Over the course of the experiments, each participant was presented with three sets of authentication questions multiple times each week.
Such actors could collect enough information from the target to steal his or her identity or wipe out their frequent flyer miles as authentication questions.
In case of single participants, over the course of the experiment, a user was presented with two sets of authentication questions multiple times each week.
The proposed system, however, is limited in generating simple authentication questions based on the arrival and departure time of different people from a smart space.
A stronger level, what you'd find with online banking, asks for more proof of who you are–a phone number, for instance–and asks you knowledge-based authentication questions when you log on from a different computer.
However, the use of pre‐agreed personal authentication questions has been widely criticized and considered to be a weak form of authentication method [1, 4 7] due to various vulnerabilities.
However, the use of such pre-agreed personal authentication questions has been widely criticized and considered to be a weak form of authentication [3 5, 7, 8, 12] due to various vulnerabilities.
Among works that looked into leveraging smartphone usage data and behavior data, Das et al. [9] proposed to generate authentication questions from users' day-to-day activities captured by their smartphones.
To simplify the authentication process and improve the usability of the system, possible answers to each authentication question are presented to the user in visual form by mapping each place to a location on a map generated using Google Maps Street View service(see Fig. 3).
Specifically, the constantly changing information about the daily behavior (e.g., phone calls, location traces) of a person is used to generate one-time authentication questions (e.g., Who did you call around 4 30 pm today?, What apps did you use in the last 24 h?).
