High-Fidelity Simulated Dataset for Enhanced Detection of Denial of Wallet Attacks (DOW) in Serverless Architecture

Serverless architectures are becoming super popular with demanding growth and better functionality. This architecture is a fantastic option for building and launching applications in the cloud. Why Serverless? Well, they can scale up easily, save some costs, and help reduce the time and amount of work required to perform a particular operation. But as more folks dive into serverless computing, some big security problems have come to light. One of the big worries that is not easily identified is the Denial of Wallet (DoW) attacks. This type of attack aims to drain resources and hit cloud service providers hard in their pockets. To counter DoW attacks, we need to grasp their characteristics and how they behave in serverless environments. This paper takes a deep dive into our way of preventing this attack by creating a dataset designed for detecting the DoW attack in the serverless architecture. The dataset which will be given by us will play a crucial role in helping researchers and experts. It helps build and improve strong techniques for spotting DoW attacks. Our work aims to secure containerized applications against ever-changing cyber threats by understanding these threats and enabling smarter reactions and approaches.