Optimization algorithm of fuzzy extractor in IoT blockchain identity authentication system

Targeting the performance bottleneck of the fuzzy extractor in the identity authentication system of IoT blockchain, this paper presents an optimization algorithm to enhance the system's efficiency and security. The optimization algorithm greatly lowers the computational complexity by optimizing the combination of BCH error correction code and efficient hash algorithm, maintaining a strong error correction capability. Experimental results indicate that under an environment with a noise rate of up to 20%, the algorithm's key generation time is only 0.22 seconds, the error correction success rate is over 90%, and the rate of collision is lower than 0.002%. Compared with the traditional fuzzy extractor, the average key generation time is reduced by 51% and the error correction success rate is improved by 6 percentage points. The optimization algorithm can strike a good balance between computational efficiency, error correction capability, and security, and is applicable to resource-constrained IoT devices and blockchain systems, offering reliable technical support for decentralized identity authentication.