Open AccessResearch on Anomaly Detection Algorithms for Financial Data Based on Angle
Author(s) -
Yuanyuan Hong
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1345/6/062038
Subject(s) - anomaly detection , anomaly (physics) , computer science , transaction data , database transaction , computation , data mining , algorithm , database , physics , condensed matter physics
With the emergence of more and more massive data, under the background of large data, the existing angle-based anomaly detection algorithms have the problem of too much computation. Based on this, this paper improves the angle-based anomaly detection method, and proposes an angle-based anomaly detection method based on Data Center for anomaly detection of large amount of network financial transaction data. By establishing data update mechanism for different data sets, real-time data detection can be carried out.