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Anomaly-detection and health-analysi...

Jin, Shi.

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Anomaly-detection and health-analysis techniques for core router systems

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Anomaly-detection and health-analysis techniques for core router systems/ by Shi Jin, Zhaobo Zhang, Krishnendu Chakrabarty, Xinli Gu.
作者:	Jin, Shi.
其他作者:	Zhang, Zhaobo.
出版者:	Cham :Springer international Publishing : : 2020.,
面頁冊數:	xiii, 148 p. :ill., digital ;24 cm.
內容註:	introduction -- Anomaly Detection Using Correlation-Based Time-Series Analysis -- Changepoint-based Anomaly Detection -- Hierarchical Symbol-based Health-Status Analysis -- Self-Learning Health-Status Analysis -- Conclusion.
Contained By:	Springer eBooks
標題:	Routing (Computer network management) -
電子資源:	https://doi.org/10.1007/978-3-030-33664-6
ISBN:	9783030336646

Anomaly-detection and health-analysis techniques for core router systems
Jin, Shi.

Anomaly-detection and health-analysis techniques for core router systems[electronic resource] /by Shi Jin, Zhaobo Zhang, Krishnendu Chakrabarty, Xinli Gu. - Cham :Springer international Publishing :2020. - xiii, 148 p. :ill., digital ;24 cm.

introduction -- Anomaly Detection Using Correlation-Based Time-Series Analysis -- Changepoint-based Anomaly Detection -- Hierarchical Symbol-based Health-Status Analysis -- Self-Learning Health-Status Analysis -- Conclusion.

This book tackles important problems of anomaly detection and health status analysis in complex core router systems, integral to today's internet Protocol (iP) networks. The techniques described provide the first comprehensive set of data-driven resiliency solutions for core router systems. The authors present an anomaly detector for core router systems using correlation-based time series analysis, which monitors a set of features of a complex core router system. They also describe the design of a changepoint-based anomaly detector such that anomaly detection can be adaptive to changes in the statistical features of data streams. The presentation also includes a symbol-based health status analyzer that first encodes, as a symbol sequence, the long-term complex time series collected from a number of core routers, and then utilizes the symbol sequence for health analysis. Finally, the authors describe an iterative, self-learning procedure for assessing the health status. Enables Accurate Anomaly Detection Using Correlation-Based Time-Series Analysis; Presents the design of a changepoint-based anomaly detector; includes Hierarchical Symbol-based Health-Status Analysis; Describes an iterative, self-learning procedure for assessing the health status.

ISBN: 9783030336646

Standard No.: 10.1007/978-3-030-33664-6doiSubjects--Topical Terms:

1002311
Routing (Computer network management)

LC Class. No.: TK5105.543 / .J567 2020

Dewey Class. No.: 004.665

Anomaly-detection and health-analysis techniques for core router systems
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