大型IT基础设施中基于网络的恶意软件检测方法

B. Kumar, C. Katsinis
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引用次数: 2

摘要

恶意软件是具有恶意意图的代码,用于窃取机密数据或获取系统的根权限等恶意目的。目前处理病毒和间谍软件等恶意软件威胁的方法是使用基于主机的反恶意软件。然而,这种方法导致许多易受攻击的机器,因为许多用户不更新他们的软件,他们的病毒签名,有些甚至禁用他们的软件,以避免这些软件造成的系统性能下降。基于主机的安全软件需要大量的管理工作,对重新配置、管理和报告分析都有一致的需求。随着安全管理员支持越来越多的用户,这种方法变得不切实际。在本文中,我们提出了一种新的基于网络的恶意软件检测架构,该架构使用主机安全向量来保护主机,而不需要主机的任何干预。这种体系结构提供了另一层安全性,可以补充现有的基于主机的解决方案。只有中央检测服务器需要主动管理,而不是单独的主机——因此为大型IT基础设施提供了更易于管理的解决方案。
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A Network Based Approach to Malware Detection in Large IT Infrastructures
Malware is code that has malicious intent and is designed for malicious purpose such as stealing confidential data, or obtaining root privileges on a system. The current approach to deal with malware threats such as virus and spyware is to use host based anti-malware software. However, this approach leads to many vulnerable machines since many users don't update their software, their virus signatures, and some even disable their software to avoid the system performance degradation caused by these software. Host based security software require a good deal of administration, with consistent needs for reconfiguration, management, and report analysis. With security administrators supporting an ever growing number of users, such an approach has become impractical. In this paper, we present a novel network based malware detection architecture that uses host security vectors to protect host machines without any intervention from hosts. This architecture provides another layer of security and can complement existing host based solutions. Only central detection server needs to be actively managed instead of individual hosts - hence providing more manageable solution for large IT infrastructures.
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