Pre-processing techniques for anomaly detection in telecommunication networks

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dc.contributor Aalto-yliopisto fi
dc.contributor Aalto University en
dc.contributor.advisor Hätönen, Kimmo
dc.contributor.author Babujee Jerome, Robin
dc.date.accessioned 2015-05-27T08:01:55Z
dc.date.available 2015-05-27T08:01:55Z
dc.date.issued 2015-05-11
dc.identifier.uri https://aaltodoc.aalto.fi/handle/123456789/16240
dc.description.abstract Anomalies in telecommunication networks can be signs of errors or malfunctions, which can originate from a wide variety of reasons. Huge amount of data collected from network elements in the form of counters, server logs, audit trail logs etc. can provide significant information about the normal state of the system as well as possible anomalies. Unsupervised methods like ‘Self-Organizing Maps’ (SOM) are often chosen for anomaly detection. They are useful for analyzing and categorizing high volume, high dimensional data. One of the major issues with using SOMs or other unsupervised methods for analyzing anomalies in Telecommunication Management Networks is that they are highly sensitive to pre-treatment of data. The main objective of this thesis is to identify the right kind of pre-processing steps that can be applied to real mobile network traffic data measurements, so that the most interesting anomalies get detected in the anomaly detection stage. Two methods of evaluating the effectiveness of an anomaly detection technique for telecom network measurement data are also proposed. en
dc.format.extent 88 + 11
dc.format.mimetype application/pdf en
dc.language.iso en en
dc.title Pre-processing techniques for anomaly detection in telecommunication networks en
dc.type G2 Pro gradu, diplomityö en
dc.contributor.school Sähkötekniikan korkeakoulu fi
dc.subject.keyword anomaly detection en
dc.subject.keyword pre-processing en
dc.subject.keyword self-organizing maps en
dc.subject.keyword telecom network management en
dc.subject.keyword quality of anomalies en
dc.subject.keyword outlier detection en
dc.identifier.urn URN:NBN:fi:aalto-201505272907
dc.programme.major Networking Technology fi
dc.programme.mcode S3029 fi
dc.type.ontasot Master's thesis en
dc.type.ontasot Diplomityö fi
dc.contributor.supervisor Asokan, N
dc.programme TLT - Master’s Programme in Communications Engineering fi
dc.location P1 fi


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