基于多属性同态加密和消息认证的群智感知隐私保护机制

A privacy protection mechanism for crowdsourced sensing based on multi-attribute homomorphic encryption and message verification

隐私保护在移动群智感知中扮演着重要的角色,保证数据的保密性和完整性是一项具有挑战性的工作。不同于以往仅关注单属性数据隐私保护的研究,本文提出了一种基于多属性同态加密和消息认证的群智感知隐私保护机制。为了保证数据的安全性,同时减少数据传输量,将椭圆曲线加密算法进行改进,使得不同属性的加密数据可以进行聚合;为了保证数据的不可篡改性和完整性,利用同态消息认证码对数据进行安全认证。安全性分析和仿真结果表明,该方案具有较高的安全性,并且能够减少传输通信量,提高传输效率。

Privacy protection plays a crucial role in mobile crowd sensing,and ensuring the confidentiality and integrity of data poses a challenging task.Different from previous studies that focused solely on single-attribute data privacy protection,this research introduces a privacy protection mechanism for crowd sensing based on multi-attribute homomorphic encryption and message verification(MAMV).Initially,improvements are made to the elliptic curve encryption algorithm to enable the aggregation of encrypted data from different attributes.Subsequently,to guarantee the data's tamper resistance and integrity,homomorphic message authentication codes are employed for secure authentication.Security analysis and simulation results demonstrate that the MAMV scheme effectively prevents both active and passive attacks,reduces transmission overhead,and enhances transmission efficiency.