Detection and Control of Credit Card Fraud Attacks in Sliding Window with Exponential Forgetting
Artikel i vetenskaplig tidskrift, 2025

Credit card fraud causes significant financial losses and frequently occurs as fraud attack, defined as short-term sequence of fraudulent transactions associated with high transaction rates and amounts, business areas historically tied to fraud, unusual transaction times and locations and different types of errors.

Confidence interval method in the moving window with exponential forgetting is proposed in this paper which allows to capture recent changes in the shopping behaviour of the cardholder, detect fraudulent amounts and mitigate the attack. Fraud risk scoring method is used for estimation of the intensity of the fraudulent activity via monitoring of the transaction rates, merchant category codes, times and some other factors for detection of the start of the attack.

The development and verification are based on detailed analysis of the transaction patterns from the dataset, which represents an extensive collection of around 24.4 million credit card transactions from IBM financial database. Recommendations for further development of the detection techniques are also presented.

fraud risk scoring

detection & control in moving window with exponential forgetting

monitoring of intensity of fraudulent activity

time series analysis

credit card fraud attacks

mitigation of fraud attack

Författare

Alexander Stotsky

Chalmers, Data- och informationsteknik, Interaktionsdesign och Software Engineering

International Journal of Computers and Applications

1206-212X (ISSN)

Vol. 186 74 0795-8887

Styrkeområden

Informations- och kommunikationsteknik

Ämneskategorier (SSIF 2025)

Systemvetenskap, informationssystem och informatik

Artificiell intelligens

DOI

10.5120/ijca2025924619

Mer information

Senast uppdaterat

2025-04-04