IPSO and SVM-Based Prevention Techniques for E-fraud: A Result Oriented Study

Abstract: Fraud is an intentionally deceptive action designed to provide the perpetrator with an unlawful gain or deny a victim a right. Fraud activities can be carried out by individuals, multiple individuals, or a business firm. This research aims to construct a deep convolutional neural network model to detect anomalies from regular patterns produced by competitive swarm optimization, with a strong focus and emphasis on fraud scenarios that cannot be detected using prior records or supervised learning. This algorithm classifies the fraud activity using real-time and another available dataset compared with the existing algorithms