一个多维,高效和安全的数据查询,基于车辆特设网络中的隐私保护

Xiangmei Zhao^1,2, Guofang Dong^1,2

¹School of Electrical and Information Technology, Yunnan Minzu University, Kunming, China.

PloS one

|November 26, 2025

概括

本研究介绍了一种有效的细粒度数据查询系统 (EFDA) 用于车辆特设网络 (VANET). EFDA允许安全,实时查询多维流量数据,同时保护用户隐私和提高效率.

科学领域:

智能运输系统智能运输系统
网络安全网络安全
数据隐私数据隐私数据

背景情况:

车辆特设网络 (VANET) 需要对智能运输进行高效和安全的数据查询.
现有系统在多维数据处理,隐私泄露以及在资源有限的环境中计算效率低等方面面临挑战.

研究的目的:

为VANETs提出一个高效的细粒度数据查询系统 (EFDA).
为了实现安全,实时查询多维流量数据,同时保持用户隐私.

主要方法:

使用多维CRT转换进行数据向量集成.
采用Paillier同态加密和区域特征掩盖,用于保护隐私的聚合.
集成ECDSA签名,以确保数据完整性和来源可靠性.
实施恶意节点监控和声誉激励机制.

主要成果:

EFDA满足数据保密性,完整性,来源可靠性和身份隐私的安全要求.
与参考方案相比,显著降低了计算开销 (85.7%,90.1%) 和通信开销 (69.1%,39.2%).
在隐私保护和查询效率之间实现平衡.

结论:

EFDA 是一种可行且高效的解决方案,用于在资源有限的 VANET 环境中查询数据.
该系统有效地解决了隐私问题,并提高了查询性能.

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