Anomalies detection in social services data in the sphere of digital economy

This article addresses the study of the anomaly and fraud detection problem in the data from social services. The problem of detecting anomalies is extremely relevant for data-driven processes in the digital economy. In this paper, we propose a two-step approach for the detection of anomalies using...

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Bibliographic Details
Published inJournal of physics. Conference series Vol. 1368; no. 5; pp. 52045 - 52050
Main Authors Khripunov, P V, Minaev, E Y, Protsenko, V I, Davydov, N S, Nikonorov, A V
Format Journal Article
LanguageEnglish
Published Bristol IOP Publishing 01.11.2019
Subjects
Algorithms
Anomalies
Coders
Digital economy
Fraud
Physics
Social services
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Summary:This article addresses the study of the anomaly and fraud detection problem in the data from social services. The problem of detecting anomalies is extremely relevant for data-driven processes in the digital economy. In this paper, we propose a two-step approach for the detection of anomalies using auto-encoders and the conjugacy indicator. An experimental study of the efficiency of the proposed algorithms was conducted using open-access data set.
ISSN:1742-6588
1742-6596
DOI:10.1088/1742-6596/1368/5/052045