Measuring Network User Trust via Mouse Behavior Characteristics Under Different Emotions

Authentication based on mouse behavior is a guarantee for network information security. But the mouse behavior is affected by the user’s emotions. Therefore, this study aims to analyze the user’s mouse behavior characteristics to measure the identity trust of users under different emotions, and to verify whether there is a significant difference. To achieve this goal, an experiment was conducted. A total of 18 college students participated in this study. The results show that there are differences in the accuracy of authentication based on the user’s mouse sliding behavior in three different emotional states, but the difference is not significant. The average accuracy of authentication under neutral, positive and negative emotions were 83.6%, 80.3% and 81.9%, respectively. The results also show that although the user performs human-computer interaction under different emotions, it will not essentially affect user authentication. Therefore, it can conclude that measuring network user trust via mouse behavior characteristics under different emotions is credible.

[1]  Soumik Mondal,et al.  A computational approach to the continuous authentication biometric system , 2015, Inf. Sci..

[2]  Wolfgang Maehr.  eMotion: Estimation of User's Emotional State by Mouse Motions , 2008 .

[3]  Mangesh Bedekar,et al.  Inferring User Emotions from Keyboard and Mouse , 2018 .

[4]  Rudy Prabowo,et al.  Sentiment analysis: A combined approach , 2009, J. Informetrics.

[5]  Munaf Rashid,et al.  Human emotion recognition from videos using spatio-temporal and audio features , 2012, The Visual Computer.

[6]  Peter J. Lang,et al.  Gaze Patterns When Looking at Emotional Pictures: Motivationally Biased Attention , 2004 .

[7]  George N. Votsis,et al.  Emotion recognition in human-computer interaction , 2001, IEEE Signal Process. Mag..

[8]  Lior Rokach,et al.  User identity verification via mouse dynamics , 2012, Inf. Sci..

[9]  Fabian Monrose,et al.  Authentication via keystroke dynamics , 1997, CCS '97.

[10]  James S. Okolica,et al.  User identification and authentication using multi-modal behavioral biometrics , 2014 .

[11]  B. Tadić,et al.  Networks and emotion-driven user communities at popular blogs , 2010 .

[12]  Ting Yu,et al.  On mouse dynamics as a behavioral biometric for authentication , 2011, ASIACCS '11.

[13]  A.K. Jain,et al.  Webbiometrics: User Verification Via Web Interaction , 2007, 2007 Biometrics Symposium.

[14]  Sungzoon Cho,et al.  Keystroke dynamics-based user authentication using long and free text strings from various input devices , 2015, Inf. Sci..

[15]  Mike Thelwall,et al.  Negative emotions boost user activity at BBC forum , 2010, 1011.5459.

[16]  Patrick Bours,et al.  A Login System Using Mouse Dynamics , 2009, 2009 Fifth International Conference on Intelligent Information Hiding and Multimedia Signal Processing.