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September 5, 2025Applied SciencesOpen Access

Enhancing Security in Airline Ticket Transactions: A Comparative Study of SVM and LightGBM

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This comparative study evaluates LightGBM and SVM for fraud detection in airline transactions, suggesting advanced methods enhance security.

LightGBM achieved an overall accuracy of 94.2%, significantly outperforming SVMs in fraud detection.
The synthetic dataset included realistic user and transaction attributes to evaluate both models' performance.
A modular feature engineering framework was designed to facilitate adaptable fraud detection in the airline sector.
Findings suggest that advanced machine learning techniques can notably improve security for online payment operations.

Arnaldo et al. (2025) studied this question.

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This comparative study evaluates LightGBM and SVM for fraud detection in airline transactions, suggesting advanced methods enhance security.