IaaS云中的异常检测

Frank Dölitzscher, M. Knahl, C. Reich, N. Clarke
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引用次数: 33

摘要

安全性仍然是云计算中的一个主要问题,特别是检测恶意使用或滥用云实例。其中一个原因是底层系统设计和体系结构的复杂性和动态性不断增长。为了能够检测对云实例的滥用,这项工作提出了一个用于基础设施即服务云的异常检测系统。它是基于云客户的使用行为分析。神经网络用于分析和学习云客户的正常使用行为,然后检测可能源于由虚拟机超载引起的云安全事件的异常情况。它提高了云客户对其云实例安全性的透明度,并支持云提供商检测对其基础设施的滥用。给出了一个仿真环境和异常检测原型。实验验证了该系统的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Anomaly Detection in IaaS Clouds
Security is still a major concern in Cloud computing, especially the detection of nefarious use or abuse of cloud instances. One reason for this, is the ever-growing complexity and dynamic of the underlying system design and architecture. To be able to detect misuse of cloud instances, this work presents an anomaly detection system for Infrastructure as a Service Clouds. It is based on Cloud customers' usage behaviour analysis. Neural networks are used to analyse and learn the normal usage behaviour of Cloud customers, to then detect anomalies which could originate from a cloud security incident caused by an overtaken virtual machine. It increases transparency for Cloud customers about the security of their Cloud instances and supports the Cloud provider to detect misuse of their infrastructure. A simulation environment and an anomaly detection prototype get presented. Experiments validate the effectiveness of the proposed system.
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