Hardware Implementation of Dynamics Keystroke Applied for Cloud Computing
Basma M. Hassan1, Khaled M. Fouad2, Mahmoud F. Hassan3
1Eng. Basma M. Hassan, Department of Electrical Engineering Technology, Faculty of Engineering, Benha University, Benha, Egypt.
2Dr. Khaled M.Fouad, Department of Computer Science, Faculty of
Computers and Informatics, Benha University, Benha, Egypt.

Professor. Mahmoud F. Hassan, Department of Basic Sciences, Faculty of Engineering, Benha University, Benha, Egypt.
Manuscript received on August 14, 2015. | Revised Manuscript received on August 28, 2015. | Manuscript published on September 05, 2015. | PP: 84-89 | Volume-5 Issue-4, September 2015 . | Retrieval Number: D2702095415/2015©BEIESP
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©The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/

Abstract: Cloud computing is a growing technology which provides remote access to computing resources and user data. Due to its core philosophy of enabling the user to access his data from anywhere and at any time, cloud computing has a major issue with security and user authentication. Biometric identification is a very good candidate technology, which can facilitate a trusted user authentication with the minimum constraints on the security of the access point. However, most of the biometric identification techniques require special hardware, thus complicate the access point and make it costly. Keystroke recognition is a biometric identification technique which relies on the user behavior while typing on the keyboard. It is more secure and does not need any additional hardware to the access point. This paper presents a hardware implementation of an algorithm based on keystroke dynamics analysis synthesized, simulated and implemented on FPGA. The authentication process is based on the GP methods to test the ability of the distance measure between keystrokes and how to distinguish users through their typing dynamics keystroke.The proposed architecture achieves maximum delay 0.55 ns.
Keywords: Cloud computing, remote access, biometric identification, access point, Keystroke recognition, FPGA, VHDL.