嵌入式系统运行时入侵检测的分层框架

Muhamed Fauzi Bin Abbas, Alok Prakash, T. Srikanthan
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引用次数: 0

摘要

现有的入侵检测系统通常依靠一个或几个特征来检测系统中的异常或入侵。它们成功检测入侵的能力在很大程度上取决于这些有限的功能,这些功能通常不能提供全面的运行时检测,特别是在关键系统中使用的大量嵌入式设备中。为了克服现有入侵检测系统的这一局限性,本文提出了一种可在资源受限的嵌入式系统上实现的轻量级运行时分层多模态入侵检测框架。这项工作依赖于各种功能,如功率跟踪、系统调用(SYSCALL)跟踪和硬件性能计数器(HPC),通过利用各个功能的优势并将它们智能地组合起来,以克服它们各自的局限性。通过大量的案例研究,所提出的框架已被证明能够在运行时可靠地检测不同类型的入侵,同时仍然足够轻量级,可以部署在资源受限的嵌入式系统中。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Hierarchical Framework for Runtime Intrusion Detection in Embedded Systems
Existing intrusion detection systems typically rely on one or a few features to detect anomalies or intrusion in a system. Their ability to successfully detect intrusion largely hinges on these limited features, which often do not provide for a comprehensive and runtime detection, especially necessitated in multitude of embedded devices used in critical systems. To overcome this limitation of existing intrusion detection systems, this paper proposes a lightweight runtime hierarchical multimodal intrusion detection framework that can be realized on resource-constrained embedded systems. This work relies on various features such as power trace, System Call (SYSCALL) trace and Hardware Performance Counter (HPC) by leveraging the strengths of the individual features and combining them intelligently to overcome their individual limitations. Using a number of case studies, the proposed framework has been shown to reliably detect intrusion of different types at runtime, while still being sufficiently lightweight to be deployed in resource- constrained embedded systems.
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