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Analysis of institutional authors

Arnaldo, César GómezCorresponding AuthorJurado, Raquel Delgado-AguileraAuthorMoreno, Francisco PérezAuthorSuárez, María ZamarreñoAuthor

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September 22, 2025
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Enhancing Security in Airline Ticket Transactions: A Comparative Study of SVM and LightGBM

Publicated to: Applied Sciences-Basel. 15 (17): 9581- - 2025-08-30 15(17), DOI: 10.3390/app15179581

Authors:

Arnaldo, Cesar Gomez; Jurado, Raquel Delgado-Aguilera; Moreno, Francisco Perez; Suarez, Maria Zamarreno
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Affiliations

Univ Politecn Madrid UPM, Dept Aerosp Syst Air Transport & Airports, Madrid 28040, Spain - Author

Abstract

Fraudulent online payment operations represent a persistent challenge in digital commerce, particularly in sectors like air travel, where credit and debit card payments dominate. This study presents a novel fraud detection framework tailored to airline ticket purchases, combining a synthetic dataset generator with a modular, customizable feature engineering process. These are two machine learning models-support vector machines (SVMs) and the light gradient boosting machine (LightGBM)-for real-time fraud detection. A synthetic dataset was generated, including a rich set of engineered features reflecting realistic user, transaction, and flight-related attributes. While both models were evaluated using classification-evaluation metrics, LightGBM outperformed SVMs in terms of overall performance with an accuracy of 94.2% and a recall of 71.3% for fraudulent cases. The main contribution of this study is the design of a reusable, customizable feature engineering framework for fraud detection in the airline sector, along with the development of a lightweight, adaptable fraud detection system for merchants, especially small and medium-sized enterprises. These findings support the use of advanced machine learning methods to enhance security in digital airline transactions.
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Keywords

Air transportationAirline ticketsClassificationClassification (of information)Computer software reusabilityCredit cardsCrimeCustomizableElectronic moneyFeature engineeringFeature engineeringsFeature extractionFraud detectionFraud preventionGradient boostingLearning systemsLight gradientsSupport vector machinesSupport vectors machineSynthetic datasets

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal Applied Sciences-Basel due to its progression and the good impact it has achieved in recent years, according to the agency WoS (JCR), it has become a reference in its field. In the year of publication of the work, 2025, it was in position 50/179, thus managing to position itself as a Q2 (Segundo Cuartil), in the category Engineering, Multidisciplinary. Notably, the journal is positioned en el Cuartil Q2 para la agencia Scopus (SJR) en la categoría Engineering (Miscellaneous).

Independientemente del impacto esperado determinado por el canal de difusión, es importante destacar el impacto real observado de la propia aportación.

Según las diferentes agencias de indexación, el número de citas acumuladas por esta publicación hasta la fecha 2026-04-01:

  • WoS: 1
  • Scopus: 1
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Impact and social visibility

From the perspective of influence or social adoption, and based on metrics associated with mentions and interactions provided by agencies specializing in calculating the so-called "Alternative or Social Metrics," we can highlight as of 2026-04-01:

  • The use, from an academic perspective evidenced by the Altmetric agency indicator referring to aggregations made by the personal bibliographic manager Mendeley, gives us a total of: 4.
  • The use of this contribution in bookmarks, code forks, additions to favorite lists for recurrent reading, as well as general views, indicates that someone is using the publication as a basis for their current work. This may be a notable indicator of future more formal and academic citations. This claim is supported by the result of the "Capture" indicator, which yields a total of: 4 (PlumX).

With a more dissemination-oriented intent and targeting more general audiences, we can observe other more global scores such as:

  • The Total Score from Altmetric: 1.

It is essential to present evidence supporting full alignment with institutional principles and guidelines on Open Science and the Conservation and Dissemination of Intellectual Heritage. A clear example of this is:

  • The work has been submitted to a journal whose editorial policy allows open Open Access publication.
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Leadership analysis of institutional authors

There is a significant leadership presence as some of the institution’s authors appear as the first or last signer, detailed as follows: First Author (GOMEZ ARNALDO, CESAR) and Last Author (ZAMARREÑO SUÁREZ, MARÍA).

the author responsible for correspondence tasks has been GOMEZ ARNALDO, CESAR.

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