Chang, Jian-PengZheng, Hong-LiangMardani, AbbasPedrycz, WitoldChen, Zhen-Song2024-05-192024-05-1920240018-93911558-0040https://doi.org10.1109/TEM.2024.3351703https://hdl.handle.net/20.500.12713/5095Evaluating the holistic privacy risk (HPR) presented by a smart home ecosystem (SHE), encompassing both internal and external entities that may be targeted by different adversaries seeking to compromise users' privacy, can enhance the comprehensive understanding of the privacy risk landscape within the SHE. This matter is influenced by the complexity of risk surroundings, the diverse perspectives of users toward privacy, and the lack of historical data. Unfortunately, existing literature falls short in addressing these factors. To fill the gap, this article develops an innovative capability-oriented model that accommodates epistemic uncertainty and wisdom of crowds (WoC), designed to assist smart home device manufacturers in accurately assessing HPR posed by their SHEs. The model presents a method for representing subjective judgments that captures epistemic uncertainty and a technique for weighting individual judgments to mitigate overconfidence bias, thus effectively harnessing WoC. In addition, this model features two specialized methods: one for quantifying HPR and another for prioritizing associated single risks, both tailored to operate effectively within uncertain context. These innovative methods are versatile and can be applied to various risk assessment scenarios, especially where historical data are not available. The practicality and effectiveness of our model are demonstrated through a detailed case study.eninfo:eu-repo/semantics/closedAccessEpistemic UncertaintyHolistic Privacy Risk (Hpr) AssessmentSmart Home Ecosystem (She)Wisdom Of Crowds (Woc)Article7153725390WOS:0011680433000042-s2.0-85182360165N/A10.1109/TEM.2024.3351703Q1