This book provides essential information on Petri net theory and Petri net-based model checking methods. As for the Petri net theory, it involves the interleaving semantics and concurrency semantics of elementary net systems, some important net structures (e.g., invariant, repetitive vector, siphon, and trap), some classical net subclasses with special structures (e.g., state machine, marked graph, free-choice net,asymmetric-choice net, normal net, and weakly persistent net), and some basi...

This book explores deep learning as a next-generation approach to online payment fraud detection in the face of increasingly complex and adaptive threats. Traditional rule-based or shallow learning methods are no longer sufficient. Through ten focused chapters, this book tackles challenges such as behavioral modeling, spatiotemporal anomaly detection, class imbalance, behavior drift, and graph-based inference. It applies advanced neural architectures including LSTM, GRU, GANs, GNNs, and sp...