Consent Management in Data Workflows: A Graph Problem

Dorota Filipczuk, E. Gerding, G. Konstantinidis
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Abstract

Inmoderndataprocessing systemsusersexpectaserviceprovider to automatically respect their consent in all data processing within the service. However, data may be processed for many different purposes by several layers of algorithms that create complex workflows. To date, there is no existing approach to automatically satisfy fine-grained privacy constraints of a user in a way which optimises the service provider’s gains from processing. In this paper, we model a data processing workflow as a graph. User constraints and processing purposes are pairs of vertices which need to be disconnected in this graph. We propose heuristics and algorithms while at the same time we show that, in general, this problem is NP-hard. We discuss the optimality versus efficiency of our algorithms and evaluate them using synthetically generated data. On the practical side, our algorithms can provide a nearly optimal solution in the face of tens of constraints and graphs of thousands of nodes, in a few seconds.
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数据工作流中的同意管理:一个图问题
在现代数据处理系统中,用户期望服务提供商在服务内的所有数据处理中自动尊重他们的同意。然而,数据可以通过创建复杂工作流的几层算法来处理许多不同的目的。到目前为止,还没有一种现有的方法可以自动满足用户的细粒度隐私约束,从而优化服务提供商从处理中获得的收益。在本文中,我们将数据处理工作流建模为一个图。用户约束和处理目的是图中需要断开连接的顶点对。我们提出了启发式和算法,同时我们表明,一般来说,这个问题是np困难的。我们讨论了算法的最优性和效率,并使用合成生成的数据对它们进行了评估。在实际方面,我们的算法可以在几秒钟内提供面对数十个约束和数千个节点的图的近乎最优解决方案。
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