Biometric Authentication

2014 ◽  
pp. 254-269
Author(s):  
Misha Voloshin
Keyword(s):  
Statistical Analysis ◽  
Information Security ◽  
Computer System ◽  
User Authentication ◽  
Biometric Authentication ◽  
Time Intervals ◽  
Legitimate User ◽  
Authentication System ◽  
System Administrator ◽  
Alerting Systems

User authentication is the keystone of information security. Even the most craftily built and diligently monitored computer system will crumble if there is a flaw in its user authentication system(Minaev, 2010). A hacker able to exploit such a flaw will be able to convince the computer system that he is a legitimate user – possibly even a specific legitimate user, entitled to all of the abilities to read or modify that user's data, or implicate that user in misdeeds that could lead to personal or professional harm. A hacker could even impersonate the system administrator herself, giving the hacker the ability to not only access all of that system's data but also to subvert the very same network monitors and automated alerting systems that would notify the real administrator of the hacker's activity(occupytheweb, 2013). This chapter introduces a mechanism that an administrator can use for increasing the strength of a computer's user authentication system and triggering a lockout and/or emailing an alert if an impostor is suspected to be accessing a user's account. It works by measuring the time intervals between keystrokes as a user types, relying on the fact that most individuals have distinct and identifiable typing patterns that can be discerned through statistical analysis.

scholarly journals Combining Cryptography with EEG Biometrics

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Robertas Damaševičius ◽  
Rytis Maskeliūnas ◽  
Egidijus Kazanavičius ◽  
Marcin Woźniak
Keyword(s):  
Error Rate ◽  
User Authentication ◽  
Discrete Logarithm ◽  
Security Analysis ◽  
Experimental Results ◽  
Biometric Authentication ◽  
Equal Error Rate ◽  
Eeg Data ◽  
Authentication System ◽  
Biometric Cryptosystem

Cryptographic frameworks depend on key sharing for ensuring security of data. While the keys in cryptographic frameworks must be correctly reproducible and not unequivocally connected to the identity of a user, in biometric frameworks this is different. Joining cryptography techniques with biometrics can solve these issues. We present a biometric authentication method based on the discrete logarithm problem and Bose-Chaudhuri-Hocquenghem (BCH) codes, perform its security analysis, and demonstrate its security characteristics. We evaluate a biometric cryptosystem using our own dataset of electroencephalography (EEG) data collected from 42 subjects. The experimental results show that the described biometric user authentication system is effective, achieving an Equal Error Rate (ERR) of 0.024.

scholarly journals A Study on User Authentication Methodology Using Numeric Password and Fingerprint Biometric Information

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Seung-hwan Ju ◽  
Hee-suk Seo ◽  
Sung-hyu Han ◽  
Jae-cheol Ryou ◽  
Jin Kwak
Keyword(s):  
Information Security ◽  
User Authentication ◽  
The Internet ◽  
Password Authentication ◽  
System Use ◽  
Authentication System ◽  
Access Information ◽  
Authentication Security ◽  
Biometric Information

The prevalence of computers and the development of the Internet made us able to easily access information. As people are concerned about user information security, the interest of the user authentication method is growing. The most common computer authentication method is the use of alphanumerical usernames and passwords. The password authentication systems currently used are easy, but only if you know the password, as the user authentication is vulnerable. User authentication using fingerprints, only the user with the information that is specific to the authentication security is strong. But there are disadvantage such as the user cannot change the authentication key. In this study, we proposed authentication methodology that combines numeric-based password and biometric-based fingerprint authentication system. Use the information in the user's fingerprint, authentication keys to obtain security. Also, using numeric-based password can to easily change the password; the authentication keys were designed to provide flexibility.

scholarly journals On keystrokes as Continuous User Biometric Authentication

2019 ◽  
Vol 8 (6) ◽  
pp. 4149-4153
Keyword(s):  
User Authentication ◽  
Support Vector ◽  
Free Text ◽  
Biometric Authentication ◽  
Text Input ◽  
Continuous Authentication ◽  
Online Examination ◽  
Continuous User ◽  
Authentication System ◽  
Identification Phase

Authentication of a user through an ID and password is generally done at the start of a session. But the continuous authentication system observe the genuineness of the user throughout the entire session, and not at login only. In this paper, we propose the usage of keystroke dynamics as biometric trait for continuous user authentication in desktop platform. Biometric Authentication involves mainly three phases named as enrollment phase, verification phase and identification phase. The identification phase marks the accessed user as an authenticated only if the input pattern matches with the profile pattern otherwise the system is logout. The proposed Continuous User Biometric Authentication (CUBA) System is based on free text input from keyboard. There is no restriction on input data during Enrolment, Verification, and Identification phase. Unsupervised One-class Support Vector Machine is used to classify the authenticated user’s input from all the other inputs. This continuous authentication system can be used in many areas like in Un-proctored online examination systems, Intrusion & Fraud Detection Systems, Areas where user alertness is required for entire period e.g. Controlling Air Traffic etc.

scholarly journals On the Design and Analysis of a Biometric Authentication System Using Keystroke Dynamics

Cryptography ◽  
2020 ◽  
Vol 4 (2) ◽  
pp. 12
Author(s):  
Robert Cockell ◽  
Basel Halak
Keyword(s):  
User Authentication ◽  
Training Data ◽  
Average Error ◽  
Biometric Authentication ◽  
Keystroke Dynamics ◽  
Systematic Analysis ◽  
Average Error Rate ◽  
Multifactor Authentication ◽  
Authentication System ◽  
Cost Efficient

