Geodesic
Deep learning method for identifying anomalies in operating computer systems
Itogi nauki i tehniki. Sovremennaâ matematika i eë priloženiâ. Tematičeskie obzory, Proceedings of the Voronezh international spring mathematical school "Modern methods of the theory of boundary-value problems. Pontryagin readings—XXXIV", Voronezh, May 3-9, 2023, Part 3, Tome 232 (2024), pp. 140-152

Voir la notice de l'article provenant de la source Math-Net.Ru

The problem of detecting anomalous behavior in large software systems can be reduced to the problem of detecting anomalies in text data streams. In this paper, we propose an approach based on a combination of deep learning (an autoencoder using convolutional neural networks and a single-layer fully connected decoder) and approaches based on the fuzzy clustering method. The solution proposed allows one to construct vector representations of groups of sequential events and identify outliers in the data using a developed layer based on fuzzy clustering and radial basis functions methods.
Keywords: anomaly detection, system log analysis, deep learning, neural networks 
@article{INTO_2024_232_a10,
     author = {O. E. Gorokhov and M. I. Petrovskii and I. V. Mashechkin},
     title = {Deep learning method for identifying anomalies in operating computer systems},
     journal = {Itogi nauki i tehniki. Sovremenna\^a matematika i e\"e prilo\v{z}eni\^a. Temati\v{c}eskie obzory},
     pages = {140--152},
     publisher = {mathdoc},
     volume = {232},
     year = {2024},
     language = {ru},
     url = {http://geodesic.mathdoc.fr/item/INTO_2024_232_a10/}
}
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O. E. Gorokhov; M. I. Petrovskii; I. V. Mashechkin. Deep learning method for identifying anomalies in operating computer systems. Itogi nauki i tehniki. Sovremennaâ matematika i eë priloženiâ. Tematičeskie obzory, Proceedings of the Voronezh international spring mathematical school "Modern methods of the theory of boundary-value problems. Pontryagin readings—XXXIV", Voronezh, May 3-9, 2023, Part 3, Tome 232 (2024), pp. 140-152. http://geodesic.mathdoc.fr/item/INTO_2024_232_a10/