Fog Computing: Mitigating Insider Data Theft Attacks in the Cloud

S. Stolfo, M. B. Salem, A. Keromytis
{"title":"Fog Computing: Mitigating Insider Data Theft Attacks in the Cloud","authors":"S. Stolfo, M. B. Salem, A. Keromytis","doi":"10.1109/SPW.2012.19","DOIUrl":null,"url":null,"abstract":"Cloud computing promises to significantly change the way we use computers and access and store our personal and business information. With these new computing and communications paradigms arise new data security challenges. Existing data protection mechanisms such as encryption have failed in preventing data theft attacks, especially those perpetrated by an insider to the cloud provider. We propose a different approach for securing data in the cloud using offensive decoy technology. We monitor data access in the cloud and detect abnormal data access patterns. When unauthorized access is suspected and then verified using challenge questions, we launch a disinformation attack by returning large amounts of decoy information to the attacker. This protects against the misuse of the user's real data. Experiments conducted in a local file setting provide evidence that this approach may provide unprecedented levels of user data security in a Cloud environment.","PeriodicalId":201519,"journal":{"name":"2012 IEEE Symposium on Security and Privacy Workshops","volume":"40 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"288","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE Symposium on Security and Privacy Workshops","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SPW.2012.19","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 288

Abstract

Cloud computing promises to significantly change the way we use computers and access and store our personal and business information. With these new computing and communications paradigms arise new data security challenges. Existing data protection mechanisms such as encryption have failed in preventing data theft attacks, especially those perpetrated by an insider to the cloud provider. We propose a different approach for securing data in the cloud using offensive decoy technology. We monitor data access in the cloud and detect abnormal data access patterns. When unauthorized access is suspected and then verified using challenge questions, we launch a disinformation attack by returning large amounts of decoy information to the attacker. This protects against the misuse of the user's real data. Experiments conducted in a local file setting provide evidence that this approach may provide unprecedented levels of user data security in a Cloud environment.
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
雾计算:减少云中的内部数据盗窃攻击
云计算承诺将显著改变我们使用计算机以及访问和存储个人和商业信息的方式。随着这些新的计算和通信范式的出现,出现了新的数据安全挑战。加密等现有数据保护机制无法防止数据盗窃攻击,尤其是由云提供商内部人员实施的攻击。我们提出了一种使用进攻性诱饵技术来保护云中的数据的不同方法。我们监控云中的数据访问并检测异常的数据访问模式。当怀疑未经授权的访问并使用挑战问题进行验证时,我们通过向攻击者返回大量诱饵信息来发起虚假信息攻击。这可以防止滥用用户的真实数据。在本地文件设置中进行的实验证明,这种方法可以在云环境中提供前所未有的用户数据安全级别。
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
Insider Threats against Trust Mechanism with Watchdog and Defending Approaches in Wireless Sensor Networks Using Consensus Clustering for Multi-view Anomaly Detection Side-Channel Analysis of Grøstl and Skein Fog Computing: Mitigating Insider Data Theft Attacks in the Cloud Slender PUF Protocol: A Lightweight, Robust, and Secure Authentication by Substring Matching
×
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