Strengthening Passwords by Keystroke Dynamics

Mészáros, Anna; Bankó, Zoltán; Czúni, László

doi:10.1109/idaacs.2007.4488486

Cited by 10 publications

(5 citation statements)

References 11 publications

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“…Instead of updating the keystroke reference template, [ 35 ] proposed to readjust the matching threshold. This method circumvents the complexity of retraining sample data over potentially complex algorithm.…”

Section: Methodsmentioning

confidence: 99%

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A Survey of Keystroke Dynamics Biometrics

Teh

Teoh

Yue

2013

The Scientific World Journal

245

135

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Research on keystroke dynamics biometrics has been increasing, especially in the last decade. The main motivation behind this effort is due to the fact that keystroke dynamics biometrics is economical and can be easily integrated into the existing computer security systems with minimal alteration and user intervention. Numerous studies have been conducted in terms of data acquisition devices, feature representations, classification methods, experimental protocols, and evaluations. However, an up-to-date extensive survey and evaluation is not yet available. The objective of this paper is to provide an insightful survey and comparison on keystroke dynamics biometrics research performed throughout the last three decades, as well as offering suggestions and possible future research directions.

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Section: Methodsmentioning

confidence: 99%

“…Some preprocessing procedures may be applied before feature extraction to ensure or to increase the quality of feature data. These steps may include feature selection [ 31 ], dimension reduction [ 32 ], and outlier detection [ 33 – 35 ].…”

Section: Keystroke Dynamicsmentioning

confidence: 99%

A Survey of Keystroke Dynamics Biometrics

Teh

Teoh

Yue

2013

The Scientific World Journal

245

135

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show abstract

“…Using the four features, authors achieved a false rejection rate of 1.45% and a false acceptance rate of 1.89% for user authentication. Meszaros, et al [22], designed an adaptive distance-based threshold on features to authenticate users. Harun, et al [34], proposed a multilayer perceptron neural network with a backpropagation learning algorithm as a classifier.…”

Section: Related Workmentioning

confidence: 99%

“…Keystroke dynamics can be categorized as fixed-text and free-text. In fixed-text [12], [14], [16], [17], [21], [22], users type a specific passphrase such as a user id and a corresponding password in a login form, while free-text [4], [6], [10], [13], [19], [20], [23] is where users type in a free uncontrolled environment. Users can type, and therefore, create keystrokes, from either physical keyboards [12] or from touch screen keyboards [16].…”

Section: Introductionmentioning

confidence: 99%

A novel non-linear transformation based multi-user identification algorithm for fixed text keystroke behavioral dynamics

Sahu¹,

Banavar²,

Schuckers³

2022

Preprint

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In this paper, we propose a new technique to uniquely classify and identify multiple users accessing a single application using keystroke dynamics. This problem is usually encountered when multiple users have legitimate access to shared computers and accounts, where, at times, one user can inadvertently be logged in on another user's account. Since the login processes are usually bypassed at this stage, we rely on keystroke dynamics in order to tell users apart. Our algorithm uses the quantile transform and techniques from localization to classify and identify users. Specifically, we use an algorithm known as ordinal Unfolding based Localization (UNLOC), which uses only ordinal data obtained from comparing distance proxies, by "locating" users in a reduced PCA/Kernel-PCA/t-SNE space based on their typing patterns. Our results are validated with the help of benchmark keystroke datasets and show that our algorithm outperforms other methods.

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“…These stringent requirements make people adopt unsafe practices such as record their password close to the authentication device, share with friends and use same passwords on multiple accounts or use familiar names. To reduce the number of security incidents, inclusion of the information contained in the "actions" category has been proposed [8,9].…”

Section: Introductionmentioning

confidence: 99%

Investigating & Improving The Reliability And Repeatability Of Keystorke Dynamics Timers

Pavaday¹,

Sunjiv²,

Shrikaant³

2010

IJNSA

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One of the most challenging tasks facing the security expert remains the correct authentication of human being which has been crucial to the fabric of our society. The emphasis is now on reliable person identification for computerized devices as the latter forms an integral part of our daily activities. Moreover with increasing geographical mobility of individuals, the identification problem has become more acute. One alternative, to curb down the increasing number of computer related crimes, is through the use of keystroke biometric technology which represents an enhancement to password mechanisms by incorporating typing rhythms in it.Time captured being critical to the performance of the identifier, it is primordial that it satisfies certain requirements at a suitable degree of acceptability This paper presents an evaluation of timing options for keystroke dynamics paying attention to their repeatability and reliability as well as their portability on different systems. In actual passwords schemes users enroll using one computer and access resources using other configurations at different locations without bothering about the different underlying operating systems.

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Strengthening Passwords by Keystroke Dynamics

Cited by 10 publications

References 11 publications

A Survey of Keystroke Dynamics Biometrics

A Survey of Keystroke Dynamics Biometrics

A novel non-linear transformation based multi-user identification algorithm for fixed text keystroke behavioral dynamics

Investigating & Improving The Reliability And Repeatability Of Keystorke Dynamics Timers

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