Abstract: Described are a system, method, and computer program product for breach detection using convolutional neural networks. The method includes receiving transaction data associated with a plurality of transactions completed in a first time period. The method also includes identifying a set of suspected fraudulent transactions of the plurality of transactions based on inputting at least one parameter of the transaction data into a fraud evaluation model. The method further includes generating an image comprising a field of points, wherein each point is associated with at least one transaction of the set of suspected fraudulent transactions, and wherein an x-axis position in the image of each point in the field of points is associated with a time subperiod of the first time period in which the at least one transaction occurred. The method further includes detecting a breach event by processing the image with a convolutional neural network (CNN) model.

Abstract: Described are a system, method, and computer program product for breach detection using convolutional neural networks. The method includes receiving transaction data associated with a plurality of transactions completed in a first time period. The method also includes identifying a set of suspected fraudulent transactions of the plurality of transactions based on inputting at least one parameter of the transaction data into a fraud evaluation model. The method further includes generating an image comprising a field of points, wherein each point is associated with at least one transaction of the set of suspected fraudulent transactions, and wherein an x-axis position in the image of each point in the field of points is associated with a time subperiod of the first time period in which the at least one transaction occurred. The method further includes detecting a breach event by processing the image with a convolutional neural network (CNN) model.

Abstract: Described are a system, method, and computer program product for merchant breach detection using convolutional neural networks. The method includes receiving transaction data associated with a plurality of transactions by a plurality of payment devices in a first time period subsequent to the plurality of payment devices transacting with a merchant. The method also includes identifying, based on inputting at least one parameter of the transaction data into a fraud evaluation model, a set of suspected fraudulent transactions of the plurality of transactions. The method further includes generating an image comprising a field of points, wherein each point of the field of points is associated with at least one transaction. The method further includes detecting breach of the merchant by processing the image with a convolutional neural network (CNN) model.