Paper Info
Title
Two-factor user authentication with the CogRAM weightless neural net
Abstract
The application of the Cognitive RAM (CogRAM) weightless neural net in testing a keystroke biometrics user authentication system for a numeric keypad is discussed in this paper. The two-factor user authentication system developed here uses the common password that is complemented with the keystroke patterns of the users. The keystroke pattern is represented by the force applied to constitute a fixed length passkey to compose a complete pattern for the entered password. The system has been designed and developed around an 8-bit microcontroller, based on the AVR enhanced RISC architecture. The preliminary experimental results showed that the designed system can successfully authenticate the unique and consistent keystroke biometric patterns of the users.
Year
DOI
Venue
2014
10.1109/IJCNN.2014.6889702
IJCNN
Keywords
Field
DocType
microcontrollers,cognitive ram weightless neural net,cogram weightless neural net,keystroke biometrics user authentication system,reduced instruction set computing,avr enhanced risc architecture,biometrics (access control),two-factor user authentication,message authentication,fixed length passkey,numeric keypad,neural nets,user keystroke patterns,microcontroller,password
Authentication,Computer science,Weightless,Artificial neural network,Computer hardware,Embedded system
Conference
ISSN
Citations 
PageRank 
2161-4393
0
0.34
References 
Authors
8
4
Name
Order
Citations
PageRank
Weng Kin Lai1547.98
Beng Ghee Tan200.68
Ming Siong Soo300.68
Imran M. Khan400.34