Secure User-Habit-Oriented Authentication for Mobile Devices
Keywords:
Authentication, habit-oriented, mobile, theory of mind, security, usabilityAbstract
Cell product safety has become progressively critical even as we are more based mostly about cellular phones. Just one basic safety trouble is individual authentication, if definitely not implemented effectively, leaves your cellular individual susceptible to harm like impersonation along with unauthorized gain access to. Although some individual authentication components have been offered in past times, reports show cellular customers preferring simplicity more than safety. On top of that, cellular customers typically uncover their particular equipment in public places spaces, inevitably resulting in a large prospects for individual experience disclosure. Determined by the over, all of us expose a new book user-habit-oriented authentication style, wherever cellular customers may combine their unique behavior (or hobbies) using individual authentication about cellular phones. Your user-habit-oriented authentication spins a new boring safety action straight into a pleasurable expertise. Additionally, all of us propose a new rhythm-based authentication program, supplying your first proof of concept in the direction of safeguarded user-habit-oriented authentication intended for cellular phones. Your proposed program in addition will take your first action in the direction of using the theory involving mind straight into safety field. Experimental final results display which the proposed program possesses large exactness when it comes to false sexual rejection fee. Additionally, you’re proposed program has the ability to guard from assaults caused by abilities disclosure, which will be critical in the event it turned out performed throughout the classic schemes.
References
[1] Cisco. (Feb. 2014). Cisco Visual Networking Index: Global Mobile Data Traf_c Forecast Update, 2013_2018. [Online].Available:http://www.cisco.com/c/en/us/solutions/collateral/service-provider/visual-networking-index-ni/white_paper_c11-520862.pdf
[2] A. Sethi, O. Manzoor, and T. Sethi, User Authentication on Mobile Devices, Cigital, Dulles, VA, USA, 2012.
[3] N. L. Clarke and S. M. Furnell, ``Authenticating mobile phone users using keystroke analysis,'' Int. J. Inf. Secur., vol. 6, no. 1, pp. 1_14,Jan. 2007.
[4] S. Furnell, N. Clarke, and S. Karatzouni, ``Beyond the PIN: Enhancing user authentication for mobile devices,'' Comput. Fraud Secur., vol. 2008, no. 8, pp. 12_17, Aug. 2008.
[5] M. Jakobsson, E. Shi, P. Golle, and R. Chow, ``Implicit authentication for mobile devices,'' in Proc. 4th USENIX Conf. Hot Topics Secur. (HotSec), 2009, pp. 9_15.
[6] McAfee. (Feb. 2014). Who's Watching You? [Online]. Available: http://www.mcafee.com/ca/resources/reports/rp-mobile-security-consumer-trends.pdf
[7] D. Drinkwater. (Feb. 2014). RSA 2014: Touchlogging the New Attack Vector for Mobile Hackers. [Online]. Available: http://www.scmagazine.com/rsa-2014-touchlogging-the-new-attack-vector-for-mobile-hackers/article/335997/
[8] J. Seto, Y. Wang, and X. Lin, ``Toward secure user-habit-oriented authentication for mobile devices,'' in Proc. IEEE Int. Conf. Global Commun. (GLOBECOM), Dec. 2014, pp. 1242_1248.
[9] Has the iPhone 5S Fingerprint Scanner Already Been Hacked? [Online]. Available: http://www.ctvnews.ca/sci-tech/has-the-iphone-5s-fingerprint-scanner-already-been-hacked-1.1468316, accessed Dec. 12, 2014.
[10] R. A. Dora, P. D. Schalk, J. E. McCarthy, and S. A. Young, ``Remote suspect identification and the impact of demographic features on keystroke dynamics,'' Proc. SPIE, vol. 8757, p. 87570B, May 2013.
[11] G. A. Carpenter, S. Grossberg, N. Markuzon, J. H. Reynolds, and D. B. Rosen, ``Fuzzy ARTMAP: A neural network architecture for incremental supervised learning of analog multidimensional maps,'' IEEE Trans. Neural Netw., vol. 3, no. 5, pp. 698_713, Sep. 1992. VOLUME 3, NO. 1, MARCH 2015.
[12] D. Premack and G. Woodruff, ``Does the chimpanzee have a theory of mind?'' Behavioral Brain Sci., vol. 1, no. 4, pp. 515_526, 1978.
[13] E. L. Newton, ``The rocky road from actions to intentions,'' Ph.D. dissertation, Dept. Psychol., Stanford Univ., Stanford, CA, USA, 1990.
[14] M. Dong, T. Kimata, K. Sugiura, and K. Zettsu, ``Quality-of- experience (QoE) in emerging mobile social networks,'' IEICE Trans Inf. Syst., vol. E97-D, no. 10, pp. 2606_2612, Oct. 2014.
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