NLP-BERT AND OPTIMIZATION OF EFFICIENCY-SECURITY IN BLOCKCHAIN-ACCOUNTING SMART CONTRACTS

Abstract

In the evolving digital era, blockchain-based accounting systems leveraging smart contracts are increasingly crucial. Blockchain, known for its transparency and security, faces challenges in the efficiency and security of smart contracts, necessitating innovative solutions. This research explores the potential of Natural Language Processing (NLP) technology such as BERT to enhance these aspects within smart contracts. Grounded in blockchain and smart contract theories, the study investigates BERT's use in detecting financial fraud and improving transaction security. The research methodology employs Bibliometric Analysis with a PICO approach to formulate research questions and gather relevant data. Bibliometric analysis provides deeper insights into current developments and challenges in this field. The analysis reveals trends in document production, author collaborations, and keywords related to blockchain and BERT. Co-occurrence networks and thematic maps highlight the significance and relevance of these terms in the context of blockchain and smart contracts. In conclusion, this study makes a significant contribution to understanding how NLP technology can be optimized to enhance the efficiency and security of smart contracts in blockchain-based accounting systems. Further research is essential to develop BERT optimization in this context.