Insights from curve fitting models in mouse dynamics authentication systems

Yi Xiang Marcus Tan; Alexander Binder; Arunava Roy

doi:10.1109/AINS.2017.8270422

Insights from curve fitting models in mouse dynamics authentication systems

Yi Xiang Marcus Tan, Alexander Binder, Arunava Roy

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research

13 Citations (Scopus)

Abstract

In this work, we investigate the impact of various curve smoothing approaches on the performance of prediction tasks using mouse movement sequences as inputs in the setting of user authentication. We make use of three time-series forecasting modelling techniques as alternatives and we perform a comparison. We demonstrate our findings for the Balabit challenge mouse movement dataset.

Original language	English
Title of host publication	2017 IEEE Conference on Applications, Information and Network Security, AINS 2017
Place of Publication	Piscataway NJ USA
Publisher	IEEE, Institute of Electrical and Electronics Engineers
Pages	42-47
Number of pages	6
ISBN (Electronic)	9781538607251
DOIs	https://doi.org/10.1109/AINS.2017.8270422
Publication status	Published - 2017
Externally published	Yes
Event	IEEE Conference on Applications, Information and Network Security 2017 - Miri, Sarawak, Malaysia Duration: 13 Nov 2017 → 14 Nov 2017 https://ieeexplore.ieee.org/xpl/conhome/8262680/proceeding (Proceedings) https://www.aconf.org/conf_108761.2017_IEEE_Conference_on_Application,_Information_and_Network_Security.html (Website)

Conference

Conference	IEEE Conference on Applications, Information and Network Security 2017
Abbreviated title	AINS 2017
Country/Territory	Malaysia
City	Miri, Sarawak
Period	13/11/17 → 14/11/17
Internet address	https://ieeexplore.ieee.org/xpl/conhome/8262680/proceeding (Proceedings) https://www.aconf.org/conf_108761.2017_IEEE_Conference_on_Application,_Information_and_Network_Security.html (Website)

Keywords

Active Authentication
Cubic Splines
Linear Support Vector Machines
Mouse Dynamics
Time Series Forecasting Models

Access to Document

10.1109/AINS.2017.8270422

Cite this

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title = "Insights from curve fitting models in mouse dynamics authentication systems",

abstract = "In this work, we investigate the impact of various curve smoothing approaches on the performance of prediction tasks using mouse movement sequences as inputs in the setting of user authentication. We make use of three time-series forecasting modelling techniques as alternatives and we perform a comparison. We demonstrate our findings for the Balabit challenge mouse movement dataset.",

keywords = "Active Authentication, Cubic Splines, Linear Support Vector Machines, Mouse Dynamics, Time Series Forecasting Models",

author = "Tan, {Yi Xiang Marcus} and Alexander Binder and Arunava Roy",

note = "Funding Information: This work was supported by both ST Electronics and the National Research Foundation (NRF), Prime Minister's Office, Singapore under Corporate Laboratory @ University Scheme (Programme Title: STEE Infosec - SUTD Corporate Laboratory). The authors also acknowledges the support by the SUTD Startup grant. Publisher Copyright: {\textcopyright} 2017 IEEE. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.; IEEE Conference on Applications, Information and Network Security 2017, AINS 2017 ; Conference date: 13-11-2017 Through 14-11-2017",

year = "2017",

doi = "10.1109/AINS.2017.8270422",

language = "English",

pages = "42--47",

booktitle = "2017 IEEE Conference on Applications, Information and Network Security, AINS 2017",

publisher = "IEEE, Institute of Electrical and Electronics Engineers",

address = "United States of America",

url = "https://ieeexplore.ieee.org/xpl/conhome/8262680/proceeding, https://www.aconf.org/conf_108761.2017_IEEE_Conference_on_Application,_Information_and_Network_Security.html",

}

Tan, YXM, Binder, A & Roy, A 2017, Insights from curve fitting models in mouse dynamics authentication systems. in 2017 IEEE Conference on Applications, Information and Network Security, AINS 2017. IEEE, Institute of Electrical and Electronics Engineers, Piscataway NJ USA, pp. 42-47, IEEE Conference on Applications, Information and Network Security 2017, Miri, Sarawak, Malaysia, 13/11/17. https://doi.org/10.1109/AINS.2017.8270422

Insights from curve fitting models in mouse dynamics authentication systems. / Tan, Yi Xiang Marcus; Binder, Alexander; Roy, Arunava.
2017 IEEE Conference on Applications, Information and Network Security, AINS 2017. Piscataway NJ USA: IEEE, Institute of Electrical and Electronics Engineers, 2017. p. 42-47.

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research

TY - GEN

T1 - Insights from curve fitting models in mouse dynamics authentication systems

AU - Tan, Yi Xiang Marcus

AU - Binder, Alexander

AU - Roy, Arunava

N1 - Funding Information: This work was supported by both ST Electronics and the National Research Foundation (NRF), Prime Minister's Office, Singapore under Corporate Laboratory @ University Scheme (Programme Title: STEE Infosec - SUTD Corporate Laboratory). The authors also acknowledges the support by the SUTD Startup grant. Publisher Copyright: © 2017 IEEE. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.

PY - 2017

Y1 - 2017

N2 - In this work, we investigate the impact of various curve smoothing approaches on the performance of prediction tasks using mouse movement sequences as inputs in the setting of user authentication. We make use of three time-series forecasting modelling techniques as alternatives and we perform a comparison. We demonstrate our findings for the Balabit challenge mouse movement dataset.

AB - In this work, we investigate the impact of various curve smoothing approaches on the performance of prediction tasks using mouse movement sequences as inputs in the setting of user authentication. We make use of three time-series forecasting modelling techniques as alternatives and we perform a comparison. We demonstrate our findings for the Balabit challenge mouse movement dataset.

KW - Active Authentication

KW - Cubic Splines

KW - Linear Support Vector Machines

KW - Mouse Dynamics

KW - Time Series Forecasting Models

UR - http://www.scopus.com/inward/record.url?scp=85047543965&partnerID=8YFLogxK

U2 - 10.1109/AINS.2017.8270422

DO - 10.1109/AINS.2017.8270422

M3 - Conference Paper

AN - SCOPUS:85047543965

SP - 42

EP - 47

BT - 2017 IEEE Conference on Applications, Information and Network Security, AINS 2017

PB - IEEE, Institute of Electrical and Electronics Engineers

CY - Piscataway NJ USA

T2 - IEEE Conference on Applications, Information and Network Security 2017

Y2 - 13 November 2017 through 14 November 2017

ER -

Insights from curve fitting models in mouse dynamics authentication systems

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Keywords

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