SysPal: System-Guided Pattern Locks for Android

Cho, Geumhwan; Huh, Jun Ho; Cho, Junsung; Oh, Seongyeol; Song, Youngbae; Kim, Hyoungshick

doi:10.1109/sp.2017.61

Cited by 34 publications

(57 citation statements)

References 24 publications

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“…However, the objective of our study was to determine whether informing users about connectivity rules through the highlighting mechanism had any impact on their pattern choices which we found to be statistically significant with this small sample. We note that our sample size (99 participants) is larger than that of Cho et al lab study (46 participants) [13].…”

Section: Limitationsmentioning

confidence: 66%

“…Moreover, the proportion of SysPal patterns that were cracked in 20 attempts are: 9.97% (1-dot), 9.36% (2-dot) and 14.11% (3-dot). These numbers suggest (also stated in [13]) that mandating too many points could potentially reduce the overall password space. Further, for patterns created using TinPal, the proportion of patterns cracked in 20 attempts is 0% (and 4% using ASIACCS'17 dataset [24]).…”

Section: A Android Pattern Lockmentioning

confidence: 84%

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TinPal: An Enhanced Interface for Pattern Locks

Tupsamudre¹,

Vaddepalli²,

Banahatti³

et al. 2018

Proceedings 2018 Workshop on Usable Security

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Pattern lock scheme in which users connect 4-9 dots in a 3 × 3 grid is one of the most popular authentication methods on mobile devices. However, numerous research studies show that users choose patterns from a small space which makes them vulnerable to a variety of attacks such as guessing attacks, shoulder-surfing attacks and smudge attacks.In this work, we enhance the existing 3 × 3 interface with a visual indicator mechanism and demonstrate how this slight modification can influence users' pattern choices, thereby improving the security of the pattern lock scheme. We refer to this enhanced interface as TinPal. As users draw their pattern, TinPal highlights the next set of unconnected dots that can be reached from the currently connected dot. We gauge the impact of this highlighting mechanism on users' pattern choices by performing a comparative study of two groups, where one group creates pattern using the existing interface while the other group creates pattern using TinPal. The study results show that participants who used TinPal created more secure patterns than participants who used the existing interface.

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Section: Limitationsmentioning

confidence: 66%

Section: A Android Pattern Lockmentioning

confidence: 84%

TinPal: An Enhanced Interface for Pattern Locks

Tupsamudre¹,

Vaddepalli²,

Banahatti³

et al. 2018

Proceedings 2018 Workshop on Usable Security

View full text Add to dashboard Cite

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“…This bias can be used by adversaries to improve their guess on unlock patterns. Figure 1 gives the 12 most common unlock patterns in the real world, according to a recent empirical study [9]. In our user study, we focus on stealing these most likely patterns only, for the following reasons.…”

Section: Phone Unlock Patternsmentioning

confidence: 99%

“…We believe our design choice is sufficient for the purpose. Figure 1: The twelve most popular unlock patterns according to [9]. An unlock pattern connects a number of dots, and it can be decomposed into several strokes separated by inflections.…”

Section: Phone Unlock Patternsmentioning

confidence: 99%

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SonarSnoop: active acoustic side-channel attacks

Cheng

Bağcı

Roedig

et al. 2019

Int. J. Inf. Secur.

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We report the first active acoustic side-channel attack. Speakers are used to emit human inaudible acoustic signals and the echo is recorded via microphones, turning the acoustic system of a smart phone into a sonar system. The echo signal can be used to profile user interaction with the device. For example, a victim's finger movements can be inferred to steal Android unlock patterns. In our empirical study, the number of candidate unlock patterns that an attacker must try to authenticate herself to a Samsung S4 phone can be reduced by up to 70% using this novel acoustic side-channel. The attack is entirely unnoticeable to victims. Our approach can be easily applied to other application scenarios and device types. Overall, our work highlights a new family of security threats.

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