Due to a rapid advancement in the electronic commerce technology, the use of credit cards has dramatically increased. As credit card becomes the most popular mode of payment for both online as well as regular purchase, cases of fraud associated with it are also rising. In this paper, we model the sequence of operations in credit card transaction processing using a Hidden Markov Model (HMM) and ...

Adam Graycar Director The plastic card industry is being targeted by organised criminal enterprise from around the world. In the past, Australia’s physical isolation from the rest of the world protected us, to some extent, from fraud trends which were taking place elsewhere. Computers, telecommunications systems, and international travel, now allow Australia to experience the same kinds of frau...

Anomaly detection on sequential data is common in many domains such as fraud detection for credit cards, intrusion detection for cyber-security or military surveillance. This paper addresses a new CUSUMlike method for change point detection on curves sequences in a context of preventive maintenance of transit buses door systems. The proposed approach is derived from a specific generative modeli...

Credit card frauds are unauthorized transactions that are made or attempted by a person or an organization that is not authorized by the card holders. Fraud with general-purpose cards (credit, debit cards etc.) is a billion dollar industry and companies are therefore investing significant efforts in identifying and preventing them. It is typical to deploy mining and machine learning-based techn...

The amount of online transactions is growing these days to a large number. A big portion of these transactions contains credit card transactions. The growth of online fraud, on the other hand, is notable, which is generally a result of ease of access to edge technology for everyone. There has been research done on many models and methods for credit card fraud prevention and detection. Artificia...

Financial institutions in the form of banks provide facilities credit cards, but with development technology, fraud on card transactions is still common, so a system needed that can detect quickly and accurately. Therefore, this study aims to classify fraudulent transactions. The proposed method Ensemble Learning which will be tested using Boosting type 3 variations, namely XGBoost, Gradient Bo...

The rising number of credit card frauds presents a significant challenge for the banking industry. Many businesses and financial institutions suffer huge losses because users are reluctant to use their cards. A primary goal fraud detection is identify prior transaction patterns detect future fraud. In this paper, hybrid ensemble model proposed combine bagging boosting techniques distinguish bet...

— With the developments in the Information Technology and improvements in the communication channels, fraud is spreading all over the world, resulting in huge financial losses. Though fraud prevention mechanisms such as CHIP&PIN are developed, these mechanisms do not prevent the most common fraud types such as fraudulent credit card usages over virtual POS terminals or mail orders. As a result,...

Phishing is a malicious form of Internet fraud with the aim to steal valuable information such as credit cards, social security numbers, and account information. This is accomplished primarily by crafting a faux online presence to masquerade as a legitimate institution and soliciting information from unsuspecting customers. Phishing attacks involving websites are among the most commonplace and ...