基于深度学习的IDS可信安全模型

K. Makdi, Frederick T. Sheldon, A. A. Hussein
{"title":"基于深度学习的IDS可信安全模型","authors":"K. Makdi, Frederick T. Sheldon, A. A. Hussein","doi":"10.1109/ICSPIS51252.2020.9340136","DOIUrl":null,"url":null,"abstract":"Contemporarily, cloud computing is becoming the most preferred choice for IT firms because it offers flexibility and pay-per-use services. Nonetheless, privacy and security issues are significant challenges in the successful deployment of cloud computing attributed to its distributed and open architectures that are exposed to intrusions. The open and distributed structures of cloud computing are increasingly appealing to potential cybercriminals. Conventional intrusion detection systems are largely ineffective in the cloud computing environment because of their openness. This paper examines the deployment of novel intrusion detection systems involving a trust-based adaptive security model for intrusion detection through deep learning.","PeriodicalId":373750,"journal":{"name":"2020 3rd International Conference on Signal Processing and Information Security (ICSPIS)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Trusted Security Model for IDS Using Deep Learning\",\"authors\":\"K. Makdi, Frederick T. Sheldon, A. A. Hussein\",\"doi\":\"10.1109/ICSPIS51252.2020.9340136\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Contemporarily, cloud computing is becoming the most preferred choice for IT firms because it offers flexibility and pay-per-use services. Nonetheless, privacy and security issues are significant challenges in the successful deployment of cloud computing attributed to its distributed and open architectures that are exposed to intrusions. The open and distributed structures of cloud computing are increasingly appealing to potential cybercriminals. Conventional intrusion detection systems are largely ineffective in the cloud computing environment because of their openness. This paper examines the deployment of novel intrusion detection systems involving a trust-based adaptive security model for intrusion detection through deep learning.\",\"PeriodicalId\":373750,\"journal\":{\"name\":\"2020 3rd International Conference on Signal Processing and Information Security (ICSPIS)\",\"volume\":\"53 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-11-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 3rd International Conference on Signal Processing and Information Security (ICSPIS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSPIS51252.2020.9340136\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 3rd International Conference on Signal Processing and Information Security (ICSPIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSPIS51252.2020.9340136","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

摘要

目前,云计算正成为IT公司的首选,因为它提供了灵活性和按使用付费的服务。尽管如此,隐私和安全问题是成功部署云计算的重大挑战,因为云计算的分布式和开放架构容易受到入侵。云计算的开放和分布式结构对潜在的网络罪犯越来越有吸引力。传统的入侵检测系统由于其开放性,在云计算环境下大多是无效的。本文研究了新型入侵检测系统的部署,其中包括基于信任的自适应安全模型,通过深度学习进行入侵检测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Trusted Security Model for IDS Using Deep Learning
Contemporarily, cloud computing is becoming the most preferred choice for IT firms because it offers flexibility and pay-per-use services. Nonetheless, privacy and security issues are significant challenges in the successful deployment of cloud computing attributed to its distributed and open architectures that are exposed to intrusions. The open and distributed structures of cloud computing are increasingly appealing to potential cybercriminals. Conventional intrusion detection systems are largely ineffective in the cloud computing environment because of their openness. This paper examines the deployment of novel intrusion detection systems involving a trust-based adaptive security model for intrusion detection through deep learning.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信