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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Authentication on public terminals e.g. on ATMs and ticket vending machines is a common practice. Due to the weaknesses of the traditional authentication approaches PIN and password, it is possible that other people gain access to the authentication information and thus to the users' personal data. This is mainly due to the physical interaction with the terminals, which enables various manipulations on these devices.In this paper, we present EyePass, an authentication mechanism based on PassShape and eye-gestures that has been created to overcome these problems by eliminating the physical connection to the terminals. EyePass additionally assists the users by providing easy-to-remember PassShapes instead of PINs or passwords. We present the concept, the prototype and the first evaluations performed. Additionally, the future work on the evaluation is outlined and expected results are discussed.

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