2020/06/16 by Behnood Momenzadeh, Shakthidhar Gopavaram, Momenzadeh, Behnood +5 · 1 citation
Computer Science · Social Sciences · #Cryptography and Security (cs.CR) #FOS: Computer and information sciences #Information and Cyber Security #Privacy, Security, and Data Protection
paper · pdf · doi:10.48550/arxiv.2006.09531
openalex publication_date 2020/06/16 · openalex created_date 2022/07/18 · openalex updated_date 2026/07/28
In the age of ubiquitous technologies, security- and privacy-focused choices\nhave turned out to be a significant concern for individuals and organizations.\nRisks of such pervasive technologies are extensive and often misaligned with\nuser risk perception, thus failing to help users in taking privacy-aware\ndecisions. Researchers usually try to find solutions for coherently extending\ntrust into our often inscrutable electronic networked environment. To enable\nsecurity- and privacy-focused decision-making, we mainly focused on the realm\nof the mobile marketplace, examining how risk indicators can help people choose\nmore secure and privacy-preserving apps. We performed a naturalistic experiment\nwith N=60 participants, where we asked them to select applications on Android\ntablets with accurate real-time marketplace data. We found that, in aggregate,\napp selections changed to be more risk-averse in the presence of user\nrisk-perception-aligned visual indicators. Our study design and research\npropose practical and usable interactions that enable more informed, risk-aware\ncomparisons for individuals during app selections. We include an explicit\nargument for the role of human decision-making during app selection, beyond the\ncurrent trend of using machine learning to automate privacy preferences after\nselection during run-time.\n