Mid-air Authentication Gestures

Aslan, Ilhan; Uhl, Andreas; Meschtscherjakov, Alexander; Tscheligi, Manfred

doi:10.1145/2663204.2663246

Cited by 35 publications

(16 citation statements)

References 28 publications

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“…Hayashi et al proposed biometric authentication using gestural patterns and body segments [19]. Aslan et al exploited individual differences among users in performing mid-air gestures for biometric authentication [3].…”

Section: Authentication Using Gesturesmentioning

confidence: 99%

Just gaze and wave

Abdrabou

Khamis

Eisa³

et al. 2019

Proceedings of the 11th ACM Symposium on Eye Tracking Research &Amp; Applications

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Eye-gaze and mid-air gestures are promising for resisting various types of side-channel attacks during authentication. However, to date, a comparison of the different authentication modalities is missing. We investigate multiple authentication mechanisms that leverage gestures, eye gaze, and a multimodal combination of them and study their resilience to shoulder surfing. To this end, we report on our implementation of three schemes and results from usability and security evaluations where we also experimented with fixed and randomized layouts. We found that the gaze-based approach outperforms the other schemes in terms of input time, error rate, perceived workload, and resistance to observation attacks, and that randomizing the layout does not improve observation resistance enough to warrant the reduced usability. Our work further underlines the significance of replicating previous eye tracking studies using today's sensors as we show significant improvement over similar previously introduced gaze-based authentication systems.

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Section: Authentication Using Gesturesmentioning

confidence: 99%

Just gaze and wave

Abdrabou

Khamis

Eisa³

et al. 2019

Proceedings of the 11th ACM Symposium on Eye Tracking Research &Amp; Applications

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show abstract

“…Most security research on gesture passwords focuses on procedural changes to authentication systems, a simple example being increasing the number of features used in authentication. Direct studies of gesture security have used information theory [34,50], shoulder sur ng [2,13,33,34], or equal error rates [1,2,13,30,34,[48][49][50] between legitimate users and attackers trying to emulate the gesture. The threat model in these scenarios is an attacker performing an observation of the gesture and trying to repeat it.…”

Section: :2 • C Liu Et Almentioning

confidence: 99%

“…Gesture passwords are a recently proposed authentication method for mobile devices that is attracting interest due to their ability to satisfy these usability criteria [1,2,13,30,34,37,[48][49][50]. A gesture in the context of this work, as well as previous work [34,50], is de ned as a series of two-dimensional lines drawn on the surface of a touchscreen with one or more ngers.…”

Section: Introductionmentioning

confidence: 99%

Guessing Attacks on User-Generated Gesture Passwords

Liu

Clark

Lindqvist

2017

Proc. ACM Interact. Mob. Wearable Ubiquitous Technol.

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Touchscreens, the dominant input type for mobile phones, require unique authentication solutions. Gesture passwords have been proposed as an alternative ubiquitous authentication technique. Prior security analysis has relied on inconsistent measurements such as mutual information or shoulder sur ng attacks. We present the rst approach for measuring the security of gestures with guessing attacks that model real-world attacker behavior. Our major contributions are: 1) a comprehensive analysis of the weak subspace for gesture passwords, 2) a method for enumerating the size of the full theoretical gesture password space, 3) a design of a novel guessing attack against user-chosen gestures using a dictionary, and 4) a brute-force attack used for benchmarking the performance of the guessing attack. Our dictionary attack, tested on newly collected user data, achieves a cracking rate of 47.71% after two weeks of computation using 10 9 guesses. This is a di erence of 35.78 percentage points compared to the 11.93% cracking rate of the brute-force attack. In conclusion, users are not taking full advantage of the large theoretical password space and instead choose their gesture passwords from weak subspaces. We urge for further work on addressing this challenge. CCS Concepts: • Security and privacy → Authentication; • Human-centered computing → Gestural input;

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“…The involvement of the hand associated behavioral features has created various types of authentication schemes like hand gestures, keystroke dynamics, mouse related events, and written signature. It's highly preferable in some environments where continuous authentication is required or wearing gloves is mandatory (Aslan, Uhl, Meschtscherjakov, & Tscheligi, 2014).…”

Section: Hand Featuresmentioning

confidence: 99%

“…Motion based gesture verification has been described in (Aslan et al, 2014). It has been able to overcome the finger oil issues related to the recording of the touch based authentication.…”

Section: ) Hand Gesturesmentioning

confidence: 99%

Authentication systems: principles and threats

Abdulkader¹,

Atia²,

Mostafa³

2015

CIS

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Identity manipulation is considered a serious security issue that has been enlarged with the spread of automated systems that could be accessed either locally or remotely. Availability, integrity, and confidentiality represent the basic requirements that should be granted for successful authentication systems. Personality verification has taken multiple forms depending on different possession types. They are divided into knowledge based, token based, and biometric based authentication. The permanent ownership to the human being has increased the chances of deploying biometrics based authentication in highly secure systems. It includes capturing the biological traits, which are physiological or behavioral, extracting the important features and comparing them to the previously stored features that belong to the claimed user. Various kinds of attacks aim to take down the basic requirements at multiple points. This paper describes different types of authentication along with their vulnerable points and threatening attacks. Then it provides more details about the biometric system structure as well as examples of distinguishing biological characteristics, organized by their locations. It shows the performance results of various biometric systems along with the deployed algorithms for different components.

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Mid-air Authentication Gestures

Cited by 35 publications

References 28 publications

Just gaze and wave

Just gaze and wave

Guessing Attacks on User-Generated Gesture Passwords

Authentication systems: principles and threats

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