KID34K: A Dataset for Identity Card Fraud Detection

Though digital financial systems have provided users with convenient and accessible services, such as supporting banking or payment services anywhere, it is necessary to have robust security to protect against identity misuse. Thus, digital identity(ID) verification plays a crucial role in securing financial services on mobile platforms. One of the most widely employed techniques for digital ID verification is that mobile applications request users to take and upload a picture of their own ID cards. However, this approach has vulnerabilities where someone takes pictures of the ID cards belonging to another person displayed on a screen, or printed on paper to be verified as the ID card owner. To mitigate the risks associated with fraudulent ID card verification, we present a novel dataset for classifying cases where the ID card images that users upload to the verification system are genuine or digitally represented. Our dataset is replicas designed to resemble real ID cards, making it available while avoiding privacy issues.

We provide the dataset through the form below:

https://docs.google.com/forms/d/e/1FAIpQLSd-RA_AscF7s3fwIAeeXK2EFAGDEjI8ql39po5gAEi6QeVBIw/viewform?usp=sf_link