Confidence and Risk Estimation Plugins for Multi-Modal Authentication on Mobile Devices using CORMORANT

Daniel Hintze; Muhammad Muaaz; Rainhard D. Findling; Sebastian Scholz; Eckhard Koch; René Mayrhofer

doi:10.1145/2837126.2843845

Confidence and Risk Estimation Plugins for Multi-Modal Authentication on Mobile Devices using CORMORANT

Daniel Hintze, Muhammad Muaaz, Rainhard D. Findling, Sebastian Scholz, Eckhard Koch, René Mayrhofer

Not published at Aalto University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

5 Citations (Scopus)

Abstract

Mobile devices, ubiquitous in modern lifestyle, embody and provide convenient access to our digital lives. Being small and mobile, they are easily lost or stole, therefore require strong authentication to mitigate the risk of unauthorized access. Common knowledge-based mechanism like PIN or pattern, however, fail to scale with the high frequency but short duration of device interactions and ever increasing number of mobile devices carried simultaneously. To overcome these limitations, we present CORMORANT, an extensible framework for risk-aware multi-modal biometric uthentication across multiple mobile devices that offers increased security and requires less user interaction.

Original language	English
Title of host publication	13th International Conference on Advances in Mobile Computing and Multimedia, MoMM 2015 - Proceedings
Editors	Ismail Khalil, Matthias Steinbauer, Liming Chen, Gabriele Anderst-Kotsis
Publisher	ACM
Pages	384-388
Number of pages	5
ISBN (Electronic)	9781450334938
DOIs	https://doi.org/10.1145/2837126.2843845
Publication status	Published - 11 Dec 2015
MoE publication type	A4 Article in a conference publication
Event	International Conference on Advances in Mobile Computing and Multimedia - Brussels, Belgium Duration: 11 Dec 2015 → 13 Dec 2015 Conference number: 13

Conference

Conference	International Conference on Advances in Mobile Computing and Multimedia
Abbreviated title	MoMM
Country	Belgium
City	Brussels
Period	11/12/2015 → 13/12/2015

Keywords

biometrics
multi-modal authentication
risk assessment

Access to Document

10.1145/2837126.2843845

Link to publication in Scopus

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Cite this

Hintze, D., Muaaz, M., Findling, R. D., Scholz, S., Koch, E., & Mayrhofer, R. (2015). Confidence and Risk Estimation Plugins for Multi-Modal Authentication on Mobile Devices using CORMORANT. In I. Khalil, M. Steinbauer, L. Chen, & G. Anderst-Kotsis (Eds.), 13th International Conference on Advances in Mobile Computing and Multimedia, MoMM 2015 - Proceedings (pp. 384-388). ACM. https://doi.org/10.1145/2837126.2843845

Hintze, Daniel ; Muaaz, Muhammad ; Findling, Rainhard D. ; Scholz, Sebastian ; Koch, Eckhard ; Mayrhofer, René. / Confidence and Risk Estimation Plugins for Multi-Modal Authentication on Mobile Devices using CORMORANT. 13th International Conference on Advances in Mobile Computing and Multimedia, MoMM 2015 - Proceedings. editor / Ismail Khalil ; Matthias Steinbauer ; Liming Chen ; Gabriele Anderst-Kotsis. ACM, 2015. pp. 384-388

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abstract = "Mobile devices, ubiquitous in modern lifestyle, embody and provide convenient access to our digital lives. Being small and mobile, they are easily lost or stole, therefore require strong authentication to mitigate the risk of unauthorized access. Common knowledge-based mechanism like PIN or pattern, however, fail to scale with the high frequency but short duration of device interactions and ever increasing number of mobile devices carried simultaneously. To overcome these limitations, we present CORMORANT, an extensible framework for risk-aware multi-modal biometric uthentication across multiple mobile devices that offers increased security and requires less user interaction.",

keywords = "biometrics, multi-modal authentication, risk assessment",

author = "Daniel Hintze and Muhammad Muaaz and Findling, {Rainhard D.} and Sebastian Scholz and Eckhard Koch and Ren{\'e} Mayrhofer",

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booktitle = "13th International Conference on Advances in Mobile Computing and Multimedia, MoMM 2015 - Proceedings",

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Hintze, D, Muaaz, M, Findling, RD, Scholz, S, Koch, E & Mayrhofer, R 2015, Confidence and Risk Estimation Plugins for Multi-Modal Authentication on Mobile Devices using CORMORANT. in I Khalil, M Steinbauer, L Chen & G Anderst-Kotsis (eds), 13th International Conference on Advances in Mobile Computing and Multimedia, MoMM 2015 - Proceedings. ACM, pp. 384-388, International Conference on Advances in Mobile Computing and Multimedia, Brussels, Belgium, 11/12/2015. https://doi.org/10.1145/2837126.2843845

Confidence and Risk Estimation Plugins for Multi-Modal Authentication on Mobile Devices using CORMORANT. / Hintze, Daniel; Muaaz, Muhammad; Findling, Rainhard D.; Scholz, Sebastian; Koch, Eckhard; Mayrhofer, René.

13th International Conference on Advances in Mobile Computing and Multimedia, MoMM 2015 - Proceedings. ed. / Ismail Khalil; Matthias Steinbauer; Liming Chen; Gabriele Anderst-Kotsis. ACM, 2015. p. 384-388.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

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AB - Mobile devices, ubiquitous in modern lifestyle, embody and provide convenient access to our digital lives. Being small and mobile, they are easily lost or stole, therefore require strong authentication to mitigate the risk of unauthorized access. Common knowledge-based mechanism like PIN or pattern, however, fail to scale with the high frequency but short duration of device interactions and ever increasing number of mobile devices carried simultaneously. To overcome these limitations, we present CORMORANT, an extensible framework for risk-aware multi-modal biometric uthentication across multiple mobile devices that offers increased security and requires less user interaction.

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Hintze D, Muaaz M, Findling RD, Scholz S, Koch E, Mayrhofer R. Confidence and Risk Estimation Plugins for Multi-Modal Authentication on Mobile Devices using CORMORANT. In Khalil I, Steinbauer M, Chen L, Anderst-Kotsis G, editors, 13th International Conference on Advances in Mobile Computing and Multimedia, MoMM 2015 - Proceedings. ACM. 2015. p. 384-388 https://doi.org/10.1145/2837126.2843845