论文标题
因果（和反事实）推理可以改善隐私威胁建模吗？
Can Causal (and Counterfactual) Reasoning improve Privacy Threat Modelling?
论文作者
论文摘要
因果问题经常在我们的日常活动中渗透。通过因果推理和反事实直觉，隐私威胁不仅可以缓解，而且可以阻止。在本文中，我们讨论什么是因果关系和反事实推理，以及如何将其应用于隐私威胁建模（PTM）。我们认为，PTM的未来取决于我们如何通过因果关系和反合想象网络安全威胁和事件。
Causal questions often permeate in our day-to-day activities. With causal reasoning and counterfactual intuition, privacy threats can not only be alleviated but also prevented. In this paper, we discuss what is causal and counterfactual reasoning and how this can be applied in the field of privacy threat modelling (PTM). We believe that the future of PTM relies on how we can causally and counterfactually imagine cybersecurity threats and incidents.
