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Traffic networks are vulnerable to disinformation attacks
Disinformation continues to raise concerns due to its increasing threat to society. Nevertheless, a threat of a disinformation-based attack on critical infrastructure is often overlooked. Here, we consider urban traffic networks and focus on fake information that manipulates drivers’ decisions to cr...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7935872/ https://www.ncbi.nlm.nih.gov/pubmed/33674635 http://dx.doi.org/10.1038/s41598-021-84291-w |
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author | Waniek, Marcin Raman, Gururaghav AlShebli, Bedoor Peng, Jimmy Chih-Hsien Rahwan, Talal |
author_facet | Waniek, Marcin Raman, Gururaghav AlShebli, Bedoor Peng, Jimmy Chih-Hsien Rahwan, Talal |
author_sort | Waniek, Marcin |
collection | PubMed |
description | Disinformation continues to raise concerns due to its increasing threat to society. Nevertheless, a threat of a disinformation-based attack on critical infrastructure is often overlooked. Here, we consider urban traffic networks and focus on fake information that manipulates drivers’ decisions to create congestion at a city scale. Specifically, we consider two complementary scenarios, one where drivers are persuaded to move towards a given location, and another where they are persuaded to move away from it. We study the optimization problem faced by the adversary when choosing which streets to target to maximize disruption. We prove that finding an optimal solution is computationally intractable, implying that the adversary has no choice but to settle for suboptimal heuristics. We analyze one such heuristic, and compare the cases when targets are spread across the city of Chicago vs. concentrated in its business district. Surprisingly, the latter results in more far-reaching disruption, with its impact felt as far as 2 km from the closest target. Our findings demonstrate that vulnerabilities in critical infrastructure may arise not only from hardware and software, but also from behavioral manipulation. |
format | Online Article Text |
id | pubmed-7935872 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-79358722021-03-08 Traffic networks are vulnerable to disinformation attacks Waniek, Marcin Raman, Gururaghav AlShebli, Bedoor Peng, Jimmy Chih-Hsien Rahwan, Talal Sci Rep Article Disinformation continues to raise concerns due to its increasing threat to society. Nevertheless, a threat of a disinformation-based attack on critical infrastructure is often overlooked. Here, we consider urban traffic networks and focus on fake information that manipulates drivers’ decisions to create congestion at a city scale. Specifically, we consider two complementary scenarios, one where drivers are persuaded to move towards a given location, and another where they are persuaded to move away from it. We study the optimization problem faced by the adversary when choosing which streets to target to maximize disruption. We prove that finding an optimal solution is computationally intractable, implying that the adversary has no choice but to settle for suboptimal heuristics. We analyze one such heuristic, and compare the cases when targets are spread across the city of Chicago vs. concentrated in its business district. Surprisingly, the latter results in more far-reaching disruption, with its impact felt as far as 2 km from the closest target. Our findings demonstrate that vulnerabilities in critical infrastructure may arise not only from hardware and software, but also from behavioral manipulation. Nature Publishing Group UK 2021-03-05 /pmc/articles/PMC7935872/ /pubmed/33674635 http://dx.doi.org/10.1038/s41598-021-84291-w Text en © The Author(s) 2021 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Waniek, Marcin Raman, Gururaghav AlShebli, Bedoor Peng, Jimmy Chih-Hsien Rahwan, Talal Traffic networks are vulnerable to disinformation attacks |
title | Traffic networks are vulnerable to disinformation attacks |
title_full | Traffic networks are vulnerable to disinformation attacks |
title_fullStr | Traffic networks are vulnerable to disinformation attacks |
title_full_unstemmed | Traffic networks are vulnerable to disinformation attacks |
title_short | Traffic networks are vulnerable to disinformation attacks |
title_sort | traffic networks are vulnerable to disinformation attacks |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7935872/ https://www.ncbi.nlm.nih.gov/pubmed/33674635 http://dx.doi.org/10.1038/s41598-021-84291-w |
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