Anticipating Advanced Persistent Threat (APT) countermeasures using collaborative security mechanisms

Natasha Arjumand Shoaib Mirza, Haider Abbas, F. A. Khan, J. Al-Muhtadi
{"title":"Anticipating Advanced Persistent Threat (APT) countermeasures using collaborative security mechanisms","authors":"Natasha Arjumand Shoaib Mirza, Haider Abbas, F. A. Khan, J. Al-Muhtadi","doi":"10.1109/ISBAST.2014.7013108","DOIUrl":null,"url":null,"abstract":"Information and communication security has gained significant importance due to its wide spread use, increased sophistication and complexity in its deployment. On the other hand, more sophisticated and stealthy techniques are being practiced by the intruder's group to penetrate and exploit the technology and attack detection. One such treacherous threat to all critical assets of an organization is Advanced Persistent Threat (APT). Since APT attack vector is not previously known, consequently this can harm the organization's assets before the patch for this security flaw is released/available. This paper presents a preliminary research effort to counter the APT or zero day attacks at an early stage by detecting malwares. Open Source version of Security Information and Event Management (SIEM) is used to detect denial of service attack launched through remote desktop service. The framework presented in this paper also shows the efficiency of the technique and it can be enhanced with more sophisticated mechanisms for APT attack detection.","PeriodicalId":292333,"journal":{"name":"2014 International Symposium on Biometrics and Security Technologies (ISBAST)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"23","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 International Symposium on Biometrics and Security Technologies (ISBAST)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISBAST.2014.7013108","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 23

Abstract

Information and communication security has gained significant importance due to its wide spread use, increased sophistication and complexity in its deployment. On the other hand, more sophisticated and stealthy techniques are being practiced by the intruder's group to penetrate and exploit the technology and attack detection. One such treacherous threat to all critical assets of an organization is Advanced Persistent Threat (APT). Since APT attack vector is not previously known, consequently this can harm the organization's assets before the patch for this security flaw is released/available. This paper presents a preliminary research effort to counter the APT or zero day attacks at an early stage by detecting malwares. Open Source version of Security Information and Event Management (SIEM) is used to detect denial of service attack launched through remote desktop service. The framework presented in this paper also shows the efficiency of the technique and it can be enhanced with more sophisticated mechanisms for APT attack detection.
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
使用协作安全机制预测高级持续性威胁(APT)对策
信息和通信安全由于其广泛的使用,其部署的复杂性和复杂性日益增加而变得非常重要。另一方面,入侵者组织正在使用更复杂和隐蔽的技术来渗透和利用技术和攻击检测。高级持续威胁(APT)是对组织所有关键资产的一种危险威胁。由于以前不知道APT攻击向量,因此在此安全漏洞的补丁发布/可用之前,这可能会损害组织的资产。本文介绍了通过检测恶意软件在早期阶段对抗APT或零日攻击的初步研究工作。SIEM (Security Information and Event Management)是开源版本,用于检测通过远程桌面服务发起的拒绝服务攻击。本文提出的框架也显示了该技术的效率,并且可以通过更复杂的APT攻击检测机制来增强它。
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
Improved skin detection based on dynamic threshold using multi-colour space Signature-Based Anomaly intrusion detection using Integrated data mining classifiers Distributed Denial of Service detection using hybrid machine learning technique Survey of anti-phishing tools with detection capabilities Effective mining on large databases for intrusion detection
×
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