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

作者归属技术通过分析候选作者的写作风格，如独特的单词和句子结构，来识别未签名文件（如电子邮件、备忘录或社交媒体帖子）的作者。每个人都会在他或她的文字中留下这些指纹。这给那些需要保持匿名的人带来了一个问题，包括在敌视他们工作的国家工作的告密者和记者。由于一小部分散文有暴露作者身份的风险，政府资助的举报人项目提供的匿名和保密保证很难维持下去。为了保护作者免受想要发现其身份的攻击者的攻击，已经提出了许多策略。这项研究比较了这些方法的有效性，并开发了软件来帮助个人以最小化身份信息泄露的方式编写文档。该项目描述了针对作者归属攻击的已知防御措施的有效性，包括一种要求来源使用广泛使用的简化英语变体进行写作的新颖防御措施。该项目开发了一种软件，可以为那些需要写散文的人提供交互式反馈，而这些散文不会透露他们的身份。这个软件工具支持自动的、非交互式的英语散文重写，保留了文档的语义内容，同时删除了识别风格的指纹。这项研究转化为可交付的成果，对实施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，并在此过程中降低举报可疑不法行为的风险。该项目将涉及研究生和本科生。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

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.