Smartphones store a significant amount of personal and private information, and are playing an increasingly important role in people's lives. It is important for authentication techniques to be more resistant against two known attacks called shoulder surfing and smudge attacks. In this work, we propose a new technique called 3D Pattern. Our 3D Pattern technique takes advantage of a new input paradigm called pre-touch, which could soon allow smartphones to sense a user's finger position at some distance from the screen. We implement the technique and evaluate it in a pilot study (n=6) by comparing it to PIN and pattern locks. Our results show that although our prototype takes about 8 seconds to authenticate, it is immune to smudge attacks and promises to be more resistant to shoulder surfing.
Many recent works on touchscreen interactions have started exploring pre-touch information; that is, positional information about the user's hands or fingers before making contact with the screen. For example, with TouchCuts and TouchZoom, @cite_21 used pre-touch finger distance to expand nearby targets on screen, facilitating easier target selection. This general approach has not yet been explored in the context of authentication techniques resistant to shoulder surfing.
@cite_21
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Touchscreens continue to advance including progress towards sensing fingers proximal to the display. We explore this emerging pre-touch modality via a self-capacitance touchscreen that can sense multiple fingers above a mobile device, as well as grip around the screen's edges. This capability opens up many possibilities for mobile interaction. For example, using pre-touch in an anticipatory role affords an "ad-lib interface" that fades in a different UI--appropriate to the context--as the user approaches one-handed with a thumb, two-handed with an index finger, or even with a pinch or two thumbs. Or we can interpret pre-touch in a retroactive manner that leverages the approach trajectory to discern whether the user made contact with a ballistic vs. a finely-targeted motion. Pre-touch also enables hybrid touch + hover gestures, such as selecting an icon with the thumb while bringing a second finger into range to invoke a context menu at a convenient location. Collectively these techniques illustrate how pre-touch sensing offers an intriguing new back-channel for mobile interaction. Although touch-screen laptops are increasing in popularity, users still do not comfortably rely on touch in these environments, as current software interfaces were not designed for being used by the finger. In this paper, we first demonstrate the benefits of using touch as a complementary input modality along with the keyboard and mouse or touchpad in a laptop setting. To alleviate the frustration users experience with touch, we then design two techniques, TouchCuts, a single target expansion technique, and ,i>TouchZoom, i>, a multiple target expansion technique. Both techniques facilitate the selection of small icons, by detecting the finger proximity above the display surface, and expanding the target as the finger approaches. In a controlled evaluation, we show that our techniques improve performance in comparison to both the computer mouse and a baseline touch-based target acquisition technique. We conclude by discussing other application scenarios that our techniques support. We present the design and evaluation of TapTap and MagStick, two thumb interaction techniques for target acquisition on mobile devices with small touch-screens. These two techniques address all the issues raised by the selection of targets with the thumb on small tactile screens: screen accessibility, visual occlusion and accuracy. A controlled experiment shows that TapTap and MagStick allow the selection of targets in all areas of the screen in a fast and accurate way. They were found to be faster than four previous techniques except Direct Touch which, although faster, is too error prone. They also provided the best error rate of all tested techniques. Finally the paper also provides a comprehensive study of various techniques for thumb based touch-screen target selection. A method of reducing the perceived latency of touch input by employing a model to predict touch events before the finger reaches the touch surface is proposed. A corpus of 3D finger movement data was collected, and used to develop a model capable of three granularities at different phases of movement: initial direction, final touch location, time of touchdown. The model is validated for target distances >= 25.5cm, and demonstrated to have a mean accuracy of 1.05cm 128ms before the user touches the screen. Preference study of different levels of latency reveals a strong preference for unperceived latency touchdown feedback. A form of 'soft' feedback, as well as other uses for this prediction to improve performance, is proposed.