Academic Journal
Voting by Mail: A Markov Chain Model for Managing the Security Risks of Absentee Voting.
| Τίτλος: | Voting by Mail: A Markov Chain Model for Managing the Security Risks of Absentee Voting. |
|---|---|
| Συγγραφείς: | Haseltine, Carmen A.1 (AUTHOR) carmen.haseltine@morgan.edu, Albert, Laura A.2 (AUTHOR) laura@engr.wisc.edu |
| Πηγή: | Decision Analysis (INFORMS). Sep2026, Vol. 23 Issue 3, p221-247. 27p. |
| Θεματικοί όροι: | *Markov processes, *Risk assessment, Absentee voting, Postal voting, Election security measures |
| Γεωγραφικοί όροι: | Milwaukee County (Wis.), United States |
| Περίληψη: | The scrutiny surrounding vote-by-mail (VBM) in the United States has increased in recent years, highlighting the need for a rigorous quantitative framework to evaluate the resilience of the absentee voting infrastructure. This paper addresses these issues by introducing a dynamic mathematical modeling framework for performing a risk assessment of VBM processes. We introduce a discrete-time Markov chain (DTMC) to model the VBM process and assess election performance and risk with a novel layered network approach that considers the interplay between VBM processes, malicious and nonmalicious threats, and security mitigations. The time-inhomogeneous DTMC framework captures dynamic risks and evaluates performance over time. The DTMC model accounts for a spectrum of outcomes, from unintended voter errors to sophisticated, targeted attacks, representing a significant advancement in the risk assessment of VBM planning and protection. A case study based on real-world data from Milwaukee County, Wisconsin, is used to evaluate the DTMC model. The analysis includes hypothetical worst-case attack scenarios to stress-test VBM processes and to assess the efficacy of security measures and the impact of different attack timings. The analysis suggests that ballot drop boxes and automatic ballot notification systems are crucial for reducing the attack surface to ensure secure and reliable operations. Funding: This work was supported by the National Science Foundation [Grant 2000986]. [ABSTRACT FROM AUTHOR] |
| Copyright of Decision Analysis (INFORMS) is the property of INFORMS: Institute for Operations Research & the Management Sciences and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
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| Items | – Name: Title Label: Title Group: Ti Data: Voting by Mail: A Markov Chain Model for Managing the Security Risks of Absentee Voting. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Haseltine%2C+Carmen+A%2E%22">Haseltine, Carmen A.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> carmen.haseltine@morgan.edu</i><br /><searchLink fieldCode="AR" term="%22Albert%2C+Laura+A%2E%22">Albert, Laura A.</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> laura@engr.wisc.edu</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Decision+Analysis+%28INFORMS%29%22">Decision Analysis (INFORMS)</searchLink>. Sep2026, Vol. 23 Issue 3, p221-247. 27p. – Name: Subject Label: Subject Terms Group: Su Data: *<searchLink fieldCode="DE" term="%22Markov+processes%22">Markov processes</searchLink><br />*<searchLink fieldCode="DE" term="%22Risk+assessment%22">Risk assessment</searchLink><br /><searchLink fieldCode="DE" term="%22Absentee+voting%22">Absentee voting</searchLink><br /><searchLink fieldCode="DE" term="%22Postal+voting%22">Postal voting</searchLink><br /><searchLink fieldCode="DE" term="%22Election+security+measures%22">Election security measures</searchLink> – Name: SubjectGeographic Label: Geographic Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Milwaukee+County+%28Wis%2E%29%22">Milwaukee County (Wis.)</searchLink><br /><searchLink fieldCode="DE" term="%22United+States%22">United States</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: The scrutiny surrounding vote-by-mail (VBM) in the United States has increased in recent years, highlighting the need for a rigorous quantitative framework to evaluate the resilience of the absentee voting infrastructure. This paper addresses these issues by introducing a dynamic mathematical modeling framework for performing a risk assessment of VBM processes. We introduce a discrete-time Markov chain (DTMC) to model the VBM process and assess election performance and risk with a novel layered network approach that considers the interplay between VBM processes, malicious and nonmalicious threats, and security mitigations. The time-inhomogeneous DTMC framework captures dynamic risks and evaluates performance over time. The DTMC model accounts for a spectrum of outcomes, from unintended voter errors to sophisticated, targeted attacks, representing a significant advancement in the risk assessment of VBM planning and protection. A case study based on real-world data from Milwaukee County, Wisconsin, is used to evaluate the DTMC model. The analysis includes hypothetical worst-case attack scenarios to stress-test VBM processes and to assess the efficacy of security measures and the impact of different attack timings. The analysis suggests that ballot drop boxes and automatic ballot notification systems are crucial for reducing the attack surface to ensure secure and reliable operations. Funding: This work was supported by the National Science Foundation [Grant 2000986]. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Decision Analysis (INFORMS) is the property of INFORMS: Institute for Operations Research & the Management Sciences and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1287/deca.2025.0386 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 27 StartPage: 221 Subjects: – SubjectFull: Markov processes Type: general – SubjectFull: Risk assessment Type: general – SubjectFull: Absentee voting Type: general – SubjectFull: Postal voting Type: general – SubjectFull: Election security measures Type: general – SubjectFull: Milwaukee County (Wis.) Type: general – SubjectFull: United States Type: general Titles: – TitleFull: Voting by Mail: A Markov Chain Model for Managing the Security Risks of Absentee Voting. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Haseltine, Carmen A. – PersonEntity: Name: NameFull: Albert, Laura A. IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 09 Text: Sep2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 15458490 Numbering: – Type: volume Value: 23 – Type: issue Value: 3 Titles: – TitleFull: Decision Analysis (INFORMS) Type: main |
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