Event logs capture the execution of business processes in terms of executed activities and their execution context. Since logs contain potentially sensitive information about the individuals involved in the process, they should be pre-processed before being published to preserve the individuals' privacy. However, existing techniques for such pre-processing are limited to a process' control-flow and neglect contextual information, such as attribute values and durations. This thus precludes any form of process analysis that involves contextual factors. To bridge this gap, we introduce PRIPEL, a framework for privacy-aware event log publishing. Compared to existing work, PRIPEL takes a fundamentally different angle and ensures privacy on the level of individual cases instead of the complete log. This way, contextual information as well as the long tail process behaviour are preserved, which enables the application of a rich set of process analysis techniques. We demonstrate the feasibility of our framework in a case study with a real-world event log.

中文翻译：

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PRIPEL：隐私保护事件日志发布，包括上下文信息

事件日志根据已执行的活动及其执行上下文来捕获业务流程的执行。由于日志包含有关参与该过程的个人的潜在敏感信息，因此应在发布之前对其进行预处理，以保护个人隐私。然而，用于此类预处理的现有技术仅限于进程的控制流，而忽略了上下文信息，例如属性值和持续时间。因此，这排除了涉及上下文因素的任何形式的过程分析。为了弥补这一差距，我们引入了 PRIPEL，这是一个隐私感知事件日志发布框架。与现有工作相比，PRIPEL 采取了根本不同的角度，并在个别案例而非完整日志的层面上确保隐私。这条路，上下文信息以及长尾流程行为都被保留下来，这使得应用丰富的流程分析技术成为可能。我们在具有真实事件日志的案例研究中证明了我们框架的可行性。