A Hybrid AI-Blockchain Framework with OCR, NER, and Anomaly Detection for Secure Land Record Management
Corresponding author: S. R. Nagaraja
Abstract
Land record systems are critical to property governance; yet remain vulnerable to forgery and manipulation. While blockchain offers tamper-proof storage, most solutions neglect to verify document authenticity before recording, allowing invalid data to become permanent. This paper studies a hybrid Artificial Intelligence (AI)–Blockchain framework integrating Optical Character Recognition (OCR), Named Entity Recognition (NER), and anomaly detection for intelligent pre-storage validation, combined with Ethereum smart contracts and InterPlanetary File System (IPFS) for secure, immutable storage. The system achieved 94.2% OCR accuracy, 90.9% NER F1-score, 93.4% validation accuracy, and 88.9% anomaly detection F1-score, ensuring that only authentic records are stored. This pre-storage validation mechanism represents a novel advancement over blockchain-only models by preventing fraudulent data from entering the ledger. Future work will focus on geospatial verification, biometric integration, and multilingual OCR to enhance scalability and regional applicability.
Keywords:
artificial intelligence, blockchain, land records, OCR, named entity recognition, anomaly detection, IPFSDownloads
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