Generalized ATM Fraud Detection

Priesterjahn, Steffen; Anderka, Maik; Klerx, Timo; Mönks, Uwe

doi:10.1007/978-3-319-20910-4_13

Cited by 4 publications

(2 citation statements)

References 17 publications

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“…Roy and George utilized DT, RF, and NB, with DT and RF performing best, to find vehicle insurance fraud. In order to detect automobile insurance fraud in the presence of unbalanced data, Subudhi and Panigrahi [4] developed an adaptive oversampling strategy, achieving a high rate of fraud detection using SVM and Decision Tree classifiers.…”

Section: G Decision Trees (Dt)mentioning

confidence: 99%

Comparative Study of Fraudulent Activities and Various Fraud Detection Techniques

Doshi¹,

Desai²,

Shukla³

2023

IJRASET

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This study highlights the critical role that effective fraud detection systems play by examining the rising occurrence of fraud across industries, which is being driven by technological advancements. By examining a number of fraud categories, such as money laundering, cryptocurrency-related schemes, credit card fraud, and mortgage fraud, this study highlights the need for rigorous preventive measures. By carefully examining a wide range of detection techniques, including Support Vector Machines, Fuzzy Logic, Artificial Neural Networks, Hidden Markov Models, K-Nearest Neighbour, and Bayesian Networks, the research reveals the expanding toolset against fraudulent activity. Through a rigorous examination of applicable literature, creative cutting-edge methods, and astute investigations, the research highlights the crucial necessity of fraud detection systems across a variety of industries. The need for more innovation and interdisciplinary collaboration is highlighted by the discovery of knowledge gaps in real-time data analysis, handling unbalanced datasets, and resilient tactics against adversarial attacks. Our research also contributes to the development of strategies for preventing fraud, ensuring the dependability of financial institutions, and fostering confidence in a time of complex technological connections.

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Section: G Decision Trees (Dt)mentioning

confidence: 99%

Comparative Study of Fraudulent Activities and Various Fraud Detection Techniques

Doshi¹,

Desai²,

Shukla³

2023

IJRASET

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“…A fairly comprehensive summary of ATM attacks and detection mechanisms are described by Priesterjahn et al in [25]. The prominent ATM attacks fall in to the following categories: card skimming, where the information in the inserted bank card is skimmed for later use; card trapping, where the bank card is trapped after the transaction is complete using an extraneous device by the attacker in order to steal it later; PIN capturing, where the user's PIN number is stolen while being used; cash trapping, where the cash dispensed is trapped by the attacker using an extraneous device in order to retrieve it later; brute force safe opening to steal the cash in ATM; and using malware to attack the ATM firmware [25]. There are several variations of a recent malware attack known as "jackpotting" [28], and all these variations seek to change the firmware processing of the ATM.…”

Section: Illustrative Examplementioning

confidence: 99%

Limitations on observability of effects in cyber-physical systems

Damodaran

Rowe

2019

Proceedings of the 6th Annual Symposium on Hot Topics in the Science of Security

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Increased interconnectivity of Cyber-Physical Systems, by design or otherwise, increases the cyber attack surface and attack vectors. Observing the effects of these attacks is helpful in detecting them. In this paper, we show that many attacks on such systems result in a control loop effect we term Process Model Inconsistency (PMI). Our formal approach elucidates the relationships among incompleteness, incorrectness, safety, and inconsistency of process models. We show that incomplete process models lead to inconsistency. Surprisingly, inconsistency may arise even in complete and correct models. We illustrate our approach through an Automated Teller Machine (ATM) example, and describe the practical implications of the theoretical results. CCS CONCEPTS• Security and privacy → Formal security models; Embedded systems security.

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A two-steps prevention model of ATM frauds communications

Embarak

2018

2018 Fifth HCT Information Technology Trends (ITT)

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Generalized ATM Fraud Detection

Cited by 4 publications

References 17 publications

Comparative Study of Fraudulent Activities and Various Fraud Detection Techniques

Comparative Study of Fraudulent Activities and Various Fraud Detection Techniques

Limitations on observability of effects in cyber-physical systems

A two-steps prevention model of ATM frauds communications

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