SaTC: CORE: Small: Collaborative: Defending Against Authorship Attribution Attacks

SaTC：核心：小型：协作：防御作者归属攻击

• 批准号: 1814602
• 负责人: Patrick Juola
• 金额: $ 23.88万
• 依托单位: Duquesne University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-01 至 2023-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1814602&HistoricalAwards=false
• 关键词: SaTC; CORE; Small; Collaborative; Defending

Authorship attribution techniques identify the author of an unsigned document such as an e-mail, memo, or social media post by analyzing candidate authors' writing styles for tell-tale "fingerprints" such as distinctive words and sentence structure. Everyone leaves these fingerprints in his or her writing. This creates a problem for people who have a need to remain anonymous, people including whistleblowers and journalists working in states hostile to their work. Because a small sample of prose risks exposing the identity of a writer, guarantees of anonymity and confidentiality offered by government-sponsored whistleblower programs are difficult to sustain. Many strategies have been proposed for protecting writers from attackers who want to discover their identities. This research compares the effectiveness of these methods and develops software to help individuals write documents in ways that minimize information revealed about their identities.This project characterizes the effectiveness of known defenses against authorship attribution attacks, including a novel defense which requires a source to write using a widely-used simplified variant of English. The project develops software which provides interactive feedback to sources who need to write prose which does not reveal their identity. This software tool supports automatic, non-interactive rewriting of English prose that preserves the semantic content of a document while removing identifying stylistic fingerprints. The research translates into deliverables which are of practical use to organizations and corporations running anonymous and confidential whistleblower programs to better protect the identities of sources and, in doing so, make reporting suspected wrongdoing less risky. The project will involve graduate and undergraduate students.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

作者归属技术通过分析候选作者的写作风格来识别未签名文档（如电子邮件、备忘录或社交媒体帖子）的作者，以获得诸如独特的单词和句子结构等的“指纹”。每个人都会在他或她的写作中留下这些指纹。 这给那些需要保持匿名的人带来了问题，包括在对其工作怀有敌意的国家工作的举报人和记者。由于一小部分散文样本有暴露作者身份的风险，政府资助的举报人计划所提供的匿名和保密保证很难维持。 已经提出了许多策略来保护作者免受想要发现其身份的攻击者的攻击。这项研究比较了这些方法的有效性，并开发软件来帮助个人以最大限度地减少有关其身份的信息泄露的方式编写文档。该项目描述了已知的针对作者归属攻击的防御措施的有效性，包括一种新型防御措施，该防御措施需要来源使用广泛使用的简化英语变体。该项目开发的软件，提供互动反馈的来源谁需要写散文，不透露他们的身份。该软件工具支持自动、非交互式重写英语散文，保留文档的语义内容，同时删除识别风格的指纹。该研究转化为可交付成果，对运行匿名和保密举报人计划的组织和公司具有实际用途，以更好地保护消息来源的身份，并在这样做的过程中，降低报告可疑不法行为的风险。该项目将涉及研究生和本科生。该奖项反映了NSF的法定使命，并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。