论文标题
用户关注上下文感知推理系统中隐私的关注
Users' Concern for Privacy in Context-Aware Reasoning Systems
论文作者
论文摘要
上下文感知的推理系统允许通过汇总看似无关的来源的数据来绘制用户行为和生理状况的复杂推断。我们进行了一项一般人口在线调查，以评估用户对这些系统收集的数据隐私的关注。我们发现，与生理传感器相比，人们更关心第三方访问环境传感器收集的数据。参与者还指出，与熟悉的第三方（例如亲戚）相比，对陌生的第三方（例如私人公司）更加关注。我们进一步发现，这些问题是可以预测的，并且（在较小程度上）受到人们对从这些类型的数据以及计算机科学背景中从这些类型的数据中推断多少的信念的影响。
Context-aware reasoning systems allow drawing sophisticated inferences about users' behaviour and physiological condition, by aggregating data from seemingly unrelated sources. We conducted a general population online survey to evaluate users' concern about the privacy of data gathered by these systems. We found that people are more concerned about third parties accessing data gathered by environmental sensors as compared to physiological sensors. Participants also indicated greater concern about unfamiliar third parties (e.g., private companies) as opposed to familiar third parties (e.g., relatives). We further found that these concerns are predicted and (to a lesser degree) causally affected by people's beliefs about how much can be inferred from these types of data, as well as by their background in computer science.
