计算机科学
事件(粒子物理)
过程(计算)
背景(考古学)
业务流程
集合(抽象数据类型)
桥(图论)
过程采矿
数据挖掘
信息流
情报检索
数据科学
在制品
业务流程管理
程序设计语言
内科学
营销
古生物学
业务
哲学
语言学
物理
生物
医学
量子力学
作者
Stephan A. Fahrenkrog-Petersen,Han van der Aa,Matthias Weidlich
出处
期刊:Springer eBooks
[Springer Nature]
日期:2020-01-01
卷期号:: 111-128
被引量:18
标识
DOI:10.1007/978-3-030-58666-9_7
摘要
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.
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