Voting by mail: a Markov chain model for managing the security risks of election systems

Computer Science > Cryptography and Security [Submitted on 15 Oct 2024 (v1), last revised 3 Apr 2026 (this version, v3)] Voting by mail: a Markov chain model for managing the security risks of election systems Carmen A. Haseltine, Laura A. Albert 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 non-malicious 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. Subjects: Cryptography and Security (cs.CR); Probability (math.PR) Cite as: arXiv:2410.13900 [cs.CR]   (or arXiv:2410.13900v3 [cs.CR] for this version)   https://doi.org/10.48550/arXiv.2410.13900 Focus to learn more Submission history From: Laura Albert [view email] [v1] Tue, 15 Oct 2024 17:35:11 UTC (4,175 KB) [v2] Tue, 29 Jul 2025 17:58:55 UTC (376 KB) [v3] Fri, 3 Apr 2026 16:49:37 UTC (340 KB) Access Paper: HTML (experimental) view license Current browse context: cs.CR < prev   |   next > new | recent | 2024-10 Change to browse by: cs math math.PR References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)