Unsupervised Anomaly Detection Using Bidirectional GRU Autoencoder Neural Network for PLOAM Message Sequence Analysis in GPON

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F22%3APU146405" target="_blank" >RIV/00216305:26220/22:PU146405 - isvavai.cz</a>
Alternative codes found
RIV/63839172:_____/22:10133475
Result on the web
<a href="https://ieeexplore.ieee.org/document/9988508" target="_blank" >https://ieeexplore.ieee.org/document/9988508</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ICECCME55909.2022.9988508" target="_blank" >10.1109/ICECCME55909.2022.9988508</a>

Result language
angličtina
Original language name
Unsupervised Anomaly Detection Using Bidirectional GRU Autoencoder Neural Network for PLOAM Message Sequence Analysis in GPON
Original language description
This paper proposes an autoencoder neural network based on bidirectional gated recurrent unit layers used for anomaly detection in sequences of management protocol messages in gigabit-capable passive optical networks (GPONs). The autoencoder uses unsupervised learning, and the learning dataset is acquired from the real GPON network using a custom-made analyzer. The anomaly detection focuses on deviations in the management protocol in comparison to the baseline. It may indicate changes in the protocol itself caused by a different protocol implementation or a potential attack on the network. The capabilities of a trained autoencoder are evaluated on a generated dataset with various types of anomalies. The autoencoder reaches an average accuracy of 66% across all types of generated anomalies. However, the detection accuracy of sequences containing a high amount of random noise is 100%.
Czech name
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Czech description
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Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
S - Specificky vyzkum na vysokych skolach

Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
2022 International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME 2022)
ISBN
978-1-6654-7095-7
ISSN
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e-ISSN
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Number of pages
5
Pages from-to
1-5
Publisher name
Institute of Electrical and Electronics Engineers (IEEE)
Place of publication
Malé, Maldives
Event location
Male
Event date
Nov 16, 2022
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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