Research on data security delivery algorithm for crowdsourcing scenario in Internet of Vehicles

In the crowd sensing model of the Internet of Vehicles, mobile sensing and crowdsourcing technologies are combined to collaboratively collect driving data via sensors deployed on distributed vehicular nodes, enabling advanced traffic sensing tasks. However, in an open and complex wireless communication environment, this model encounters substantial security challenges, including malicious tampering of crowdsensing data and privacy breaches. This paper proposes a secure data delivery scheme for crowdsensing data in the IoV, which designs a homomorphic encryption-based data aggregation and secure transmission algorithm. Additionally, aggregate signature schemes are employed to achieve batch authentication for data source users, improving authentication efficiency. The scheme further incorporates an aggregation data verification algorithm based on homomorphic hash functions to ensure data integrity. Security analysis demonstrates that the scheme not only resists various traditional attacks but also ensures data unforgeability against adaptive chosen message attacks and identity unforgeability under chosen identity attacks. Performance analysis indicates that the scheme provides notable advantages in terms of computational and communication costs, effectively accommodating the high mobility and limited computational resources of vehicular nodes in IoV environments.