PPLS: A Privacy-Preserving Location-Sharing Scheme in Vehicular Social Networks
This work addresses privacy and performance issues in vehicular social networks, which is an incremental improvement over prior schemes.
The paper tackles the problem of protecting users' interest information in interest-based forwarding schemes for Social Internet of Vehicles (SIOV) by proposing a privacy-preserving authentication protocol and a community energy metric, resulting in improved forwarding performance as demonstrated through simulations outperforming existing algorithms like BEEINFO, Epidemic, and PRoPHET.
Recent advances in Socially Aware Networks (SANs) have allowed its use in many domains, out of which social Internet of vehicles (SIOV) is of prime importance. SANs can provide a promising routing and forwarding paradigm for SIOV by using interest-based communication. Though able to improve the forwarding performance, existing interest-based schemes fail to consider the important issue of protecting users' interest information. In this paper, we propose a PRivacy-preserving Interest-based Forwarding scheme (PRIF) for SIOV, which not only protects the interest information, but also improves the forwarding performance. We propose a privacy-preserving authentication protocol to recognize communities among mobile nodes. During data routing and forwarding, a node can know others' interests only if they are affiliated with the same community. Moreover, to improve forwarding performance, a new metric {\em community energy} is introduced to indicate vehicular social proximity. Community energy is generated when two nodes encounter one another and information is shared among them. PRIF considers this energy metric to select forwarders towards the destination node or the destination community. Security analysis indicates PRIF can protect nodes' interest information. In addition, extensive simulations have been conducted to demonstrate that PRIF outperforms the existing algorithms including the BEEINFO, Epidemic, and PRoPHET.