Privacy Engineering in Smart Home (SH) Systems: A Comprehensive Privacy Threat Analysis and Risk Management Approach
CoRR(2024)
摘要
Addressing trust concerns in Smart Home (SH) systems is imperative due to the
limited study on preservation approaches that focus on analyzing and evaluating
privacy threats for effective risk management. While most research focuses
primarily on user privacy, device data privacy, especially identity privacy, is
almost neglected, which can significantly impact overall user privacy within
the SH system. To this end, our study incorporates privacy engineering (PE)
principles in the SH system that consider user and device data privacy. We
start with a comprehensive reference model for a typical SH system. Based on
the initial stage of LINDDUN PRO for the PE framework, we present a data flow
diagram (DFD) based on a typical SH reference model to better understand SH
system operations. To identify potential areas of privacy threat and perform a
privacy threat analysis (PTA), we employ the LINDDUN PRO threat model. Then, a
privacy impact assessment (PIA) was carried out to implement privacy risk
management by prioritizing privacy threats based on their likelihood of
occurrence and potential consequences. Finally, we suggest possible privacy
enhancement techniques (PETs) that can mitigate some of these threats. The
study aims to elucidate the main threats to privacy, associated risks, and
effective prioritization of privacy control in SH systems. The outcomes of this
study are expected to benefit SH stakeholders, including vendors, cloud
providers, users, researchers, and regulatory bodies in the SH systems domain.
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