Scholarlink

<p>In response to the need for a privacy protection method for Large models(LM) data that can accommodate partial information hiding and authentication of both data and interactor identity, paper proposes an enhanced SM9 algorithm based on blockchain technology. The proposed algorithm employs blind signature techniques to ensure the privacy of data while uniquely authenticating both the data and the identity of the interactor. The article proposes the least recently used (LRU) strategy to enhance the cuckoo filter, thereby optimizing the time efficiency of data interaction in the blockchain environment while ensuring secure and effective data privacy protection, signature verification and authentication, and public depository. The theory validates the accuracy and security of the proposed multifactor SM9 blind signature scheme and authentication method. The experimental results demonstrate that paper's method outperforms existing cryptographic schemes in terms of signing, signature checking, and authentication efficiency while optimizing the time consumption of the SM2/Schnorr scheme in the blind signature checking phase of the larger experimental data test volume was found to be 4.7/5.9 times faster, respectively, memory consumption reduced by an average of 26.91%, and demonstrates a 47.3% data interaction reduction and 16.56% throughput enhancement in blockchain's improved Cuckoo consensus, with 14.3% communication reduction and 10.38% latency optimization, indicating excellent performance and a lower growth rate of time consumption.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Multifactor SM9 blind signature large models data privacy preservation approach

  • 期刊论文

  • 发表日期：

    2025年5月22日

查看全文
  • Jiazheng Zhang,
  • Shouwei Li,
  • Minghui Chen

摘要

In response to the need for a privacy protection method for Large models(LM) data that can accommodate partial information hiding and authentication of both data and interactor identity, paper proposes an enhanced SM9 algorithm based on blockchain technology. The proposed algorithm employs blind signature techniques to ensure the privacy of data while uniquely authenticating both the data and the identity of the interactor. The article proposes the least recently used (LRU) strategy to enhance the cuckoo filter, thereby optimizing the time efficiency of data interaction in the blockchain environment while ensuring secure and effective data privacy protection, signature verification and authentication, and public depository. The theory validates the accuracy and security of the proposed multifactor SM9 blind signature scheme and authentication method. The experimental results demonstrate that paper's method outperforms existing cryptographic schemes in terms of signing, signature checking, and authentication efficiency while optimizing the time consumption of the SM2/Schnorr scheme in the blind signature checking phase of the larger experimental data test volume was found to be 4.7/5.9 times faster, respectively, memory consumption reduced by an average of 26.91%, and demonstrates a 47.3% data interaction reduction and 16.56% throughput enhancement in blockchain's improved Cuckoo consensus, with 14.3% communication reduction and 10.38% latency optimization, indicating excellent performance and a lower growth rate of time consumption.