A Real-Time Authentication Method Based on Cursor-hidden Scene

DOI

10.2991/ccis-13.2013.80How to use a DOI?

Keywords

insider threat, identify theft, behavior biometrics, mouse dynamic

Abstract

Identity theft, as a common insider attack method, is difficult to detect because it is hard to distinguish the legal user from the masquerader with a stolen legal identity. Compared with traditional identity authentication method such as password or fingerprint, behavior biometrics based on HCI (Human-Computer Interaction) has been more useful and effective in real-time authentication. However, existed approaches either require longer authentication time or are designed for special scenario. In this paper, we propose a real-time authentication approach based on mouse-hidden scene to detect identify theft attack. When operations of the suspicious masquerader are detected, the cursor is hidden deliberately. Under the scene, we assume that mouse operators become anxious and show some unique and instinct mouse movement operations. Based on the movement traces, behavioral model is generated and used for detecting the suspicious masquerader. The experiments show the approach can achieve 2.6 percent of FAR and 3.3 percent of FRR while authentication time consumed is acceptable in practice.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Zicheng Wei
AU  - Xiaojun Chen
AU  - Yiguo Pu
AU  - Rui Xu
PY  - 2013/11
DA  - 2013/11
TI  - A Real-Time Authentication Method Based on Cursor-hidden Scene
BT  - Proceedings of the The 1st International Workshop on Cloud Computing and Information Security
PB  - Atlantis Press
SP  - 346
EP  - 350
SN  - 1951-6851
UR  - https://doi.org/10.2991/ccis-13.2013.80
DO  - 10.2991/ccis-13.2013.80
ID  - Wei2013/11
ER  -