论文标题
GDPR下的隐私文件合规生成：实施自动化和机器学习的路线图
Compliance Generation for Privacy Documents under GDPR: A Roadmap for Implementing Automation and Machine Learning
论文作者
论文摘要
如今，最著名的研究通过以消费者为中心和公共调节的方法来解决遵守数据保护法。我们将这一观点转变为Privatech项目，将专注于公司和律师事务所作为合规代理。为了遵守数据保护法，数据处理器必须执行责任措施，以评估和记录与隐私文件和隐私惯例有关的依从性。在本文中，我们一方面调查了当前关于GDPR自动化的研究，另一方面，公司面临的运营挑战符合GDPR，这可能会受益于新的自动化形式。我们试图弥合差距。我们通过确定合规性问题，将其分解为可以通过机器学习和自动化解决的任务，并提供有关Privatech项目中相关发展的注释，从而为合规性评估和生成提供路线图。
Most prominent research today addresses compliance with data protection laws through consumer-centric and public-regulatory approaches. We shift this perspective with the Privatech project to focus on corporations and law firms as agents of compliance. To comply with data protection laws, data processors must implement accountability measures to assess and document compliance in relation to both privacy documents and privacy practices. In this paper, we survey, on the one hand, current research on GDPR automation, and on the other hand, the operational challenges corporations face to comply with GDPR, and that may benefit from new forms of automation. We attempt to bridge the gap. We provide a roadmap for compliance assessment and generation by identifying compliance issues, breaking them down into tasks that can be addressed through machine learning and automation, and providing notes about related developments in the Privatech project.
