Abstract: A system and method for detecting fraudulent transactions of incremental transactions via incrementally training classifiers on a number of data subsets to obtain transaction label predictions. Recent information on fraudulent transactions is implemented to update the classifiers, thereby eliminating the problems of concept drift and verification latency. Some of the incremental transactions may be labeled as fraudulent according to the incrementally modified classifiers and thereby rejected.

Abstract: A system and method for detecting fraudulent transactions of incremental transactions via incrementally training classifiers on a number of data subsets to obtain transaction label predictions. Recent information on fraudulent transactions is implemented to update the classifiers, thereby eliminating the problems of concept drift and verification latency. Some of the incremental transactions may be labeled as fraudulent according to the incrementally modified classifiers and thereby rejected.

Abstract: A method and system for Threat Image Projection (TIP) data collection and image transformation of the TIP image data for inserting threat images in images of scanned objects, such as scanned luggage. A few scans for each threat object at predefined orientations can be stored in the system database and the system can transformed this image data to closely correspond to arbitrary threat positions in the tunnel. The transformed images can provide a close approximation in accuracy to images obtained by direct scanning at the corresponding appropriate location in the tunnel. The image data in the TIP image database can be scaled for use in other systems that have different geometries from the original system in which they were generated.