Temporal transaction scraping assisted point of compromise detection with autoencoder based feature engineering

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dc.contributor.authorOgme, Fuat
dc.contributor.authorYavuz, Ali Gökhan
dc.contributor.authorGüvensan, M. Amaç
dc.contributor.authorKarsligil, Mine Elif
dc.date.accessioned2024-04-19T12:24:38Z
dc.date.available2024-04-19T12:24:38Z
dc.date.issued2021
dc.departmentTAÜ, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümüen_US
dc.description.abstractCredit card fraudsters exploit various methods to capture card information. One of the common methods is to duplicate the credit cards by skimming. In this study, we introduce a new point of compromise detection method in order to trace and identify merchants where the skimming operation took place and card information has been captured by criminals. The proposed method first extracts discriminative features by using principle component analysis(PCA) and Autoencoder extractors and then it clusters similar fraudulent transactions with K-Means algorithm, afterwards it highlights possible merchants that are involved in this scheme by finding matching merchants in the produced clusters with a retrospective analysis of all transactions. Our experiments showed that the proposed method could achieve promising results with zeroknowledge on the existing skimming points. The application of our proposed method on real-life card transactions enabled us to pinpoint 7 out of 9 point of compromise previously identified by the reporting bank.
dc.identifier.citationOgme, F., Yavuz, Ali G., Güvensan, M. A., Karsligil, Mine E. (2021). Temporal transaction scraping assisted point of compromise detection with autoencoder based feature engineering. 9, 109536-109547. IEEE Access.
dc.identifier.doi10.1109/ACCESS.2021.3101738
dc.identifier.endpage109547en_US
dc.identifier.startpage109536en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12846/1079
dc.identifier.volume9en_US
dc.language.isoen
dc.relation.ispartofIEEE Access
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectFinancial frauden_US
dc.subjectPoint of compromise detectionen_US
dc.subjectCredit card skimmingen_US
dc.subjectClusteringen_US
dc.subjectAutoencoderen_US
dc.subjectRetrospective analysisen_US
dc.titleTemporal transaction scraping assisted point of compromise detection with autoencoder based feature engineering
dc.typeArticle

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