Advanced Encryption Using Generative Adversarial Network for Enhancing Security of Non-Fungible Tokens (NFTs)

Non-fungible tokens (NFTs) represent a unique form of digital asset stored on a blockchain, encompassing a wide array of assets from digital art to real-world commodities. While NFTs offer robust security through decentralization and smart contract enforcement, they are not impervious to cyber threats. Traditionally, NFTs are transferred over blockchain platforms via smart contracts. The primary objective of this study is to introduce a cryptographic framework that integrates an advanced encryption algorithm layer to fortify NFT image transfers, reinforcing content protection in an evolving digital ecosystem. Various pixel-based encryption algorithms have been implemented using image processing techniques and compared considering their levels of encryption and execution times. Based on the comparison, an advanced encryption algorithm has been devised with an added level of encryption and fast execution time. The proposed encryption algorithm leverages alpha composition with a randomly generated image obtained using a Generative Adversarial Network (GAN). The GAN-generated image is infused with Gaussian noise to deter decryption by unauthorized algorithms, thereby enhancing resilience against cryptanalysis. The encrypted image metadata would be transferred through both on-chain (i.e., blockchain) and off-chain methods to facilitate efficiency and security during NFT transfers. The image decryption protocol mandates the new owner/receiver of NFT to possess the correct private identification, transaction key, and off-chain data, ensuring exclusive access while automatically revoking ownership from the previous holder upon successful transfer. This approach not only secures the transfer process but also minimizes the risk of data leaks, as intermediaries should not have access to the complete metadata. This cryptographic approach not only safeguards digital assets but also aligns with the futuristic vision of secure transactions in the metaverse and Web 3.0. The experimental analysis based on the security level and encryption time based on multiple encryption algorithms justifies the benefits of the proposed method.