Preserving Ownership and Trading of AI Prompts in Decentralized Manner via Hyperledger Besu-Based Blockchain and IPFS-Backed NFTs

The increasing adoption of AI-generated content brings in challenges related to authenticity, ownership, and secure monetization of creative prompts. No existing centralized platform ensures transparent ownership records and royalty mechanisms. This leaves creators open to theft of intellectual property and less than adequate compensation. In this paper, we propose a blockchain-based framework for tokenizing AI-generated prompts as NFTs that ensures authenticity, ownership, and secure monetization. It supports two types of prompts: text-based prompts and text + media file prompts. The former are directly stored on the blockchain, enabling an immutable record. For text + media file prompts, the media files are stored in a decentralized manner using IPFS (InterPlanetary File System), which generates a unique Content Identifier (CID). A hash of the content, the CID, and metadata is then committed to the blockchain for traceability and security. Smart contracts regulate ownership, royalties, and licensing, thereby allowing creators to monetize through initial sales, resale royalties, and sub-licensing. Prompts are tokenized as Non-Fungible Tokens (NFTs) through smart contracts. Each NFT is uniquely linked to the metadata of its corresponding prompt, ensuring authenticity and traceability. The system achieves an average throughput of 800 TPS, a latency of 2.5 seconds, and 70% CPU efficiency, outperforming traditional mechanisms like Proof-of-Work (PoW) and Proof-of-Stake (PoS) in scalability and responsiveness.

Authors

Institutions

Publication Details

Published
2025-06-27
DOI
https://doi.org/10.1109/ncim65934.2025.11160076
Primary Topic
Blockchain Technology Applications and Security
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Preserving Ownership and Trading of AI Prompts in Decentralized Manner via Hyperledger Besu-Based Blockchain and IPFS-Backed NFTs

Md Hamid Uddin, Saha Reno, Abrar Khan Alvi, Rafi Ibne Azad
Blockchain Technology Applications and Security
article

Preserving Ownership and Trading of AI Prompts in Decentralized Manner via Hyperledger Besu-Based Blockchain and IPFS-Backed NFTs

Md Hamid Uddin, Saha Reno, Abrar Khan Alvi, Rafi Ibne Azad
article en

Abstract

The increasing adoption of AI-generated content brings in challenges related to authenticity, ownership, and secure monetization of creative prompts. No existing centralized platform ensures transparent ownership records and royalty mechanisms. This leaves creators open to theft of intellectual property and less than adequate compensation. In this paper, we propose a blockchain-based framework for tokenizing AI-generated prompts as NFTs that ensures authenticity, ownership, and secure monetization. It supports two types of prompts: text-based prompts and text + media file prompts. The former are directly stored on the blockchain, enabling an immutable record. For text + media file prompts, the media files are stored in a decentralized manner using IPFS (InterPlanetary File System), which generates a unique Content Identifier (CID). A hash of the content, the CID, and metadata is then committed to the blockchain for traceability and security. Smart contracts regulate ownership, royalties, and licensing, thereby allowing creators to monetize through initial sales, resale royalties, and sub-licensing. Prompts are tokenized as Non-Fungible Tokens (NFTs) through smart contracts. Each NFT is uniquely linked to the metadata of its corresponding prompt, ensuring authenticity and traceability. The system achieves an average throughput of 800 TPS, a latency of 2.5 seconds, and 70% CPU efficiency, outperforming traditional mechanisms like Proof-of-Work (PoW) and Proof-of-Stake (PoS) in scalability and responsiveness.

Ahsanullah University of Science and Technology (BD)
Openalex Percentile: Top 63%
Blockchain Technology Applications and Security
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.