A user identification system using signature written with mouse

1998 ◽  
pp. 403-414 ◽  
Author(s):  
Agus Fanar Syukri ◽  
Eiji Okamoto ◽  
Masahiro Mambo
Keyword(s):  
Identification System ◽  
User Identification

scholarly journals Development of security systems using DNN and i & x-vector classifiers

2021 ◽  
Vol 4 (9(112)) ◽  
pp. 32-45
Author(s):  
Orken Mamyrbayev ◽  
Aizat Kydyrbekova ◽  
Keylan Alimhan ◽  
Dina Oralbekova ◽  
Bagashar Zhumazhanov ◽  
...  
Keyword(s):  
Information Systems ◽  
Biometric Identification ◽  
Identification System ◽  
Security Systems ◽  
User Identification ◽  
Verification Algorithm ◽  
Voice Identification ◽  
Biometric Systems ◽  
Function Blocks ◽  
Individual Voice

The widespread use of biometric systems entails increased interest from cybercriminals aimed at developing attacks to crack them. Thus, the development of biometric identification systems must be carried out taking into account protection against these attacks. The development of new methods and algorithms for identification based on the presentation of randomly generated key features from the biometric base of user standards will help to minimize the disadvantages of the above methods of biometric identification of users. We present an implementation of a security system based on voice identification as an access control key and a verification algorithm developed using MATLAB function blocks that can authenticate a person's identity by his or her voice. Our research has shown an accuracy of 90 % for this user identification system for individual voice characteristics. It has been experimentally proven that traditional MFCCs using DNN and i and x-vector classifiers can achieve good results. The paper considers and analyzes the most well-known approaches from the literature to the problem of user identification by voice: dynamic programming methods, vector quantization, mixtures of Gaussian processes, hidden Markov model. The developed software package for biometric identification of users by voice and the method of forming the user's voice standards implemented in the complex allows reducing the number of errors in identifying users of information systems by voice by an average of 1.5 times. Our proposed system better defines voice recognition in terms of accuracy, security and complexity. The application of the results obtained will improve the security of the identification process in information systems from various attacks.

USER IDENTIFICATION WITH USER'S STEPPING PATTERN OVER THE UBIFLOORII

2008 ◽  
Vol 22 (03) ◽  
pp. 497-514 ◽  
Author(s):  
JAESEOK YUN ◽  
GREGORY D. ABOWD ◽  
JEHA RYU ◽  
WOONTACK WOO
Keyword(s):  
Neural Network ◽  
Home Environment ◽  
Recognition Accuracy ◽  
Heel Strike ◽  
Identification System ◽  
Software Module ◽  
User Identification ◽  
Stepping Pattern

In this paper, we propose the UbiFloorII, a novel floor-based user identification system to recognize humans based on their stepping pattern, the arrays of the transitional footprints from heel-strike to toe-off. To obtain users' stepping pattern from their gait, we deployed photo interrupter sensors instead of switch sensors used in the UbiFloorI. We developed a software module to extract stepping pattern from users' gait. For user identification, we employed neural network trained with users' stepping samples. We achieved about 92% recognition accuracy using this floor-based approach. The UbiFloorII system may be used to automatically and transparently identify users in a home environment.

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