Completely Automated Public Physical test to tell Computers and Humans Apart: A usability study on mobile devices

Guerar, Meriem; Merlo, Alessio; Migliardi, Mauro

doi:10.1016/j.future.2017.03.012

Cited by 18 publications

(12 citation statements)

References 23 publications

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“…Computer and Humans Apart (CAPPCHA) [11,12], which, in order to spot the presence of automations, leverages the physical nature of human subjects instead of requiring them to tackle a complex cognitive task. In doing this, CAPPCHA asks the user to tilt the smartphone to a specific degree to be recognized as a human.…”

Section: Accepted Manuscriptmentioning

confidence: 99%

“…Beside acting as standard CAPTCHA, CAPPCHA can be used to enhance the security of PIN authentication against mobile malware. In [12], authors presented an extended usability study of CAPPCHA based on 200 volunteers. Their experiment results show that CAPPCHA is easy to understand and use, and it shows a high acceptance rate by the users.…”

Section: Captcha Strengthened Authentication and Its Alternativesmentioning

confidence: 99%

“…Strong taps present variation peaks with more amplitude than the gentle taps. Similar to CAPPCHA [11,12], the rationale behind our work is that malware cannot physically move the device. However,…”

Section: The Invisible Cappcha Conceptmentioning

confidence: 99%

“…Invisible CAPPCHA leverages that idea in a fully transparent way that requires no additional task or challenge to be performed or tackled by the user; this is a major difference from CAPPCHA [11,12], which asks the user to tilt the device to a specific degree as a challenge. As the phone movement caused by user's finger tap is small, compared to tilting the smartphone action, we conducted several experiments to prove that the micro-movements generated by the user tapping actions can be identified with a high level of accuracy and, at the same time, that such activity cannot be simulated by malware leveraging unsecured hardware such as the smartphone's vibration motor.…”

Section: Accepted Manuscriptmentioning

confidence: 99%

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Invisible CAPPCHA: A usable mechanism to distinguish between malware and humans on the mobile IoT

Guerar

Merlo

Migliardi

et al. 2018

Computers & Security

Self Cite

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Smartphone devices are often assuming the role of edge systems in mobile IoT scenarios and the access to cloud-based services through smartphones, for transmitting multiple sensory data related to human activities, often implying some lawful evidence, has become increasingly common. Thus the need for protecting such transactions from abuses and frauds based on automation techniques is now a critical issue. The most widely adopted method to prevent unauthorized access and abuse of a service by malicious software automation is CAPTCHA. However, trying to strengthen CAPTCHA resilience to automated attacks has led to challenges that, while still being vulnerable, are both difficult and unpleasant for humans. Hence, the strong need for a mechanism that is both secure and usable. In this paper, we present Invisible CAPPCHA, a mechanism that, leveraging trusted sensors embedded in a secure element located on a smartphone is capable of separating humans from computers in a way that is completely transparent to users. Furthermore, as no challenge is required, no additional time is needed and the user cannot fail it by mistake. Compared to the state of the art, our proposal is both secure and more user friendly, lending itself optimally to secure mobile cloud services.

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Section: Accepted Manuscriptmentioning

confidence: 99%

Section: Captcha Strengthened Authentication and Its Alternativesmentioning

confidence: 99%

Section: The Invisible Cappcha Conceptmentioning

confidence: 99%

Section: Accepted Manuscriptmentioning

confidence: 99%

See 2 more Smart Citations

Invisible CAPPCHA: A usable mechanism to distinguish between malware and humans on the mobile IoT

Guerar

Merlo

Migliardi

et al. 2018

Computers & Security

Self Cite

View full text Add to dashboard Cite

show abstract

“…In fact, it is an interdisciplinary research, involving cognitive science, biomedicine, information science and other fields. Harmonious natural human-computer interaction [1][2][3] and emotional computing technology [4] research is inseparable from emotional psychological theory and methods. Amongst the methods of emotional representation, the classical method aims to cluster the emotional vocabulary and obtain a qualitative representation of the emotion category.…”

Section: Introductionmentioning

confidence: 99%

Meta-KANSEI Modeling with Valence-Arousal fMRI Dataset of Brain

et al. 2018

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Securing PIN‐based authentication in smartwatches with just two gestures

Guerar

Migliardi

Palmieri

et al. 2019

Concurrency and Computation

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Summary Smartwatches are becoming increasingly ubiquitous as they offer new capabilities to develop sophisticated applications that make daily life easier and more convenient for consumers. The services provided include applications for mobile payment, ticketing, identification, access control, etc. While this makes modern smartwatches very powerful devices, it also makes them very attractive targets for attackers. Indeed, PINs and Pattern Lock have been widely used in smartwatches for user authentication. However, such authentication methods are not robust against various forms of cybersecurity attacks, such as side channel, phishing, smudge, shoulder surfing, and video‐recording attacks. Moreover, the recent adoption of hardware‐based solutions, like the Trusted Execution Environment (TEE), can mitigate only partially such problems. Thus, the user's security and privacy are at risk without a strong authentication scheme in place. In this work, we propose 2GesturePIN, a new authentication framework that allows users to authenticate securely to their smartwatches and related sensitive services through solely two gestures. 2GesturePIN leverages the rotating bezel or crown, which are the most intuitive ways to interact with a smartwatch, as a dedicated hardware. 2GesturePIN improves the resilience of the regular PIN authentication method against state‐of‐the‐art cybersecurity attacks while maintaining a high level of usability.

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Completely Automated Public Physical test to tell Computers and Humans Apart: A usability study on mobile devices

Abstract: performance and the usability of CAPPCHA involving a high number of physical users, and we provide comparisons of CAPPCHA with existing flavors of CAPTCHA.

Cited by 18 publications

References 23 publications

Invisible CAPPCHA: A usable mechanism to distinguish between malware and humans on the mobile IoT

Invisible CAPPCHA: A usable mechanism to distinguish between malware and humans on the mobile IoT

Meta-KANSEI Modeling with Valence-Arousal fMRI Dataset of Brain

Securing PIN‐based authentication in smartwatches with just two gestures

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