Electronic consumption vouchers fraud detection of city Y based on improved LSTM-AE structure

Mozhou He; Yi Guo; Kewei Zeng; Shishun Xia

doi:10.1117/12.3051182

20 January 2025 Electronic consumption vouchers fraud detection of city Y based on improved LSTM-AE structure

Mozhou He, Yi Guo, Kewei Zeng, Shishun Xia

Author Affiliations +

Proceedings Volume 13422, Fourth International Conference on Intelligent Traffic Systems and Smart City (ITSSC 2024); 1342227 (2025) https://doi.org/10.1117/12.3051182
Event: Fourth International Conference on Intelligent Traffic Systems and Smart City (ITSSC 2024), 2024, Xi'an, China

Abstract

In response to the post-COVID-19 economic recession, City Y, as part of its smart city initiatives, issued electronic consumption vouchers (ECVs) to boost the market economy. However, some individuals exploited these vouchers, affecting their fairness and effectiveness. Thus, this paper presents an unsupervised deep learning framework to detect fraudulent merchants and anomalies in voucher redemptions. We use Long Short-Term Memory (LSTM) units combined with an autoencoder (AE) to learn long-term dependencies in time series data. A smoothing unit is also used to reduce prediction bias. The fraud scoring module assesses merchants based on the ratio of anomalous redemptions to total redemptions. Our experimental results show that this approach significantly improves fraud detection accuracy and efficiency, making it a promising tool for maintaining the fairness and effectiveness of ECVs within the smart city ecosystem.

(2025) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Mozhou He, Yi Guo, Kewei Zeng, and Shishun Xia "Electronic consumption vouchers fraud detection of city Y based on improved LSTM-AE structure", Proc. SPIE 13422, Fourth International Conference on Intelligent Traffic Systems and Smart City (ITSSC 2024), 1342227 (20 January 2025); https://doi.org/10.1117/12.3051182

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