scholarly journals Biometric Quality: Analysis of Iris Recognition Techniques with other Biometric Authentication Systems

2017 ◽  
Vol 162 (4) ◽  
pp. 31-36
Author(s):  
Prashant Kapoor ◽  
Paresh Rawat
Keyword(s):  
Iris Recognition ◽  
Quality Analysis ◽  
Biometric Authentication ◽  
Biometric Quality

USABLE SECURITY IN BIOMETRIC AUTHENTICATION SYSTEMS

2021 ◽  
Vol 17 (1) ◽  
pp. 287-292
Author(s):  
Adriana-Meda UDROIU ◽  
Ștefan-Antonio DAN-ȘUTEU
Keyword(s):  
Iris Recognition ◽  
Accurate Method ◽  
Biometric Authentication ◽  
Usable Security ◽  
Security Systems ◽  
Field Methods ◽  
Secure Systems ◽  
Authentication System ◽  
Secure Authentication ◽  
Pattern Variability

Abstract: We introduce the term usable security to refer to security systems, models, mechanisms and applications that have as the main goal usability. Secure systems cannot exist without secure authentication methods. Thus we outline biometric authentication methods and we focus on iris recognition because is the most reliable and accurate method for human identification]. The most important advantage of iris biometric over other biometrics is that irises have enormous pattern variability meaning that the variation between individual is almost maximum and variation for any person across time or conditions is minimum. Taking into consideration this observations, this survey covers researches in this field, methods of technical implementation and the usability of this method as an authentication system on iOS environment.

scholarly journals Detection of Involuntary Iris Scanning for Enhanced Biometric Security

2019 ◽  
Vol 8 (9S) ◽  
pp. 526-532
Keyword(s):  
Sample Size ◽  
Iris Recognition ◽  
Recognition System ◽  
Biometric Authentication ◽  
Eye Blink ◽  
Biometric Security ◽  
Significant Difference ◽  
Proactive Measures ◽  
Average Size ◽  
Iris Scanning

Although iris recognition system is considered as most robust, hard to counterfeit and the most secure system of biometric authentication. However the existing system fails to detect a forced authentication which might be misused by criminals to unlock the user's account. In this paper we examine the conditions in which a real user is forcibly presented in front of iris scanner on gun point to unlock the account. In this case a significant difference is noted in the area of iris visibility with respect to user's normal iris area visibility. An abnormal eye blink is also detected in forced condition. We successfully design and developed an algorithm to detect such conditions to protect the users from criminals when a user is forcibly presented to an iris scanner to unlock their account. A sample size of 65 volunteers are taken to record the iris authentication in both the conditions i.e. normal with consent of user and forced under without user’s consent. The average size of iris is recorded 10.1 mm while it expands on 13.2 mm (average) in fear when iris is being scanned forcibly by criminals. We conclude that a variation of 2 to 3 mm in iris exposure is a clear biomarker to indicate some presence of criminal traces and take proactive measures to prevent losses.

scholarly journals An optimized rubber sheet model for normalization phase of IRIS recognition

2020 ◽  
Vol 1 (3) ◽  
pp. 126-134
Author(s):  
Selvamuthukumaran S. ◽  
Ramkumar T. ◽  
Shantharajah Shantharajah
Keyword(s):  
Iris Recognition ◽  
Histogram Equalization ◽  
Normalization Method ◽  
Polar Coordinates ◽  
Experimental Result ◽  
Biometric Authentication ◽  
Spherical Coordinates ◽  
Rubber Sheet ◽  
Segmented Image ◽  
Human Iris

Iris recognition is a promising biometric authentication approach and it is a very active topic in both research and realistic applications because the pattern of the human iris differs from person to person, even between twins. In this paper, an optimized iris normalization method for the conversion of segmented image into normalized form has been proposed. The existing methods are converting the Cartesian coordinates of the segmented image into polar coordinates. To get more accuracy, the proposed method is using an optimized rubber sheet model which converts the polar coordinates into spherical coordinates followed by localized histogram equalization. The experimental result shows the proposed method scores an encouraging performance with respect to accuracy.

scholarly journals Future of Cybersecurity: A Study on Biometric Scans

2021 ◽  
Vol 9 (11) ◽  
pp. 1180-1185
Author(s):  
Amogh Joshi
Keyword(s):  
Statistical Analysis ◽  
Human Body ◽  
Iris Recognition ◽  
Facial Recognition ◽  
Voice Recognition ◽  
Biological Characteristics ◽  
Behavioral Characteristics ◽  
Biometric Authentication ◽  
Security Breaches

Abstract: Biometrics is a statistical analysis of people's unique behavioral characteristics. The technology is used for CYBERSECURITY. The basics of biometric authentication is that to stop security breaches by analyzing a person’s unique behavioral characteristics. The term biometrics is derived from the Greek word’s “bios” meaning life and “metricos” meaning to measure. It refers to measurements of physical and biological characteristics of the human body. In this paper, we have studied some biometric methods such as facial recognition, iris recognition, Retinal Recognition, voice recognition. Keywords: Biometrics, Cybersecurity, Biometric Scan, Retinal Scan, Iris Scan, Gait, Voice Recognition.

scholarly journals Secure Authentication with Iris using Hamming Distance

2019 ◽  
Vol 8 (4) ◽  
pp. 4787-4790
Keyword(s):  
Pattern Matching ◽  
Iris Recognition ◽  
Hamming Distance ◽  
Behavioral Characteristics ◽  
Biometric Authentication ◽  
Previous Knowledge ◽  
Unique Identifier ◽  
Automated Recognition ◽  
Feature Encoding ◽  
Secure Authentication

Biometrics authentication is the automated recognition of physiological or behavioral characteristics of a person without any previous knowledge. It adds a unique identifier and it is extremely difficult to duplicate. One of the most unique biometric authentication structures is iris pattern. It is the most solid and exact distinguishing proof structure existing around. The exhibition of this acknowledgment framework can be estimated with quality and acknowledgment rate. In the proposed work, iris code were generated by the processing the iris image by applying preprocessing, gaber filter, normalization, feature encoding by Fast Fourier Transform and then Hamming distance was used for pattern matching. The overall success rate shows that iris recognition is a reliable and accurate biometric authentication

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