: A cyber alerts visualization object","authors":"David Brosset, Camille Cavelier, Benjamin Costé, Y. Kermarrec, Joffrey Lartigaud, Pedro Merino Laso","doi":"10.1109/CyberSA.2017.8073401","DOIUrl":null,"url":null,"abstract":"With the increasing number of connected devices and given the complexity of computer networks, to identify cyber anomalies is more and more challenging. Either at home, in the work place or for military defense purposes a better cyber situation awareness is needed. However, the visualization methods are often made for specialists and the information difficult to interpret. In this paper we describe an object made for the visualization of abnormal network events in a user-friendly way using colors, sound and information scrolling. It is still under development but the first user feedback are encouraging.","PeriodicalId":365296,"journal":{"name":"2017 International Conference On Cyber Situational Awareness, Data Analytics And Assessment (Cyber SA)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Conference On Cyber Situational Awareness, Data Analytics And Assessment (Cyber SA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CyberSA.2017.8073401","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
With the increasing number of connected devices and given the complexity of computer networks, to identify cyber anomalies is more and more challenging. Either at home, in the work place or for military defense purposes a better cyber situation awareness is needed. However, the visualization methods are often made for specialists and the information difficult to interpret. In this paper we describe an object made for the visualization of abnormal network events in a user-friendly way using colors, sound and information scrolling. It is still under development but the first user feedback are encouraging.