CRJan 22, 2020

Security and Privacy in Vehicular Social Networks

arXiv:2001.08014v110 citations
Originality Synthesis-oriented
AI Analysis

It addresses security and privacy risks for users and infrastructure in VSNs, but is incremental as it builds on existing work.

The paper surveys security and privacy challenges in Vehicular Social Networks (VSNs), focusing on peer-to-peer interactions, and shows that existing solutions can evolve to address these challenges and accelerate VSN adoption.

We surveyed and presented the state-of-the-art VC systems, security and privacy architectures and technologies, emphasizing on security and privacy challenges and their solutions for P2P interactions in VSNs towards standardization and deployment. We note that beyond safety applications that have drawn a lot of attention in VC systems, there is significant and rising interest in vehicle-to-vehicle interaction for a range of transportation efficiency and infotainment applications, notably LBS as well as a gamut of services by mobile providers. While this enriches the VC systems and the user experience, security and privacy concerns are also intensified. This is especially so, considering (i) the privacy risk from the exposure of the users to the service providers, and (ii) the security risk from the interaction with malicious or selfish and thus misbehaving users or infrastructure. We showed existing solutions can in fact evolve and address the VSN-specific challenges, and improve or even accelerate the adoption of VSN applications.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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