Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 18 of 18 for “"credit-card fraud"”.
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Context-Aware Credit Card Fraud Detection
Credit card fraud has emerged as major problem in the electronic payment sector. In this thesis, we study data-driven fraud detection and address several of its intricate challenges by means of machine learning methods with the goal to identify fraudulent transactions that have been issued …
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Using Context for Credit Card Fraud Detection
Online payment fraud is one of the biggest challenges accompanying the ubiquitous adoption of digital payment methods. The academic literature shows that providing data-driven models with additional context of a transaction results in significant improvements in fraud detection performance. …
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Credit card fraud detection using incremental feature learning
Detecting credit card fraud is essential and it is one of the most popular payment methods. Credit card fraud can cause huge losses for cardholders. Therefore, so many studies have focused on proposing different standard machine learning methods and limited use of incremental learning to create a …
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Modelling highly imbalanced credit card fraud detection data using statistical learning
Credit card fraud is a major concern for businesses worldwide, yielding losses of up to $67 billion per year in major banks and institutions. Machine learning techniques used to detect fraudulent transactions face several challenges when dealing with highly imbalanced data, which is often the case …
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Credit card fraud detection using machine learning with integration of contextual knowledge
… In fact, we model the authentic and fraudulent behavior of merchants and card holders according to two univariate characteristics: the date and the amount of transactions. In addition, attributes based on HMMs are created in a supervised manner, thereby reducing the need for expert …
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RESONANT: Reinforcement Learning Based Moving Target Defense for Detecting Credit Card Fraud
According to security.org, as of 2023, 65% of credit card (CC) users in the US have been subjected to fraud at some point in their lives, which equates to about 151 million Americans. The proliferation of advanced machine learning (ML) algorithms has also contributed to detecting credit card fraud …
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Optimising credit card fraud detection through machine learning and deep learning with spatial-temporal imbalance handling
… on digital payment systems and raised financial fraud, highlighting the need for effective fraud detection systems. This research addresses the "class imbalance challenge" in credit card fraud detection by integrating geolocation and temporal analysis to improve trend identification and anomaly …
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Australian attitudes towards computer crime
… the attitudes of the respondents to computer fraud, credit card fraud, copying software and hacking into computer systems. The research found, from questionnaire responses, that computer crimes are considered to be insignificant compared with other crimes which have far less impact on society …
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Developing a Practical Intervention to Prevent Identity Theft: A Behavioral-Science Field Study
… aim to actively involve cashiers in decreasing credit-card fraud. After baseline observations, cashiers at one store received a participative goal-setting and feedback intervention, whereby they collaboratively set a store goal for checking customers' identification. Over 23 days, the cashiers …
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Simulating high-throughput cryptocurrency payment channel networks
… based on behavioral modeling techniques used in credit card fraud research. Our simulation is the first payment channel network simulator to seed user behaviors with data from real-world credit card users. Our framework can be used to evaluate expected case performance and resiliency to attacks …
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A Constrained Box Algorithm for Imbalanced Data in Remote Sensing Images
… problem can be found in many domains such as credit card fraud detection and rare diseases diagnosis.</p> <p>Imbalanced data is a prominent issue also in remote sensing images (RSI) which are used to obtain information of earth resources and the surrounding environment. RSI are collected by …
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New approaches for outlier detection
… care, engineering, data processing and analysis, credit card fraud, monitoring computer and internet intrusions and wearable personal health sensors. Outlier detection once represented a single pre-processing step, completed prior to the analysis of data proper. Today it has importance in all …
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One-class classification in the presence of point, collective, and contextual anomalies
… be exposed early in order to avoid loss, e.g. in credit card fraud detection. One-class classification is a machine learning concept that is especially suited for the anomaly detection problem. Intrinsically unsupervised, it aims at providing a concise description of a given data set such that …
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Towards Real-World Quantum Machine Learning
… accuracy on Wisconsin breast cancer and 85% on credit-card fraud). This contribution is accompanied by an international patent filing (WO2025050205A1). Second, I develop a resource-efficient quantum kernel that enables high-dimensional embeddings with substantially fewer qubits and entanglers, …
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The relevant and reliable language theory : developing a language measure of trust for online groups
… in a virtual community focused on discussing credit card fraud, i.e. a criminal online group. The discussions were relational, rather than task focused, thus The Relevant and Reliable Language Theory predicted that LSM would be the most important language variable related to trust. The theory …
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A New Generative Adversarial Network for Improving Classification Performance for Imbalanced Data
… many industries, particularly in fields such as fraud detection and medical diagnosis. Imbalanced data refers to datasets where the distribution of classes is not equal, resulting in an over- representation of one class and an under-representation of another. This can lead to biassed and …
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Intervening to Increase the ID-Checking Behavior of Cashiers: Cashier-Focused vs. Customer-Focused Approaches
… cashiers to ask customers for their ID during a credit purchase. Research assistants (RAs) visited various stores and made credit purchases, while displaying one of the four prompts covering their card's signature line to the cashier during check-out. The results showed RAs were checked for ID …