The Design of Personal Privacy and Security Risk Scores for Minimizing Consumers' Cognitive Gaps in IoT Settings

Choi, Daeeun
Lowry, Paul
Wang, Alan
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The advent of Internet of Things (IoT) technology exponentially increases the collection of new information types in consumers’ lives from various sensors. However, many consumers do not fully recognize the potential privacy and security risks (PSR) associated with IoT. Those who are aware rarely take action to protect their personal information because of a cognitive gap between PSR and its impact. To address this problem, we propose a design framework for evaluating and quantifying IoT PSRs related to IoT adoption. Grounded in the cognitive dissonance theory (CDT) and information processing theory (IPT), the proposed framework defines IoT PSR scores and proposes a visual representation for improving consumers’ awareness of PSRs. Furthermore, we suggest a PSR control balance theory (PSR-CBT) to explicate the consumers’ two internal power conflicts. The proposed PSR scores can reduce consumers’ cognitive gaps, and thus, help them make informed purchase decisions toward IoT devices and services.
Advances in Design Science Research, cognitive dissonance theory, design science research, internet of things, privacy and security risk control balance theory, privacy and security risk scores
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