Tapprints: your finger taps have fingerprints
By Emiliano Miluzzo, Alex Varshavsky, Suhrid Balakrishnan, Romit Roy Choudhury. ACM SIGMOBILE International Conference on Mobile Systems, Applications, and Services, 2012
360 citations recorded by the source corpus.
Subfields: Information Systems, Signal Processing
View Paper: https://www.semanticscholar.org/paper/7f8213487ef7910c74d8494b1609a591def2461e
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Information Systems
- Daniel Gruss
- Moritz Lipp
- Clémentine Maurice
- Stefan Mangard
- Prateek Mittal
- Supriyo Chakraborty
- Nitesh Saxena
- Changchang Liu
In Signal Processing
- Daniel Gruss
- Moritz Lipp
- Clémentine Maurice
- Stefan Mangard
- Prateek Mittal
- Supriyo Chakraborty
- Changchang Liu
- Romit Roy Choudhury
Citations in the corpus
- ARMageddon: Cache Attacks on Mobile Devices (2015, background): “, the accelerometer and the gyroscope [8,12,13,40,60] or the ambient-light sensor [50].”
- Spearphone: A Speech Privacy Exploit via Accelerometer-Sensed Reverberations from Smartphone Loudspeakers (2019, background): “TapPrints [9] further shows that the tap prints on the smartphone touchscreen can be characterized by accelerometers and gyroscopes on the smartphone to identify users.”
- AccelPrint: Imperfections of Accelerometers Make Smartphones Trackable (2014, background): “went one step ahead to develop TapPrint [45] that uses gyroscopic and accelerometer reading in combination to infer the location of tapping on tablet and smartphone keyboards.”
- DeepSense: A Unified Deep Learning Framework for Time-Series Mobile Sensing Data Processing (2016, background): “These capabilities serve diverse application areas including health and wellbeing [20, 33, 24], tracking and imaging [25, 46], mobile security [29, 41], and vehicular road sensing [17, 19, 45].”
- Rocking Drones with Intentional Sound Noise on Gyroscopic Sensors (2015, methodology): “Because a gyroscope can be used to measure changes in tilt, orientation, and rotation, it can be used to steal a smartphone user’s keystroke information, such as unlock passwords, banking passwords, and credit card numbers [36, 47].”
- DEEProtect: Enabling Inference-based Access Control on Mobile Sensing Applications (2017, background): “, Passwords or PINs) (sensitive inference) [91], [62], [13], [59].”
- You Are How You Touch: User Verification on Smartphones via Tapping Behaviors (2014, background): “However, given the same mobile device, behavioral biometrics tend to be less sensitive to the surrounding environmental factors like darkness or noise.”