Measuring user confidence in smartphone security and privacy

By Erika Chin, Adrienne Porter Felt, Vyas Sekar, David A. Wagner. Symposium On Usable Privacy and Security, 2012

394 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/a054f6a9c9c37d13c06318e183d851bbbcd71a97

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Citations in the corpus

Machine Heuristic: When We Trust Computers More than Humans with Our Personal Information (2019, background): “Specifically, various contextual factors underlying online and mobile contexts, such as users’ time constraints, lack of technological efficacy [7], and information overload [23], make it difficult to comply with the privacy protection ideals that users want to attain.”
Modeling Users' Mobile App Privacy Preferences: Restoring Usability in a Sea of Permission Settings (2014, background): “A great deal of past work analyzing smartphone apps has focused on developing useful techniques and tools to detect and manage leakage of sensitive personal information [8-10, 14-26] or studying how users react to these usages [6, 13, 27, 28].”
Imagined Connectivities: Synthesized Conceptions of Public Wi-Fi in Urban India (2017, background): “Less attention is paid to the choice of Wi-Fi non-use that might result from such misunderstandings; however, see [13]).”
Device Switching in Online Purchasing: Examining the Strategic Contingencies (2018, background): “As a consequence, they may perceive lower risks than less experienced customers perceive (Chin et al. 2012; Moorthy, Ratchford, and Talukdar 1997).”
The relationship between trust in AI and trustworthy machine learning technologies (2019, background): “situations that their data is being collected [22].”
Interactions With Robots: The Truths We Reveal About Ourselves (2017, background): “The concerns people currently have over security and privacy on digital devices (Chin et al. 2012) are likely to transfer to robots.”
Expectation and purpose: understanding users' mental models of mobile app privacy through crowdsourcing (2012, background): “For example, Felt et al. [28], Chin et al. [27], and Egelman et al [36] conducted surveys and interviews to understand mobile users’ mobile privacy concerns as well as their over understanding of the choices they are expected to make.”