Keystroke Dynamics Analysis to Enhance Password Security of Mobile Banking Applications
Abstract
Nowadays, there are many cases where users’ personal accounts get hacked using their own password. The factors for such cases can vary depending on password strength and obvious passwords which are similar to the user’s details such as usernames and emails. For that, there are new ways of preventing such incidents to happen and to strengthen the security of the accounts. This paper studies the usage of keystroke analysis to enhance password security which includes biometrics and typing patterns. This paper will also discuss the previous researches regarding this method on many platforms including touch screen devices. After that, this paper will look deeply into the implementation process of this technique followed by a detailed experiments and analysis. using keystroke dynamics analysis to enhance password security on mobile devices proved to have a great chance of success and how it can affect the everyday users of banking applications.
Downloads
References
.Yaseein Soubhi Hussein, Ahmed Saeed Alabed, Mustafa Al Mafrachi, Maen Alrshdan, Qusay Al-Maatouk, Li-Fi Technology for Smart Cities, Solid State Technology, p 2391-2399, 2020
.Norton Setup Blog, Top 10 most infamous digital assault in history, 2019. online: https://norton.comsetup-activate.com/blog/top-10-biggest-cyber-attacks-in-history/.
.S. T. Prof P. D. Thakare, "Graphical-Based Password Keystroke Dynamic Authentication System " irjet, vol. 5, no. 2, pp. 2395-0072, 2018.
.S. K. Swarna Bajaj, "Typing Speed Analysis of Human for Password Protection ( Based On Keystrokes Dynamics)," International Journal of Innovative Technology and Exploring Engineering (IJITEE), vol. 3, no. 2, pp. 2278-3075, 2013.
.R. Chan, "7-Eleven Japan shut down a mobile payments app after only two days because hackers exploited a simple security flaw and customers lost over $500,000," ed, 2019.
. K. O'Flaherty, "Password Managers Have A Security Flaw -- Here's How to Avoid It," ed, 2019.
.A. Salem, D. Zaidan, A. Swidan, and R. Saifan, "Analysis of Strong Password Using Keystroke Dynamics Authentication in Touch Screen Devices," Amman, Jordan, 2016: IEEE.
.S. Mondal, "Context Independent Continuous Authentication using Behavioural Biometrics," 2015: IEEE.
. T.-Y. C. Cheng Jung Tasia, Pei Cheng Cheng, Jyun Hao Lin, "Two novel biometric features in keystroke dynamics authentication systems for touch screen devices," Security and Communication Networks, vol. 7, no. 4, pp. 750-758, 2014.
.Yadav, Amrendra Singh, et al. "Increasing Efficiency of Sensor Nodes by Clustering in Section Based Hybrid Routing Protocol with Artificial Bee Colony." Procedia Computer Science 171 (2020): 887-896.
.R. Arora, "Comparative Analysis of Classification Algorithms on Different Datasets using WEKA," International Journal of Computer Applications vol. 54, no. 13, pp. 0975–8887, 2012.
.J. Jayan, "Sequential Minimal Optimization for Support Vector Machines," in towardsdatascience, ed, 2020.
.H. Crawford, "Authentication on the Go: Assessing the Effect of Movement on Mobile Device Keystroke Dynamics," Santa Clara, 2017: Usenix.
.M. Goel, "WalkType: Using accelerometer data to accommodate situational impairments in mobile touch screen text entry," Seattle, 2017: Research Gate.
.C. Giuffrida, "I Sensed It Was You: Authenticating Mobile Users with Sensor-Enhanced Keystroke Dynamics," 2014: Springer.
.A. Z. Al-Othmani, A. A. Manaf, A. M. Zeki, Q. Almaatouk, A. Aborujilah and M. T. Al-Rashdan, "Correlation Between Speaker Gender and Perceptual Quality of Mobile Speech Signal," 2020 14th International Conference on Ubiquitous Information Management and Communication (IMCOM), Taichung, Taiwan, 2020, pp. 1-6, DOI: 10.1109/IMCOM48794.2020.9001793.
.R. W. S. Scott MacKenzie, "Phrase Sets for Evaluating Text Entry Techniques," New York, 2003: York University.
.Mewada, Arvind, et al. "Network intrusion detection using multiclass support vector machine." Special Issue of IJCCT 1.2-4 (2010): 172-175.
.Syed Zulkarnain Syed Idrus. Soft Biometrics for Keystroke Dynamics. Computer Vision andPattern Recognition. Universit ́e de Caen Basse-Normandie, 2014. English.
.Yap Sing Chuen, Maen Al-Rashdan, Qusay Al-Maatouk, “Graphical Password Strategy”, Journal of Critical Reviews, Vol 7, Issue 3, 2020
.M. Tubishat, M. Alswaitti, S. Mirjalili, M. A. Al-Garadi, M. T. Alrashdan and T. A. Rana, "Dynamic Butterfly Optimization Algorithm for Feature Selection," in IEEE Access, vol. 8, pp. 194303-194314, 2020, doi: 10.1109/ACCESS.2020.3033757
.Teo Min Xuan, Maen T. Alrashdan, Qusay Al-Maatouk, Mosab Tayseer Alrashdan, “Blockchain Technology in E-Commerce Platform”, International Journal of Management, vol. 11, issue 10, pp. 1688-1697, 2020, doi: 10.34218/IJM.11.10.2020.154.
.R. Gandhi, "Naive Bayes Classifier," in towardsdatascience, ed, 2018.
.Derrick Chan Jianli, Maen Al-Rashdan, Qusay Al-Maatouk, Secure Data Storage System, Journal of Critical Reviews, Vol 7, Issue 3, 2020.