Authors - Noor, Soumya Mukherjee, Shivraj Singh Yadav Abstract - The increasing numbers of deepfakes and AI tools have made it difficult to trust digital images these days. Images can be altered and ownership can be established without revealing private information. Current systems have many limitations, and systems that either rely on easyto change metadata or on cryptographic methods that are too costly like ZKSNARKs. To overcome these limitations, an authentication verification model has been presented named ZKP-Guard based on a Dual- Lock architecture framework. The detection system verifies an image is a real image by using ECDSA signatures and a custom ownership in the Schnorr-based Zero-Knowledge Proof for the protocol. This framework was tested on a dataset with significant number of images and produced desired results.
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