Secure and privacy-preserving data aggregation in the Internet of Vehicles (IoV) continues to be a focal point of interest in both the industry and academia. Aiming at tackling the challenges and solving the remaining limitations of existing works, this paper introduces a novel Schnorr approval-based IoV data aggregation framework based on a two-layered architecture. In this framework, a server can aggregate the IoV data from clusters without inferring the raw data, real identity and trajectories of vehicles. Notably, we avoid incorporating the widely-accepted techniques such as homomorphic encryption and digital pseudonym to avoid introducing high computation cost to vehicles. We propose a novel concept, data approval, based on the Schnorr signature scheme. With the approval, the fake data injection attack carried out by a cluster head can be defended against. The separation of liability is achieved as well. The evaluation shows that the framework is secure and lightweight for vehicles in terms of the computation and communication costs.

翻译：车联网（IoV）中安全且保护隐私的数据聚合问题，始终是工业界与学术界共同关注的焦点。为应对现有方案挑战并解决其局限性，本文提出了一种基于双层架构的新型Schnorr认证车联网数据聚合框架。在该框架中，服务器可在不获取车辆原始数据、真实身份及行驶轨迹的前提下，完成对簇内IoV数据的聚合。值得注意的是，为避免为车辆引入高额计算开销，我们摒弃了同态加密、数字假名等广泛使用的技术手段。基于Schnorr签名方案，我们提出了"数据认证"这一全新概念。通过该认证机制，既能有效防御簇头发起的虚假数据注入攻击，又能实现责任分离。评估结果表明，本框架在计算与通信开销方面均具备安全性与轻量级特性，适用于车辆场景。