Keystroke Dynamics-Based Authentication System Using Empirical Thresholding Algorithm

2021 ◽  
Vol 15 (4) ◽  
pp. 98-117
Author(s):  
Priya C. V. ◽  
K. S. Angel Viji
Keyword(s):  
Rejection Rate ◽  
Threshold Values ◽  
Equal Error Rate ◽  
Keystroke Dynamics ◽  
System Protection ◽  
Timing Information ◽  
Authentication System ◽  
Thresholding Algorithm ◽  
Password Based Authentication ◽  
Algorithmic Procedure

In a password-based authentication technique, whenever the typed password and username matches the system database, the secure login page allows the client to access it. Despite the password matching, the proposed method checks the similarity between the typing rhythm of entered password and the rhythm of password samples in client's database. In this paper, a novel algorithmic procedure is presented to authenticate the legal client based on empirical threshold values obtained from the timing information of the client's keystroke dynamics. The exploratory outcomes demonstrate an impressive diminish in both false rejection rate and false acceptance rate. Equal error rate and authentication accuracy are also assessed to show the superiority and robustness of the method. Therefore, the proposed keystroke dynamics-based authentication method can be valuable in securing the system protection as a correlative or substitute form of client validation and as a useful resource for identifying the illegal invasion.

An authentication system using keystroke dynamics

2018 ◽  
Vol 10 (1) ◽  
pp. 65
Author(s):  
Farhana Javed Zareen ◽  
Chirag Matta ◽  
Akshay Arora ◽  
Sarmod Singh ◽  
Suraiya Jabin
Keyword(s):  
Keystroke Dynamics ◽  
Authentication System

An authentication system using keystroke dynamics

2018 ◽  
Vol 10 (1) ◽  
pp. 65
Author(s):  
Suraiya Jabin ◽  
Sarmod Singh ◽  
Akshay Arora ◽  
Farhana Javed Zareen ◽  
Chirag Matta
Keyword(s):  
Keystroke Dynamics ◽  
Authentication System

scholarly journals New Authentication Model for Multimodal Biometrics Based on Shape Features Vectors

2019 ◽  
Vol 54 (6) ◽  
Author(s):  
Sundos Abdulameer Alazawi ◽  
Huda Abdulaaliabdulbaqi ◽  
Yasmin Makki Mohialden
Keyword(s):  
High Performance ◽  
Feature Fusion ◽  
Personal Data ◽  
Rejection Rate ◽  
Shape Features ◽  
Multimodal Biometrics ◽  
Invariant Moments ◽  
Measurement And Analysis ◽  
Authentication System ◽  
Form Features

Biometrics is the science and technology dealing with the measurement and analysis of the biological features of the human body. The analysis is based on comparing the value of certain measured features with the form features in the database. Unimodal Biometric Systems have many limitations regarding precision in the identification/authentication of personal data. To accurately identify a person, a multimodal biometrics system such as combining face and fingerprint characteristic is used. Many such multi-biometrics fusion possibilities exist that can be utilized as an authentication system. In this paper, we present a new authentication system of the multimodal biometrics method for both face and fingerprint characteristics based on general shape feature fusion vectors. There are two main phases in our method: first, the fused shape features for both face and fingerprint images are extracted in accordance with central moments, and second, these features were recognized for retrieval of an authorized person using direct Euclidian distance. Experimentally, we tested about 100 shape features vectors, and observed that our method allows to improve the multimodal biometrics model when we are using the same features for two biometric images. A new method has a high-performance precision when invariant moments are used to extract shape features vectors and when similarity measurements computed based on direct Euclidean distance in the experiments are performed. We recorded False Acceptance Rate, False Rejection Rate, and Accuracy, FAR and FRR where the accuracy of the model is 91 %.

scholarly journals Novel Biometric Fusion System using GA-PSO and ANN

2020 ◽  
Vol 9 (4) ◽  
pp. 3122-3129
Keyword(s):  
Rejection Rate ◽  
Fusion System ◽  
Scale Invariant ◽  
Fusion Strategy ◽  
Bee Colony ◽  
Face Features ◽  
Authentication System ◽  
Nature Inspired Algorithms ◽  
High Level ◽  
Biometric Fusion

Technology advancements have led to the emergence of biometrics as the most relevant future authentication technology. On practical grounds, unimodal biometric authentication systems have inevitable momentous limitations due to varied data quality and noise levels. The paper aims at investigating fusion of face and fingerprint biometric characteristics to achieve a high level personal authentication system. In the fusion strategy face features are extracted using Scale-Invariant Feature Transform (SIFT) algorithm and fingerprint features are extracted using minutiae feature extraction. These extracted features are optimized using nature inspired Genetic Algorithm (GA). The efficiency of the proposed fusion authentication system is enhanced by training and testing the data by applying Artificial Neural Network (ANN). The quality of the proposed design is evaluated against two nature inspired algorithms, namely, Particle Swarm Optimization (PSO)and Artificial Bee Colony (ABC) in terms of False Acceptance Rate (FAR), False Rejection Rate (FRR) and recognition accuracy. Simulation results over a range of image sample from 10 to 100 images have shown that the proposed biometric fusion strategy resulted in FARof 2.89, FAR 0.71and accuracy 97.72%.Experimental evaluation of the proposed system also outperformed the existing biometric fusion system.

The impact of using different keyboards on free-text keystroke dynamics authentication for Arabic language

2019 ◽  
Vol 27 (2) ◽  
pp. 221-232
Author(s):  
Suliman A. Alsuhibany ◽  
Muna Almushyti ◽  
Noorah Alghasham ◽  
Fatimah Alkhudhayr
Keyword(s):  
Recognition Accuracy ◽  
Rejection Rate ◽  
Arabic Language ◽  
Free Text ◽  
Keystroke Dynamics ◽  
Content Type ◽  
High Level ◽  
Traditional Approaches ◽  
The Impact ◽  
Keyboard Layout

Purpose Nowadays, there is a high demand for online services and applications. However, there is a challenge to keep these applications secured by applying different methods rather than using the traditional approaches such as passwords and usernames. Keystroke dynamics is one of the alternative authentication methods that provide high level of security in which the used keyboard plays an important role in the recognition accuracy. To guarantee the robustness of a system in different practical situations, there is a need to examine how much the performance of the system is affected by changing the keyboard layout. This paper aims to investigate the impact of using different keyboards on the recognition accuracy for Arabic free-text typing. Design/methodology/approach To evaluate how much the performance of the system is affected by changing the keyboard layout, an experimental study is conducted by using two different keyboards which are a Mac’s keyboard and an HP’s keyboard. Findings By using the Mac’s keyboard, the results showed that the false rejection rate (FRR) was 0.20, whilst the false acceptance rate (FAR) was 0.44. However, these values have changed when using the HP’s keyboard where the FRR was equal to 0.08 and the FAR was equal to 0.60. Research limitations/implications The number of participants in the experiment, as the authors were targeting much more participants. Originality/value These results showed for the first time the impact of the keyboards on the system’s performance regarding the recognition accuracy when using Arabic free-text.

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