The present study investigates to what degree individual differences can predict frequency and duration of actual behaviour, manifested in mobile application (app) usage on smartphones. In particular, this work focuses on the identification of stable associations between personality on the factor and facet level, fluid intelligence, demography and app usage in 16 distinct categories. A total of 137 subjects (87 women and 50 men), with an average age of 24 (SD = 4.72), participated in a 90‐min psychometric lab session as well as in a subsequent 60‐day data logging study in the field. Our data suggest that personality traits predict mobile application usage in several specific categories such as communication, photography, gaming, transportation and entertainment. Extraversion, conscientiousness and agreeableness are better predictors of mobile application usage than basic demographic variables in several distinct categories. Furthermore, predictive performance is slightly higher for single factor—in comparison with facet‐level personality scores. Fluid intelligence and demographics additionally show stable associations with categorical app usage. In sum, this study demonstrates how individual differences can be effectively related to actual behaviour and how this can assist in understanding the behavioural underpinnings of personality. Copyright © 2017 European Association of Personality Psychology

This paper presents BoD Shapes, a novel authentication method for smartphones that uses the back of the device for input. We argue that this increases the resistance to shoulder surfing while remaining reasonably fast and easy-to-use. We performed a user study (n = 24) comparing BoD Shapes to PIN authentication, Android grid unlock, and a front version of our system. Testing a front version allowed us to directly compare performance and security measures between front and back authentication. Our results show that BoD Shapes is significantly more secure than the three other approaches. While performance declined, our results show that BoD Shapes can be very fast (up to 1.5 seconds in the user study) and that learning effects have an influence on its performance. This indicates that speed improvements can be expected in long-term use.

Authentication methods can be improved by considering implicit, individual behavioural cues. In particular, verifying users based on typing behaviour has been widely studied with physical keyboards. On mobile touchscreens, the same concepts have been applied with little adaptations so far. This paper presents the first reported study on mobile keystroke biometrics which compares touch-specific features between three different hand postures and evaluation schemes. Based on 20.160 password entries from a study with 28 participants over two weeks, we show that including spatial touch features reduces implicit authentication equal error rates (EER) by 26.4 -36.8% relative to the previously used temporal features. We also show that authentication works better for some hand postures than others. To improve applicability and usability, we further quantify the influence of common evaluation assumptions: known attacker data, training and testing on data from a single typing session, and fixed hand postures. We show that these practices can lead to overly optimistic evaluations. In consequence, we describe evaluation recommendations, a probabilistic framework to handle unknown hand postures, and ideas for further improvements.

In this paper, we discuss the use of eye-gaze tracking technology for mobile phones. In particular we investigate how gaze interaction can be used to control applications on handheld devices. In contrast to eye-tracking systems for desktop computers, mobile devices imply several problems like the intensity of light for outdoor use and calibration issues. Therefore, we compared two different approaches for controlling mobile phones with the eyes: standard eye-gaze interaction based on the dwell-time method and gaze gestures. Gaze gestures are a new concept, which we think has the potential to overcome many of these problems. We conducted a user study to see whether people are able to interact with applications using these approaches. The results confirm that eye-gaze interaction for mobile phones is attractive for the users and that the gaze gestures are an alternative method for eye-gaze based interaction.

Personal identification numbers (PINs) are one of the most common ways of electronic authentication these days and used in a wide variety of applications, especially in ATMs (cash machines). A non-marginal amount of tricks are used by criminals to spy on these numbers to gain access to the owners' valuables. Simply looking over the victims' shoulders to get in possession of their PINs is a common one. This effortless but effective trick is known as shoulder surfing. Thus, a less observable PIN entry method is desirable. In this work, we evaluate three different eye gaze interaction methods for PINentry, all resistant against these common attacks and thus providing enhanced security. Besides the classical eye input methods we also investigate a new approach of gaze gestures and compare it to the well known classical gaze-interactions. The evaluation considers both security and usability aspects. Finally we discuss possible enhancements for gaze gestures towards pattern based identification instead of number sequences.

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Most of today's smartphones and tablet computers feature touchscreens as the main way of interaction. By using these touchscreens, oily residues of the users' fingers, smudge, remain on the device's display. As this smudge can be used to deduce formerly entered data, authentication tokens are jeopardized. Most notably, grid-based authentication methods, like the Android pattern scheme are prone to such attacks.Based on a thorough development process using low fidelity and high fidelity prototyping, we designed three graphicbased authentication methods in a way to leave smudge traces, which are not easy to interpret. We present one gridbased and two randomized graphical approaches and report on two user studies that we performed to prove the feasibility of these concepts. The authentication schemes were compared to the widely used Android pattern authentication and analyzed in terms of performance, usability and security. The results indicate that our concepts are significantly more secure against smudge attacks while keeping high input speed.

In this paper, we present SwiPIN, a novel authentication system that allows input of traditional PINs using simple touch gestures like up or down and makes it secure against human observers. We present two user studies which evaluated different designs of SwiPIN and compared it against traditional PIN. The results show that SwiPIN performs adequately fast (3.7 s) to serve as an alternative input method for risky situations. Furthermore, SwiPIN is easy to use, significantly more secure against shoulder surfing attacks and switching between PIN and SwiPIN feels natural.