This paper proposes a portable hardware token for user’s authentication; it is based on the use of keystroke dynamics to verify users biometrically. The proposed approach allows for a multifactor authentication scheme, in which a user cannot be granted access unless they provide a correct password on a hardware token and their biometric signature. The latter is extracted while the user is typing their password. This paper explains the design rationale of the proposed system and provides a comprehensive insight in the development of a hardware prototype of the same. The paper also presents a feasibility study that included a systematic analysis based on training data obtained from 32 users. Our results show that dynamic keystroke can be employed to construct a cost-efficient solution for biometric user authentication with an average error rate of 4.5%.

scholarly journals Gaze Touch Cross PIN: Secure Multimodal Authentication using Gaze and Touch PIN

2019 ◽  
Vol 9 (1) ◽  
pp. 777-781 ◽  
Keyword(s):  
Information Security ◽  
User Authentication ◽  
Personal Identification ◽  
Personal Identification Number ◽  
Public Places ◽  
The Gaze ◽  
Shoulder Surfing ◽  
Basic Goal ◽  
Authentication System ◽  
Reliability And Availability

The basic goal of information security is, to protect the privacy, reliability, and availability of information on devices that manipulate and store the information. To protect this information, the fundamental step is user authentication. The most common method for authentication on devices is the personal identification number (PIN) method, which is vulnerable to shoulder surfing attack. Shoulder surfing attack used by attacker especially in the crowded public places. For shoulder surfing attack prevention several methods had been proposed. This paper proposed a GazeTouchCrossPIN authentication method that overcome the limitations found in the earlier work. we propose a multimodal authentication system that combines between the gaze gesture and touch PIN authentication systems. The results illustrate that the proposed GazeTouchCrossPIN method is more secure hence it decreases the shoulder surfing rate in both side attacks and iterative attacks.

scholarly journals Graphical User Authentication System Resistant to Shoulder Surfing Attack

2019 ◽  
pp. 1-8 ◽  
Author(s):  
Oluwaseyifunmitan Osunade ◽  
Iyanuoluwa A. Oloyede ◽  
Titilayo O. Azeez
Keyword(s):  
Information Security ◽  
User Authentication ◽  
Traditional Methods ◽  
Graphical Password ◽  
Shoulder Surfing ◽  
Authentication System ◽  
Alternative Solutions ◽  
Visual Interface

User authentication is one of the most significant issues in the field of Information Security. The most common and convenient authentication method used is the alphanumeric password  which has significant drawbacks. To overcome the vulnerabilities of traditional methods, graphical password schemes have been developed as possible alternative solutions to text-based scheme. A potential drawback of graphical password schemes is that they are more vulnerable to shoulder surfing than conventional alphanumeric text passwords due to their visual interface. To overcome the shortcoming of existing graphical password schemes this project focuses on developing a graphical authentication system that is resistant to shoulder surfing attack.

scholarly journals A Framework for Continuous Authentication Based on Touch Dynamics Biometrics for Mobile Banking Applications

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4212
Author(s):  
Priscila Morais Argôlo Bonfim Estrela ◽  
Robson de Oliveira Albuquerque ◽  
Dino Macedo Amaral ◽  
William Ferreira Giozza ◽  
Rafael Timóteo de Sousa Júnior
Keyword(s):  
User Authentication ◽  
Internet Banking ◽  
Supervised Machine Learning ◽  
Smart Devices ◽  
Static Verification ◽  
User Behaviors ◽  
Legitimate User ◽  
Continuous User ◽  
Mobile Banking Applications ◽  
Effective Layer

As smart devices have become commonly used to access internet banking applications, these devices constitute appealing targets for fraudsters. Impersonation attacks are an essential concern for internet banking providers. Therefore, user authentication countermeasures based on biometrics, whether physiological or behavioral, have been developed, including those based on touch dynamics biometrics. These measures take into account the unique behavior of a person when interacting with touchscreen devices, thus hindering identitification fraud because it is hard to impersonate natural user behaviors. Behavioral biometric measures also balance security and usability because they are important for human interfaces, thus requiring a measurement process that may be transparent to the user. This paper proposes an improvement to Biotouch, a supervised Machine Learning-based framework for continuous user authentication. The contributions of the proposal comprise the utilization of multiple scopes to create more resilient reasoning models and their respective datasets for the improved Biotouch framework. Another contribution highlighted is the testing of these models to evaluate the imposter False Acceptance Error (FAR). This proposal also improves the flow of data and computation within the improved framework. An evaluation of the multiple scope model proposed provides results between 90.68% and 97.05% for the harmonic mean between recall and precision (F1 Score). The percentages of unduly authenticated imposters and errors of legitimate user rejection (Equal Error Rate (EER)) are between 9.85% and 1.88% for static verification, login, user dynamics, and post-login. These results indicate the feasibility of the continuous multiple-scope authentication framework proposed as an effective layer of security for banking applications, eventually operating jointly with conventional measures such as password-based authentication.

Biometric authentication system using EEG biometric trait – A review

2021 ◽  
Author(s):  
Fatin Atiqah Rosli ◽  
Saidatul Ardeenawatie Awang ◽  
Azian Azamimi Abdullah ◽  
Mohammad Shahril Salim
Keyword(s):  
Biometric Authentication ◽  
Authentication System ◽  
Biometric Trait

Motor Imagery Based Multimodal Biometric User Authentication System Using EEG

2020 ◽  
Author(s):  
Akshay Valsaraj ◽  
Ithihas Madala ◽  
Nikhil Garg ◽  
Mohit Patil ◽  
Veeky Baths
Keyword(s):  
Motor Imagery ◽  
User Authentication ◽  
Authentication System
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