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Multi-level Network Resilience: Traffic Analysis, Anomaly Detection and Simulation

机译:多级网络弹性:流量分析,异常检测和仿真

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摘要

Traffic analysis and anomaly detection have been extensively used to characterize network utilization as well as to identify abnormal network traffic such as malicious attacks. However, so far, techniques for traffic analysis and anomaly detection have been carried out independently, relying on mechanisms and algorithms either in edge or in core networks alone. In this paper we propose the notion of multi-level network resilience, in order to provide a more robust traffic analysis and anomaly detection architecture, combining mechanisms and algorithms operating in a coordinated fashion both in the edge and in the core networks. This work is motivated by the potential complementarities between the research being developed at IIT Madras and Lancaster University. In this paper we describe the current work being developed at IIT Madras and Lancaster on traffic analysis and anomaly detection, and outline the principles of a multi-level resilience architecture.
机译:流量分析和异常检测已广泛用于表征网络利用率以及识别异常网络流量,例如恶意攻击。但是,到目前为止,流量分析和异常检测技术是独立进行的,仅依赖于边缘网络或核心网络中的机制和算法。在本文中,我们提出了多级网络弹性的概念,以便提供更健壮的流量分析和异常检测体系结构,并结合在边缘和核心网络中以协调方式运行的机制和算法。 IIT Madras与兰开斯特大学之间正在开展的研究之间的潜在互补性促使了这项工作。在本文中,我们描述了IIT Madras和Lancaster在流量分析和异常检测方面正在开发的当前工作,并概述了多级弹性体系结构的原理。

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