A Mission-Impact-Based Approach to INFOSEC Alarm Correlation

2002 ◽  
pp. 95-114 ◽  
Author(s):  
Phillip A. Porras ◽  
Martin W. Fong ◽  
Alfonso Valdes
Keyword(s):  
Alarm Correlation

Discovering Alarm Correlation Rules for Network Fault Management

2021 ◽  
pp. 228-239
Author(s):  
Philippe Fournier-Viger ◽  
Ganghuan He ◽  
Min Zhou ◽  
Mourad Nouioua ◽  
Jiahong Liu
Keyword(s):  
Fault Management ◽  
Alarm Correlation ◽  
Correlation Rules ◽  
Network Fault

DIVIDE ET IMPERA – A HYBRID APPROACH TO ALARM CORRELATION FOR SDH NETWORKS

Networks ◽  
2002 ◽  
Author(s):  
RALF BAYER ◽  
GUIDO CARLS ◽  
BIRGIT FROHNHOFF
Keyword(s):  
Hybrid Approach ◽  
Alarm Correlation

A preliminary two-stage alarm correlation and filtering system using SOM neural network and K-means algorithm

2010 ◽  
Vol 29 (6) ◽  
pp. 712-723 ◽  
Author(s):  
Gina C. Tjhai ◽  
Steven M. Furnell ◽  
Maria Papadaki ◽  
Nathan L. Clarke
Keyword(s):  
Neural Network ◽  
Two Stage ◽  
Alarm Correlation ◽  
Som Neural Network

scholarly journals Alarm Correlation in Mobile Telecommunications Networks based on k-means Cluster Analysis Method

2018 ◽  
Vol 2 ◽  
pp. 95-102 ◽  
Author(s):  
Artur Mazdziarz
Keyword(s):  
Cluster Analysis ◽  
Network Management ◽  
New Technologies ◽  
Rapid Development ◽  
Geographical Area ◽  
Analysis Method ◽  
Mobile Telecommunications ◽  
Essential Information ◽  
Alarm Correlation ◽  
Cluster Analysis Method

Event correlation and root cause analysis play a fundamental role in the process of troubleshooting all technical faults and malfunctions. An in-depth, complicated multiprotocol analysis can be greatly supported or even replaced by a troubleshooting methodology based on data analysis approaches. The mobile telecommunications domain has been experiencing rapid development recently. Introduction of new technologies and services, as well as multivendor environment distributed across the same geographical area create a lot of challenges in network operation routines. Maintenance tasks have been recently becoming more and more complicated, time consuming and require big data analyses to be performed. Most network maintenance activities are completed manually by experts using raw network management information available in the network management system via multiple applications and direct database queries. With these circumstances considered, identification of network failures is a very difficult, if not an impossible task. This explains why effective yet simple tools and methods providing network operators with carefully selected, essential information are needed. Hence, in this paper efficient approximated alarm correlation algorithm based on the k-means cluster analysis method is proposed.

scholarly journals FAULT LOCALIZATION AND ALARM CORRELATION IN OPTICAL WDM NETWORKS

2010 ◽  
Vol 01 (02) ◽  
pp. 91-97
Author(s):  
Ramesh G ◽  
◽  
SundaraVadivelu S ◽  
Keyword(s):  
Fault Localization ◽  
Wdm Networks ◽  
Optical Wdm Networks ◽  
Optical Wdm ◽  
Alarm Correlation
Sign in / Sign up

Export Citation Format

Share Document