EAGER: Collaborative: Process-Based Technology to Support Comparison and Evaluation of the Security of Elections

EAGER：协作：基于流程的技术支持选举安全性的比较和评估

• 批准号: 1258588
• 负责人: Leon Osterweil
• 金额: $ 7.5万
• 依托单位: University of Massachusetts Amherst
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-10-01 至 2013-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1258588&HistoricalAwards=false
• 关键词: EAGER; Collaborative; Process; Based; Technology

This project explores process composition tools as applied to elections, concentrating particularly on mail-in and Internet voting. This includes exploration of how to compose systems from pre-analyzed process components, how to analyze the vulnerability of these systems to attacks, and how to guarantee that important security properties are ensured for the resulting composed system. The underlying processes represent aspects of national and local elections, their composition produces an election process, and analysis of the composition gives insight into potential errors or attacks on the election.Elections are human-intensive processes, processes that directly involve humans in important decision-making and coordination activities, including their interactions with hardware and software components. Providing an approach for formally reasoning about human participation extends current security work. The project also breaks new ground by exploring process-based approaches for modeling and defending against attacks.The project works closely with government agencies at both the national and local levels to provide in-depth realistic evaluation of results.Election officials in the U.S. can directly employ the results of this work to make U.S. election processes more verifiably secure, simpler, and easier to change as new technologies, laws, and regulations are imposed. Moreover the technologies developed in this project can be used in most human-intensive processes that have critical security concerns.

本项目探讨了应用于选举的过程组合工具，特别侧重于邮寄和互联网投票。这包括探索如何从预先分析的流程组件组成系统，如何分析这些系统对攻击的脆弱性，以及如何确保最终组成的系统的重要安全属性得到保证。潜在的过程代表了国家和地方选举的各个方面，它们的组成产生了选举过程，对组成的分析可以洞察选举的潜在错误或攻击。选举是人类密集的过程，在重要的决策和协调活动中直接涉及人类，包括他们与硬件和软件组件的互动。提供一种对人类参与进行正式推理的方法，扩展了当前的安全工作。该项目还通过探索基于过程的建模和防御攻击的方法开辟了新的领域。该项目与国家和地方各级政府机构密切合作，对结果进行深入、现实的评价。美国的选举官员可以直接利用这项工作的结果，使美国的选举过程更加可靠、更简单，并且随着新技术、法律和法规的实施，更容易改变。此外，本项目开发的技术可用于大多数具有关键安全问题的人力密集型流程。