A Systematic Strategy Flow on Identification of Credit Card Fraud Detection from Banker Side using Machine Learning

Cloud computing has revolutionized IT infrastructure, offering on-demand access to computing resources. However, cloud environments are susceptible to various security threats. This paper presents a comprehensive review of simulation techniques for evaluating the impact of attacks on cloud environments. We discuss different attack types, simulation tools, and key metrics for assessing security posture. Additionally, we propose a comprehensive framework for simulating attacks on cloud environments, combining existing approaches and addressing their limitations. This framework can guide researchers and practitioners in designing and conducting effective simulations to strengthen cloud security for reducing credit card fraud at banker side [1].