基于代数方法的云计算中基于信任的入侵检测

Amira Bradai, H. Afifi
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引用次数: 11

摘要

提出了一种基于信任的混合云入侵检测方案。我们考虑了一个基于诚实、合作和效率的信任度量来检测恶意机器。我们使用Perron-Frobenius定理来检测基于信任和观察的入侵。通过统计分析对信任分布结果,应用门户采用基于信任的入侵检测来评估系统的可信度和恶意程度。建立了性能分析模型并进行了仿真。我们根据最小信任阈值分析假警报的敏感性,低于该阈值的节点被认为是恶意的。结果证实,我们的建议是足够灵活的检测恶意行为考虑各种参数。这项工作可以指导未来在云资源中的执行。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Enforcing Trust-Based Intrusion Detection in Cloud Computing Using Algebraic Methods
A trust-based intrusion detection scheme for hybrid cloud computing is proposed. We consider a trust metric based on honesty, cooperation and efficiency for detecting malicious machines. We use Perron-Frobenius theorem to detect intrusion based on trust and observations. By statistically analyzing pair trust distributed results, the portal of the application applies trust-based intrusion detection to assess the trustworthiness and maliciousness. An analytical model and simulation for performance are developed. We analyze the sensitivity of false alarms with respect to the minimum trust threshold below which a node is considered malicious. Results confirm that our proposal is flexible enough to detect malicious behaviours considering various parameters. This work can guide future execution in the cloud resource.
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