Protecting infrastructure performance from disinformation attacks
Abstract Disinformation campaigns are prevalent, affecting vaccination coverage, creating uncertainty in election results, and causing supply chain disruptions, among others. Unfortunately, the problems of misinformation and disinformation are exacerbated due to the wide availability of online platf...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2022-07-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-022-16832-w |
| _version_ | 1818501829999198208 |
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| author | Saeed Jamalzadeh Kash Barker Andrés D. González Sridhar Radhakrishnan |
| author_facet | Saeed Jamalzadeh Kash Barker Andrés D. González Sridhar Radhakrishnan |
| author_sort | Saeed Jamalzadeh |
| collection | DOAJ |
| description | Abstract Disinformation campaigns are prevalent, affecting vaccination coverage, creating uncertainty in election results, and causing supply chain disruptions, among others. Unfortunately, the problems of misinformation and disinformation are exacerbated due to the wide availability of online platforms and social networks. Naturally, these emerging disinformation networks could lead users to engage with critical infrastructure systems in harmful ways, leading to broader adverse impacts. One such example involves the spread of false pricing information, which causes drastic and sudden changes in user commodity consumption behavior, leading to shortages. Given this, it is critical to address the following related questions: (i) How can we monitor the evolution of disinformation dissemination and its projected impacts on commodity consumption? (ii) What effects do the mitigation efforts of human intermediaries have on the performance of the infrastructure network subject to disinformation campaigns? (iii) How can we manage infrastructure network operations and counter disinformation in concert to avoid shortages and satisfy user demands? To answer these questions, we develop a hybrid approach that integrates an epidemiological model of disinformation spread (based on a susceptible-infectious-recovered model, or SIR) with an efficient mixed-integer programming optimization model for infrastructure network performance. The goal of the optimization model is to determine the best protection and response actions against disinformation to minimize the general shortage of commodities at different nodes over time. The proposed model is illustrated with a case study involving a subset of the western US interconnection grid located in Los Angeles County in California. |
| first_indexed | 2024-12-10T21:01:41Z |
| format | Article |
| id | doaj.art-5c52179998124e84a4bdd3e7b8886628 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-12-10T21:01:41Z |
| publishDate | 2022-07-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-5c52179998124e84a4bdd3e7b88866282022-12-22T01:33:47ZengNature PortfolioScientific Reports2045-23222022-07-0112111410.1038/s41598-022-16832-wProtecting infrastructure performance from disinformation attacksSaeed Jamalzadeh0Kash Barker1Andrés D. González2Sridhar Radhakrishnan3School of Industrial and Systems Engineering, University of OklahomaSchool of Industrial and Systems Engineering, University of OklahomaSchool of Industrial and Systems Engineering, University of OklahomaSchool of Computer Science, University of OklahomaAbstract Disinformation campaigns are prevalent, affecting vaccination coverage, creating uncertainty in election results, and causing supply chain disruptions, among others. Unfortunately, the problems of misinformation and disinformation are exacerbated due to the wide availability of online platforms and social networks. Naturally, these emerging disinformation networks could lead users to engage with critical infrastructure systems in harmful ways, leading to broader adverse impacts. One such example involves the spread of false pricing information, which causes drastic and sudden changes in user commodity consumption behavior, leading to shortages. Given this, it is critical to address the following related questions: (i) How can we monitor the evolution of disinformation dissemination and its projected impacts on commodity consumption? (ii) What effects do the mitigation efforts of human intermediaries have on the performance of the infrastructure network subject to disinformation campaigns? (iii) How can we manage infrastructure network operations and counter disinformation in concert to avoid shortages and satisfy user demands? To answer these questions, we develop a hybrid approach that integrates an epidemiological model of disinformation spread (based on a susceptible-infectious-recovered model, or SIR) with an efficient mixed-integer programming optimization model for infrastructure network performance. The goal of the optimization model is to determine the best protection and response actions against disinformation to minimize the general shortage of commodities at different nodes over time. The proposed model is illustrated with a case study involving a subset of the western US interconnection grid located in Los Angeles County in California.https://doi.org/10.1038/s41598-022-16832-w |
| spellingShingle | Saeed Jamalzadeh Kash Barker Andrés D. González Sridhar Radhakrishnan Protecting infrastructure performance from disinformation attacks Scientific Reports |
| title | Protecting infrastructure performance from disinformation attacks |
| title_full | Protecting infrastructure performance from disinformation attacks |
| title_fullStr | Protecting infrastructure performance from disinformation attacks |
| title_full_unstemmed | Protecting infrastructure performance from disinformation attacks |
| title_short | Protecting infrastructure performance from disinformation attacks |
| title_sort | protecting infrastructure performance from disinformation attacks |
| url | https://doi.org/10.1038/s41598-022-16832-w |
| work_keys_str_mv | AT saeedjamalzadeh protectinginfrastructureperformancefromdisinformationattacks AT kashbarker protectinginfrastructureperformancefromdisinformationattacks AT andresdgonzalez protectinginfrastructureperformancefromdisinformationattacks AT sridharradhakrishnan protectinginfrastructureperformancefromdisinformationattacks |