Bidirectional privacy authorization for large models based on private set intersection

YANG Shuai; HAN Yiliang; WU Xuguang; FENG Haokang; WANG Yuanyuan

doi:10.11959/j.issn.2096-109x.2025062

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Bidirectional privacy authorization for large models based on private set intersection

更新时间：2025-11-08

- Bidirectional privacy authorization for large models based on private set intersection
- Chinese Journal of Network and Information Security Vol. 11, Issue 5, Pages: 101-114(2025)
- 作者机构：
  
  1.武警工程大学密码工程学院，陕西西安710086
  2.武警工程大学反恐指挥信息工程教育部重点实验室，陕西西安710086
- 作者简介：
- 基金信息：
  
  The Natural Science Basic Research Program of Shaanxi Province(2025JC-YBMS-664)
- DOI：10.11959/j.issn.2096-109x.2025062
  CLC： TP309
- Received：09 April 2025，
  
  Revised：2025-06-24，
  
  Published：25 October 2025
- 稿件说明：
移动端阅览
杨帅, 韩益亮, 吴旭光, 等. 基于隐私集合求交的大模型双向隐私授权[J]. 网络与信息安全学报, 2025, 11(5): 101-114.

YANG S, HAN Y L, WU X G, et al. Bidirectional privacy authorization for large models based on private set intersection[J]. Chinese Journal of Network and Information Security, 2025, 11(5): 101-114.
杨帅, 韩益亮, 吴旭光, 等. 基于隐私集合求交的大模型双向隐私授权[J]. 网络与信息安全学报, 2025, 11(5): 101-114. DOI： 10.11959/j.issn.2096-109x.2025062.

YANG S, HAN Y L, WU X G, et al. Bidirectional privacy authorization for large models based on private set intersection[J]. Chinese Journal of Network and Information Security, 2025, 11(5): 101-114. DOI： 10.11959/j.issn.2096-109x.2025062.

摘要

针对大语言模型多模态接入场景面临的隐私泄露风险，以及传统基于角色和属性的访问控制模型在用户属性多元、访问规模大时难以实现细粒度隐私管控的问题，提出一种基于布谷鸟混淆布隆过滤器的隐私集合求交协议，并构建支持隐私保护的属性访问控制框架。首先，设计布谷鸟混淆布隆过滤器结构，通过引入多重哈希链机制降低元素插入时的碰撞概率，并采用异或操作对过滤器内元素的存储位置进行混淆处理，进一步增强其抗攻击能力；其次，基于该过滤器构建两方隐私集合求交协议，在标准半诚实模型下实现了单轮通信开销；最后，结合基于属性的访问控制模型，设计具备双向隐私验证能力的访问控制框架，利用隐私集合求交技术实现访问策略与用户属性信息的双向隐私保护。实验结果表明，在属性数量为200、并发访问量为10万的场景下，所提方案的策略验证耗时相较于基于椭圆曲线密码的密文策略属性加密（CP-ABC）方案降低约55%，显著提升了高并发访问场景下的处理效率，为大语言模型多模态接入场景提供了兼顾安全与性能的隐私保护方案。

Abstract

To address the privacy leakage risks in multimodal access scenarios of large language models (LLMs) and the limitations of traditional role-and attribute-based access control models in achieving fine-grained privacy control with diverse user attributes and large-scale access

a private set intersection (PSI) protocol based on cuckoo-garbled Bloom filter (CGBF) was proposed

and an attribute-based access control framework supporting privacy protection was constructed. The CGBF structure was designed: the collision probability during element insertion was reduced by introducing a multiple hash chain mechanism

and the storage positions of elements in the filter were garbled through XOR operations

which further enhanced its anti-attack capability. A two-party PSI protocol was constructed based on this filter

achieving single-round communication overhead under the standard semi-honest model. By integrating with the attribute-based access control model

an access control framework with bidirectional privacy verification capability was designed. And the bidirectional privacy protection of access policies and user attribute information was realized using PSI technology. Experimental results show that in scenarios with 200 attributes and 100

000 concurrent accesses

the policy verification time of the proposed scheme is reduced by approximately 55% compared to the CP-ABC scheme based on elliptic curve cryptography

and processing efficiency in high-concurrency access scenarios is significantly improved. This scheme is demonstrated to provide a privacy protection solution that balances security and performance for multimodal access scenarios of LLMs.

关键词

Keywords

references

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