Validating an Insider Threat Detection System: A Real Scenario Perspective

Ioannis Agrafiotis, Arnau Erola, J. Happa, M. Goldsmith, S. Creese
{"title":"Validating an Insider Threat Detection System: A Real Scenario Perspective","authors":"Ioannis Agrafiotis, Arnau Erola, J. Happa, M. Goldsmith, S. Creese","doi":"10.1109/SPW.2016.36","DOIUrl":null,"url":null,"abstract":"There exists unequivocal evidence denoting the dire consequences which organisations and governmental institutions face from insider threats. While the in-depth knowledge of the modus operandi that insiders possess provides ground for more sophisticated attacks, organisations are ill-equipped to detect and prevent these from happening. The research community has provided various models and detection systems to address the problem, but the lack of real data due to privacy and ethical issues remains a significant obstacle for validating and designing effective and scalable systems. In this paper, we present the results and our experiences from applying our detection system into a multinational organisation, the approach followed to abide with the ethical and privacy considerations and the lessons learnt on how the validation process refined the system in terms of effectiveness and scalability.","PeriodicalId":341207,"journal":{"name":"2016 IEEE Security and Privacy Workshops (SPW)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE Security and Privacy Workshops (SPW)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SPW.2016.36","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 15

Abstract

There exists unequivocal evidence denoting the dire consequences which organisations and governmental institutions face from insider threats. While the in-depth knowledge of the modus operandi that insiders possess provides ground for more sophisticated attacks, organisations are ill-equipped to detect and prevent these from happening. The research community has provided various models and detection systems to address the problem, but the lack of real data due to privacy and ethical issues remains a significant obstacle for validating and designing effective and scalable systems. In this paper, we present the results and our experiences from applying our detection system into a multinational organisation, the approach followed to abide with the ethical and privacy considerations and the lessons learnt on how the validation process refined the system in terms of effectiveness and scalability.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
验证内部威胁检测系统:一个真实的场景视角
有明确的证据表明,组织和政府机构面临着来自内部威胁的可怕后果。虽然内部人员对作案手法的深入了解为更复杂的攻击提供了基础,但组织在检测和防止这些攻击发生方面装备不足。研究界已经提供了各种模型和检测系统来解决这个问题,但是由于隐私和伦理问题而缺乏真实数据仍然是验证和设计有效和可扩展系统的重大障碍。在本文中,我们介绍了将我们的检测系统应用于跨国组织的结果和经验,遵循遵守道德和隐私考虑的方法,以及验证过程如何在有效性和可扩展性方面改进系统的经验教训。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
A Semi-Automated Methodology for Extracting Access Control Rules from the European Data Protection Directive A Critical Analysis of Privacy Design Strategies At Your Fingertips: Considering Finger Distinctness in Continuous Touch-Based Authentication for Mobile Devices Investigating Airplane Safety and Security Against Insider Threats Using Logical Modeling A Model-Based Approach to Predicting the Performance of Insider Threat Detection Systems
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1