NFTGenesis - An NFT Generation and Authentication System with Market Intelligence Using Deep Learning Based Steganography

This research paper proposes a novel approach of integrating traditional steganography techniques with modern deep learning methodology as a solution against prevailing cyber fraud in the blockchain space. Despite standard authentication measures in place, Non-Fungible Tokens (NFTs) are prone to dat...

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Bibliographic Details
Published in2024 IEEE International Conference on Contemporary Computing and Communications (InC4) Vol. 1; pp. 1 - 6
Main Authors N, Divya, Dhawan, Eeshan, Sundar, H Sarath, Jain, Harshit, Dinakar, Ruby
Format Conference Proceeding
LanguageEnglish
Published IEEE 15.03.2024
Subjects
Blockchain
Crypto-steganography
Cybersecurity
Deep learning
Fraud
Generative AI
Measurement
Non-Fungible Tokens (NFTs)
Protocols
Registers
Safety
Steganography
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Summary:This research paper proposes a novel approach of integrating traditional steganography techniques with modern deep learning methodology as a solution against prevailing cyber fraud in the blockchain space. Despite standard authentication measures in place, Non-Fungible Tokens (NFTs) are prone to data theft, replication, and misrepresentation of ownership. Hence, our work leverages deep learning infused with advanced crypto-steganography to add multi-layered authentication to these digital tokens. The research elaborates on multiple utilities relevant to NFTs such as their generation, verification, and price forecasting, while emphasizing mainly on authentication to provide a secure ecosystem. The research aims to delve into multiple methodologies that are integrated into a robust, comprehensive and a user-friendly NFT minting platform that works cohesively with the blockchain network. Hence, an extensive study is undertaken on the applications of deep learning in countering data theft in the NFT marketplaces.
DOI:10.1109/InC460750.2024.10649392