Citation

Raponi S, Sciancalepore S, Oligeri G, Di Pietro R. arXiv 2020; arXiv:2002.05051v2 [cs].

Copyright

(Copyright © 2020, The author(s), Publisher Cornell University Library)

DOI

unavailable

PMID

unavailable

Abstract

[SafetyLit note: This document is a "preprint: Preprints and early-stage research may not have been peer reviewed yet.]

Assisted navigation software apps have a relevant impact on our daily life. Such apps infer the current state of roads mainly relying on the information provided by the devices they are running over. However, technological progress in two independent fields, i.e., mobile phone virtualization and Software Defined Radios, has enabled brand new types of attacks. It is nowadays possible to create fake queues of vehicles wherever in the world, as well as to make a congested street look like the best path to speed your travel. We refer to the aforementioned attacks as road traffic poisoning. These attacks open up several dreadful scenarios, where users can be maliciously re-routed by creating congestion in target positions, or to have users choose a given path since it is allegedly free from traffic, in both cases possibly affecting people's safety. In this paper, we analyze several scenarios, and discuss different adversary models, tools, and related attacks. We also propose a few novel countermeasures that could be adopted to mitigate the above threats, their limitations, and the open issues ahead.

Language: en

Keywords

Computer Science - Computers and Society; Computer Science - Cryptography and Security