Understanding Smartphone Sensor and App Data for Enhancing the Security of Secret Questions
Many web applications provide secondary authentication methods, i.e., secret questions (or password recovery questions), to reset the account password when a user’s login fails. However, the answers to many such secret questions can be easily guessed by an acquaintance or exposed to a stranger that has access to public online tools (e.g., online social networks); moreover, a user may forget her/his answers long after creating the secret questions. Today’s prevalence of smartphones has granted us new opportunities to observe and understand how the personal data collected by smartphone sensors and apps can help create personalized secret questions without violating the users’ privacy concerns. In this paper, we present a Secret-Question based Authentication system, called “Secret-QA”, that creates a set of secret questions on basic of people’s smartphone usage. We develop a prototype on Android smartphones, and evaluate the security of the secret questions by asking the acquaintance/stranger who participate in our user study to guess the answers with and without the help of online tools; meanwhile, we observe the questions’ reliability by asking participants to answer their own questions. Our experimental results reveal that the secret questions related to motion sensors, calendar, app installment, and part of legacy app usage history (e.g., phone calls) have the best memorability for users as well as the highest robustness to attacks.
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Peng Zhao, Kaigui Bian, Tong Zhao, Xintong Song, Jung-Min “Jerry” Park, Xiaoming Li, Fan Ye, Wei Yan, “Understanding Smartphone Sensor and App Data for Enhancing the Security of Secret Questions”, IEEE Transactions on Mobile Computing, 2017.