Recently, the data protection practices of researchers in human-computer interaction and elsewhere have gained attention. Initial results suggest that researchers struggle with anonymization, partly due to a lack of clear, actionable guidance. In this work, we propose simulating re-identification attacks using the approach of red teaming versus blue teaming: a technique commonly employed in security testing, where one team tries to re-identify data, and the other team tries to prevent it. We discuss our experience applying this method to data collected in a mixed-methods study in human-centered privacy. We present usable materials for researchers to apply red teaming when anonymizing and publishing their studies' data.

翻译：近来，人机交互及其他领域研究人员的数据保护实践受到关注。初始结果表明，研究人员在匿名化方面存在困难，部分原因是缺乏清晰且可操作的指导。本文提出利用红队与蓝队对抗的方法模拟重识别攻击：该技术常用于安全测试，其中一方试图重识别数据，另一方则试图阻止此行为。我们讨论了将这一方法应用于以人为中心的隐私研究混合方法数据收集中的实践经验。我们提供了可供研究人员在匿名化并发布研究数据时应用红队策略的实用材料。