Year: 2024
Type: article
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
Authors: Utkarsha Kulkarni, Rahul Paikrao
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4404660146