Personal Feature Extraction via Grip Force Sensors Mounted on a Mobile Phone: Authenticating the User During Key-operation

Personal Feature Extraction via Grip Force Sensors Mounted on a Mobile Phone: Authenticating the User During Key-operation. Iso, T., Horikoshi, T., Tsukamoto, M., & Higuchi, T. In Proceedings of the 11th International Conference on Mobile and Ubiquitous Multimedia, of MUM '12, pages 30:1--30:4, New York, NY, USA, 2012. ACM.

Paper doi abstract bibtex

We propose an algorithm for authenticating the user of a mobile phone from the outputs of pressure sensors during key-operations such as button-pushes. While not intended to replace password identification, it does help in providing the service which is suitable for a user without any his/her specific action. For example, during user's entering key strokes. if a service cloud can recognize user-authentication by analyzing key strokes, then, it can find the optimal services based on the user preference. Our algorithm is based on a statistic probabilistic model based approach; it calculates the probability distribution of the temporal differential values of pressure by Kalman filtering. The captured sensory data is compared to predicted sensory data based on the probability distribution to judge whether the person making the key-operation is the registered owner or not. We implement the proposed system and subject it to feasibility experiments with 10 subjects; its user-authentication accuracy is quite good with a FAR-FRR error rate of only 10[%].

@inproceedings{iso_personal_2012,
	address = {New York, NY, USA},
	series = {{MUM} '12},
	title = {Personal {Feature} {Extraction} via {Grip} {Force} {Sensors} {Mounted} on a {Mobile} {Phone}: {Authenticating} the {User} {During} {Key}-operation},
	isbn = {978-1-4503-1815-0},
	shorttitle = {Personal {Feature} {Extraction} via {Grip} {Force} {Sensors} {Mounted} on a {Mobile} {Phone}},
	url = {http://doi.acm.org/10.1145/2406367.2406404},
	doi = {10.1145/2406367.2406404},
	abstract = {We propose an algorithm for authenticating the user of a mobile phone from the outputs of pressure sensors during key-operations such as button-pushes. While not intended to replace password identification, it does help in providing the service which is suitable for a user without any his/her specific action. For example, during user's entering key strokes. if a service cloud can recognize user-authentication by analyzing key strokes, then, it can find the optimal services based on the user preference. Our algorithm is based on a statistic probabilistic model based approach; it calculates the probability distribution of the temporal differential values of pressure by Kalman filtering. The captured sensory data is compared to predicted sensory data based on the probability distribution to judge whether the person making the key-operation is the registered owner or not. We implement the proposed system and subject it to feasibility experiments with 10 subjects; its user-authentication accuracy is quite good with a FAR-FRR error rate of only 10[\%].},
	urldate = {2014-05-13TZ},
	booktitle = {Proceedings of the 11th {International} {Conference} on {Mobile} and {Ubiquitous} {Multimedia}},
	publisher = {ACM},
	author = {Iso, Toshiki and Horikoshi, Tsutomu and Tsukamoto, Masakatsu and Higuchi, Takeshi},
	year = {2012},
	pages = {30:1--30:4}
}

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