Combining BERT and Blockchain Technology to Improve Network Authentication Security

With the rapid development of the Internet, network identity authentication faces increasingly severe security challenges, such as identity theft, data tampering, and privacy leakage. To address these issues, this study introduces a method that combines the BERT (Bidirectional Encoder Representations from Transformers) model in natural language processing with blockchain technology to build an efficient and secure network identity authentication system. In the method part, first, the BERT model is used to perform deep semantic understanding and feature extraction of user identity information to improve the accuracy and robustness of identity authentication. Next, blockchain technology is used to build a distributed ledger to ensure that the data in the identity authentication process cannot be tampered with and is transparent and traceable, thereby enhancing the overall security of the system. Finally, smart contracts are used to automate the identity authentication process, reduce the risk of human intervention, and improve the response speed and efficiency of the system. Experimental results show that the accuracy of traditional methods fluctuates between 80% and 90%, while the accuracy of BERT methods is mostly above 90%. The response time of the BERT+Blockchain system fluctuates slightly, ranging from 0.51 seconds to 0.99 seconds. In summary, the network identity authentication scheme based on BERT and blockchain adopted in this paper not only improves the security and reliability of identity authentication, but also provides a new technical path for future network security protection.