Authors: Aji Teguh Prihatnom, Naufal Suryanto, Harashta Tatimma Larasati, Yustus Eko Oktian, Thi-Thu-Huong Le, Howon Kim

Conference: WISA 2023

Abstract: Non-Fungible Tokens (NFTs) have transformed the digital asset landscape with unique ownership verification. However, securing NFT images remains a crucial challenge. This paper proposes a verification framework for NFT images in a quantum blockchain environment. We explore the fundamentals, characteristics, and security challenges of NFT images. We examine the significance of quantum computing for digital security, highlighting vulnerabilities in classical encryption. We discuss existing image verification techniques and their limitations, leading to our proposed methodology that combines quantum-inspired approaches with a Deep Learning-based model. Additionally, we investigate the potential of ConvNeXt as a part of Deep Learning methods to enhance NFT image verification security and trust. Our comprehensive technique combines the Deep Learning-based method with a quantum blockchain to ensure the integrity, scalability, and validity of NFT images. Experimental evaluation demonstrates the feasibility and effectiveness of our approach. We discuss implications, including comparisons, limitations, and future research areas. This research advances digital security, providing insights into NFT image verification in the quantum computing era and laying the foundation for secure NFT ecosystems, promoting adoption across various domains. 

Link: https://link.springer.com/chapter/10.1007/978-981-99-8024-6_7