Faculty of Computing-Scopus

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Subject: search.filters.subject.Blockchain

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    Smart Heritage: A Blockchain and NFT Framework for Secure Authentication and Fractional Investment in Sri Lankan Handicrafts
    (Institute of Electrical and Electronics Engineers Inc., 2026-07-06) Manohara K.K.K; Dharmasena E.A.H.T.; Rajapaksha D.N; Bandara H.D; Chamara, D; Abeywardena, K.Y; Nismi, N
    The Sri Lankan handicraft sector possesses significant cultural and economic value; however, counterfeit production, limited ownership traceability, and the absence of resale royalty mechanisms restrict its global scalability. Traditional systems fail to provide reliable provenance verification and sustainable financial benefits for artisans and previous owners. This paper proposes a blockchain-enabled ecosystem integrating Non-Fungible Tokens (NFTs), NFC-based authentication, fractional ownership, and a smart security box to enhance authenticity, transparency, and value creation. Each handicraft is linked to a unique NFT and a cryptographically secured NFC tag, creating a tamper-resistant connection between the physical artifact and its digital identity. Smart contracts enable transparent ownership tracking and automated lifetime royalty distribution, ensuring artisans receive royalties from every future resale without intermediaries. The proposed framework also introduces a fractional ownership model for culturally significant, non-commercial heritage artifacts, enabling collective digital ownership with tiered access to exclusive cultural content while distributing cascading royalties to previous shareholders upon resale. A smart security box with NFC further protects high-value physical artifacts. Prototype evaluation on an Ethereum-compatible test network achieved a 100% success rate across 24 smart contract unit tests, 100% NFC authentication accuracy for 12 handicraft items with average response times of 380-450 ms, and consistent royalty and Proof-of-Residency distribution across nine simulated resale transactions. The key contributions of this work are: (1) a cryptographic NFC-NFT binding mechanism resistant to tag cloning, (2) a smart contract-based lifetime royalty engine with previous-owner redistribution, and (3) a fractional community ownership model that supports global participation in preserving non-commercial cultural heritage. The proposed architecture demonstrates the potential of blockchain technology to preserve cultural heritage while creating a sustainable economic ecosystem for artisans and investors.
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    Blockchain-Based Custody Evidence Management System for Healthcare Forensics
    (Institute of Electrical and Electronics Engineers Inc., 2025) Jayasinghe R.D.D.L.K; Sasanka M.W.K.L; Athukorala D.A.S.M; Sandeepani M.A.D; Jayakody, A; Senarathna, A
    As digital evidence increasingly growing in significance in healthcare forensics, safeguarding sensitive medical data's confidentiality, integrity, and limited access remains to be an important issue. Existing forensic evidence management systems are subject to data breaches and illegal access since they frequently lack significant privacy-preserving measures. In order to overcome such challenges, this research suggests a Blockchain-Based Custody Evidence Management System for Healthcare Forensics, which combines blockchain technology, machine learning, and encryption methods to improve security, privacy, and accessibility. To ensure accurate and efficient gathering of information, machine learning algorithms are used to extract handwritten and printed text from medical photographs. AES encryption ensures safe storage, while Fully Homomorphic Encryption (FHE) is used for dynamic access level control to protect gathered evidence. Identity verification is made possible via a web-based authentication system that uses Zero-Knowledge Proofs (ZKP) to protect privacy by preventing the disclosure of personal data. By preventing unintended modifications, blockchain technology is used to preserve the custody chain's integrity. Furthermore, machine learning-driven PII detection and masking methods balance the requirement for forensic investigation with privacy compliance by controlling data accessibility according to access entitlements. Based on permitted access levels, the system makes it possible to share safe evidence with law enforcement agencies, such as courts, the police, and other forensic groups. Using blockchain to guarantee data immutability, cryptographic security to restrict access, and artificial intelligence (AI) to safeguard data, this approach enhances the privacy, security, and dependability of handling forensic evidence in medical investigations
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    Smart Agricultural Platform for Sri Lankan Farmers with Price Prediction, Blockchain Security, and Adaptive Interfaces
    (Institute of Electrical and Electronics Engineers Inc., 2025) Kuruppu K.A.G.S.R.; Kandambige S.T; Perera W.H.T.H; Cooray N.T.L; Nawinna, D; Perera, J
    Improper management of seed demand in Sri Lanka's agricultural sector can result in market imbalances, affecting farmers' decision-making and supply chain efficiency. This research introduces an integrated system for monitoring vegetable seed demand using digital technologies. The proposed system utilizes machine learning techniques to predict vegetable prices, a blockchain network for secure transactions, and a reward-based system to encourage user engagement. It also incorporates an adaptive user interface to accommodate different levels of digital literacy, ensuring accessibility for all farmers, especially senior citizens. Furthermore, the system features an AI Chatbot powered by Langchain and Pinecone, offering domain-specific responses and real-time support for farmers. The solution aims to combine advanced technology with agricultural practices to improve seed demand forecasting, promote transparency in transactions, and ensure a more efficient supply chain. This paper presents a multi-component agricultural platform that integrates predictive analytics, blockchain-secured transactions, gamified incentives, and adaptive user interfaces to support farming decision-making. The system combines machine learning for price forecasting, dynamic reward mechanisms to drive user engagement, and personalized UI/UX optimizations tailored for diverse user groups, including senior farmers. A multilingual AI-powered chatbot enhances accessibility and real-time support, enabling a robust, transparent, and inclusive digital solution for agricultural supply chain management.