This paper studies the security and memorability of free-form multitouch gestures for mobile authentication. Towards this end, we collected a dataset with a generate-test-retest paradigm where participants (N=63) generated free-form gestures, repeated them, and were later retested for memory. Half of the participants decided to generate one-finger gestures, and the other half generated multi-finger gestures. Although there has been recent work on template-based gestures, there are yet no metrics to analyze security of either template or free-form gestures. For example, entropy-based metrics used for text-based passwords are not suitable for capturing the security and memorability of free-form gestures. Hence, we modify a recently proposed metric for analyzing information capacity of continuous full-body movements for this purpose. Our metric computed estimated mutual information in repeated sets of gestures. Surprisingly, one-finger gestures had higher average mutual information. Gestures with many hard angles and turns had the highest mutual information. The best-remembered gestures included signatures and simple angular shapes. We also implemented a multitouch recognizer to evaluate the practicality of free-form gestures in a real authentication system and how they perform against shoulder surfing attacks. We conclude the paper with strategies for generating secure and memorable free-form gestures, which present a robust method for mobile authentication.
Finally, on non-security related work, @cite_2 studied the information capacity of continuous full-body movements. Our metric is motivated by their work. Specifically, they did not study 2D gestures or their security and memorability or use for an authentication system. When asked to create gestures for non-security purposes, previous work @cite_17 @cite_26 indicates that people tend to repeat gestures that are seen on a daily basis and are context-dependent (e.g. that the gestures people perform are dependent on whether they are directing someone to perform a task or receiving directions on a task).
@cite_26 @cite_17 @cite_2
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This paper explores how interaction with systems using touchless gestures can be made intuitive and natural. Analysis of 912 video clips of gesture production from a user study of 16 subjects communicating transitive actions (manipulation of objects with or without external tools) indicated that 1) dynamic pantomimic gestures where imagined tool object is explicitly held are performed more intuitively and easily than gestures where a body part is used to represent the tool object or compared to static hand poses and 2) gesturing while communicating the transitive action as how the user habitually performs the action (pantomimic action) is perceived to be easier and more natural than gesturing while communicating it as an instruction. These findings provide guidelines for the characteristics of gestures and user mental models one must consciously be concerned with when designing and implementing gesture vocabularies of touchless interaction. We present a novel metric for information capacity of full-body movements. It accommodates HCI scenarios involving continuous movement of multiple limbs. Throughput is calculated as mutual information in repeated motor sequences. It is affected by the complexity of movements and the precision with which an actor reproduces them. Computation requires decorrelating co-dependencies of movement features (e.g., wrist and elbow) and temporal alignment of sequences. HCI researchers can use the metric as an analysis tool when designing and studying user interfaces.