Network Hexagons Under Attack: Secure Crowdsourcing of Geo-Referenced Data
Okemawo Obadofin, Joao Barros

TL;DR
This paper analyzes security vulnerabilities in the Nexagon protocol for geo-referenced data collection in ITS, proposing an enhanced architecture with PKI and pseudonyms to improve privacy without significant performance loss.
Contribution
It identifies security flaws in Nexagon and introduces a novel security architecture combining PKI and pseudonyms to mitigate privacy risks effectively.
Findings
Nexagon is vulnerable to user re-identification and session linkage.
The proposed architecture enhances privacy with minimal latency increase.
Prototype validation shows practical deployment feasibility.
Abstract
A critical requirement for modern-day Intelligent Transportation Systems (ITS) is the ability to collect geo-referenced data from connected vehicles and mobile devices in a safe, secure and anonymous way. The Nexagon protocol, which builds on the IETF Locator/ID Separation Protocol (LISP) and the Hierarchical Hexagonal Clustering (H3) geo-spatial indexing system, offers a promising framework for dynamic, privacy-preserving data aggregation. Seeking to address the critical security and privacy vulnerabilities that persist in its current specification, we apply the STRIDE and LINDDUN threat modelling frameworks and prove among other that the Nexagon protocol is susceptible to user re-identification, session linkage, and sparse-region attacks. To address these challenges, we propose an enhanced security architecture that combines public key infrastructure (PKI) with ephemeral pseudonym…
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