A Survey of Keystroke Dynamics Biometrics

Teh, Pin Shen; Teoh, Andrew Beng Jin; Yue, Shigang

doi:10.1155/2013/408280

Cited by 245 publications

(148 citation statements)

References 132 publications

(287 reference statements)

Supporting

Mentioning

145

Contrasting

Unclassified

Order By: Relevance

“…Keystroke dynamics is the process of analyzing the habitual rhythm of a user typing on a keyboard or on a mobile touch screen device to extract typing features as speed, latency between keystrokes, and pressure [64]. Those features are used to create a unique signature for each user "No two users type in the same way [65]" for easily later identifying.…”

Section: Keystroke Dynamicsmentioning

confidence: 99%

Biometric-based Authentication Techniques for Securing Cloud Computing Data - A Survey

Asmaa¹,

Hala²,

Mostafa-Sami³

2018

IJCA

View full text Add to dashboard Cite

Cloud Computing is the most growing paradigm for delivering computational resources as a service over the internet. By 2018, many different enterprises have adopted this utility-based computing for reducing the operational and capital expenditure of building their infrastructure network, buying software licenses, hiring IT teams and other requirements. With this unlimited growth of using cloud services and the multi-tenancy nature of sharing cloud service instance between different consumers and enterprises, securing accessing to the data of the cloud became a major issue. Traditional authentication techniques and credentials does not provide enough security against the modern means of attacks. So, new biometric-based authentication techniques have been discovered to overcome the loop holes. Here we present a comprehensive survey on the existing user's authentication techniques especially biometric-based techniques used for accessing cloud data.

show abstract

Section: Keystroke Dynamicsmentioning

confidence: 99%

Biometric-based Authentication Techniques for Securing Cloud Computing Data - A Survey

Asmaa¹,

Hala²,

Mostafa-Sami³

2018

IJCA

View full text Add to dashboard Cite

show abstract

“…Biometric authentication [9,13] is an authentication mechanism that identify users base on measuring their unique characteristic. In other words, biometric authentication is base on verifying personal attributes of users [11].…”

Section: Literature Reviewmentioning

confidence: 99%

“…It is based on style of each person's typing on a keyboard, as well as it can identify the user based on their habitual typing pattern. Keystroke dynamics implies on the process of measuring human's typing rhythm on digital devices such as mobile devices [9]. In other words, it is not important what you type; the important point is how you type.…”

Section: Fig1: Classification Of Biometric Authenticationmentioning

confidence: 99%

“…This is a huge drawback of KSA; due to system can use by anyone once the user is authenticated at login [36]. Majority of the researches have focused on KSA using inter-keystroke latency mechanism [9]. Static authentication provides more strong and robust user authentication than simple password or PIN; however it cannot keep continuous security.…”

Section: Introductionmentioning

confidence: 99%

“…In other words, the typing patterns of users are constantly analyzed and when they do not match accessing of users will block [9,34]. The main goal of KDA is recognizing mobile users by identifying and analyzing their unique feature for authentication such as typing pressure, keystroke duration, typing error, and latency of keystrokes [9].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Keystroke Dynamic Authentication in Mobile Cloud Computing

Babaeizadeh¹,

Bakhtiari²,

Maarof³

2014

IJCA

View full text Add to dashboard Cite

One of the important challenges in Mobile Cloud Computing (MCC) is related to the authentication of users. There is increasing demand for suitable authentication method for accessing to the shared information via the Internet through Cloud Service Provider (CSP). Personal identification number is the most common mechanism for authentication in mobile devices; however it is not secure way for authenticating users. This work presents a method of authentication which able to identify users based on Keystroke Dynamic Authentication (KDA). Furthermore, keystrokes duration is considered as an attribute for measuring keystrokes of mobile's users. This paper proposed strong method of authentication in the password authentication scheme by combining it with keystroke authentication, which is a type of behavioral biometric mechanism. Experimental results show, the proposed method can work 97.014% correctly, due to the keystroke duration of each user depends on their behavioral characteristic and it can be measured up to milliseconds. On the other hand, if unauthorized person knows the username and password of legal user can not gain access rights because of difference between their keystroke duration. Therefore, it is hard for an attacker to pretend as an owner, and this method enhances the security of authentication in MCC

show abstract

Soft Smart Biopatch for Continuous Authentication‐Enabled Cardiac Biometric Systems

Lee,

Kwon

et al. 2023

Advanced Sensor Research

View full text Add to dashboard Cite

Biometric locking systems offer a seamless integration of an individual's physiological characteristics with secure authentication. However, they suffer from limitations such as false positive and negative authentication, environmental interference, and varying disadvantages across multiple authentication methods. To address these limitations, this study develops a soft smart biopatch for a continuous cardiac biometric wearable device that can continuously gather novel biometric data from an individual's heart sound for authentication with minimal error (less than 0.5%). The device is designed to be discreet and user‐friendly, and it employs soft biocompatible materials to ensure comfort and ease of use. The patch system incorporates a miniaturized microphone to monitor sounds over long periods and multiple dimensions, enhancing the reliability of the biometric data. Furthermore, the use of machine‐learning algorithms has enabled the creation of unique identification keys for individuals based on the continuous monitoring properties of the low‐cost device. These advantages make it more effective and efficient than traditional biometric systems, with the potential to enhance the security of mobile devices and door locks.

show abstract

A Survey of Keystroke Dynamics Biometrics

Cited by 245 publications

References 132 publications

Biometric-based Authentication Techniques for Securing Cloud Computing Data - A Survey

Biometric-based Authentication Techniques for Securing Cloud Computing Data - A Survey

Keystroke Dynamic Authentication in Mobile Cloud Computing

Soft Smart Biopatch for Continuous Authentication‐Enabled Cardiac Biometric Systems

Contact Info

Product

Resources

About