论文标题
Pabau：生物识别API使用的隐私分析
PABAU: Privacy Analysis of Biometric API Usage
论文作者
论文摘要
生物识别数据隐私正在成为大数据时代的许多组织，尤其是在ICT行业中的主要问题，因为在应用程序中很容易利用它。大多数应用程序通过访问通用应用程序编程接口（API）来利用生物识别技术；因此，我们的目标是对它们的用法进行分类。基于行为的分类可能与用户生物识别数据的敏感处理密切相关，因此突出了关键的生物识别数据隐私评估问题。我们提出了Pabau，《生物识别API使用的隐私分析》。 Pabau学习生物特征API中方法的语义特征，并使用它们根据其与隐私相关的行为来检测和分类生物特征API实现的使用。这项技术通过为双方提供一种自动化方法来弥合组织中技术和非技术人员之间的沟通和背景知识差距，以便双方对应用程序中生物识别API的基本行为进行快速了解，以及未来对数据保护官（DPO）的支持（DPO），并通过法律文档（例如进行数据保护影响评估）（DPIA）（DPIA）。
Biometric data privacy is becoming a major concern for many organizations in the age of big data, particularly in the ICT sector, because it may be easily exploited in apps. Most apps utilize biometrics by accessing common application programming interfaces (APIs); hence, we aim to categorize their usage. The categorization based on behavior may be closely correlated with the sensitive processing of a user's biometric data, hence highlighting crucial biometric data privacy assessment concerns. We propose PABAU, Privacy Analysis of Biometric API Usage. PABAU learns semantic features of methods in biometric APIs and uses them to detect and categorize the usage of biometric API implementation in the software according to their privacy-related behaviors. This technique bridges the communication and background knowledge gap between technical and non-technical individuals in organizations by providing an automated method for both parties to acquire a rapid understanding of the essential behaviors of biometric API in apps, as well as future support to data protection officers (DPO) with legal documentation, such as conducting a Data Protection Impact Assessment (DPIA).
