Have a personal or library account? Click to login
Mouse dynamics based user recognition using deep learning Cover

Mouse dynamics based user recognition using deep learning

By: Margit Antal and  Norbert Fejér  
Open Access
|Jul 2020

References

  1. [1] A. A. E. Ahmed, I. Traore, A new biometric technology based on mouse dynamics, IEEE Transactions on Dependable and Secure Computing4, 3 (2007) 165–179. ⇒4110.1109/TDSC.2007.70207
  2. [2] A. A. E. Ahmed, I. Traore, Dynamic sample size detection in continuous authentication using sequential sampling, In Proceedings of the 27th Annual Computer Security Applications Conference ACSAC ’11, pp. 169–176, New York, NY, USA, 2011. ACM. ⇒4110.1145/2076732.2076756
  3. [3] M. Antal, L. Dénes-Fazakas, User verification based on mouse dynamics: a comparison of public data sets, In 2019 23th International Symposium on Applied Computational Intelligence and Informatics, pp. 143–147, May 2019. ⇒4410.1109/SACI46893.2019.9111596
  4. [4] P. Chong, Y. Elovici, A. Binder, User authentication based on mouse dynamics using deep neural networks: A comprehensive study, IEEE Transactions on Information Forensics and Security, 15 (2020) 1086–1101. ⇒42, 4810.1109/TIFS.2019.2930429
  5. [5] P. Chong, Y. X. M. Tan, J. Guarnizo, Y. Elovici, A. Binder, Mouse authentication without the temporal aspect – what does a 2d-cnn learn? In 2018 IEEE Security and Privacy Workshops (SPW), pp. 15–21, May 2018. ⇒42, 4810.1109/SPW.2018.00011
  6. [6] C. Feher, Y. Elovici, R. Moskovitch, L. Rokach, A. Schclar. User identity verification via mouse dynamics. Inf. Sci.201 (2012) 19–362. ⇒42
  7. [7]Á. Fülöp, L. Kovács, T. Kurics, E. Windhager-Pokol, Balabit mouse dynamics challenge data set, 2016. ⇒44
  8. [8] H. Gamboa, A. Fred. A behavioral biometric system based on human-computer interaction. In Proc. SPIE 5404, Biometric Technology for Human Identification, (25 August 2004), 5404, pp. 381–392, 2004. ⇒41
  9. [9] KERAS. Keras, 2016. ⇒43, 46
  10. [10] C. Shen, Z. Cai, X. Guan, Continuous authentication for mouse dynamics: A pattern-growth approach, In Proceedings of the 2012 42Nd Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN), DSN ’12, pp. 1–12, Washington, DC, USA, 2012. IEEE Computer Society. ⇒4110.1109/DSN.2012.6263955
  11. [11] C. Shen, Z. Cai, X. Guan, Y. Du, R. A. Maxion, User authentication through mouse dynamics, IEEE Transactions on Information Forensics and Security, 8, 1 (2013) 16–30. ⇒4110.1109/TIFS.2012.2223677
  12. [12] C. Shen, Z. Cai, X. Guan, R. A. Maxion, Performance evaluation of anomaly-detection algorithms for mouse dynamics, Computers & Security45 (2014) 156–171. ⇒4110.1016/j.cose.2014.05.002
  13. [13] N. Zheng, A. Paloski, H. Wang, An efficient user verification system via mouse movements, In Proceedings of the 18th ACM Conference on Computer and Communications Security, CCS ’11, pp. 139–150, New York, NY, USA, 2011. ACM. ⇒4210.1145/2046707.2046725
  14. [14] N. Zheng, A. Paloski, H. Wang, An efficient user verification system using angle-based mouse movement biometrics, ACM Trans. Inf. Syst. Secur., 18, 3 (2016) 11:1–11:27. ⇒4210.1145/2893185
Language: English
Page range: 39 - 50
Submitted on: Jan 25, 2020
|
Accepted on: Feb 16, 2020
|
Published on: Jul 16, 2020
In partnership with: Paradigm Publishing Services
Publication frequency: 2 issues per year

© 2020 Margit Antal, Norbert Fejér, published by Sapientia Hungarian University of Transylvania
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.