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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 16 Issue 10, 2025.
Abstract: The existing user identity confirmation methods in property management systems are vulnerable to attacks and forgery, posing serious threats to system security and reliability. To address these issues, this study proposes a novel user identity confirmation method that combines the state secret SM9 algorithm with blockchain technology. The system utilizes blockchain for managing and verifying user identity information, while employing the SM9 algorithm for double encryption of user data. This approach ensures robust protection against identity theft and fraud, enhancing security and privacy. The proposed method was tested experimentally, and the results show that the model achieves an average communication connection and verification initiation time of approximately 11.07 ms, with a key negotiation success rate of 88.73%. Moreover, the model achieved a user identity confirmation accuracy of 90.41%, which is significantly higher than traditional methods. These findings highlight that the integration of the SM9 algorithm and blockchain technology offers high accuracy, low latency, and improved scalability, making it an ideal solution for enhancing the security and efficiency of property management systems.
Xiao Tian and Xing Chen. “User Identity Confirmation Property Management System Based on State Secret Algorithm and Blockchain Technology”. International Journal of Advanced Computer Science and Applications (IJACSA) 16.10 (2025). http://dx.doi.org/10.14569/IJACSA.2025.0161083
@article{Tian2025,
title = {User Identity Confirmation Property Management System Based on State Secret Algorithm and Blockchain Technology},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2025.0161083},
url = {http://dx.doi.org/10.14569/IJACSA.2025.0161083},
year = {2025},
publisher = {The Science and Information Organization},
volume = {16},
number = {10},
author = {Xiao Tian and Xing Chen}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.