Keystroke Biometric Identification and Authentication on Long-Text Input

2010 ◽  
pp. 342-367 ◽  
Author(s):  
Charles C. Tappert ◽  
Mary Villani ◽  
Sung-Hyuk Cha
Keyword(s):  
Hierarchical Model ◽  
Biometric Identification ◽  
The Internet ◽  
Free Text ◽  
User Identification ◽  
Java Applet ◽  
Model Parameter ◽  
Text Input ◽  
Feature Extractor ◽  
Text Length

A novel keystroke biometric system for long-text input was developed and evaluated for user identification and authentication applications. The system consists of a Java applet to collect raw keystroke data over the Internet, a feature extractor, and pattern classifiers to make identification or authentication decisions. Experiments on over 100 subjects investigated two input modes–copy and free-text input–and two keyboard types–desktop and laptop keyboards. The system can accurately identify or authenticate individuals if the same type of keyboard is used to produce the enrollment and questioned input samples. Longitudinal experiments quantified performance degradation over intervals of several weeks and over an interval of two years. Additional experiments investigated the system’s hierarchical model, parameter settings, assumptions, and sufficiency of enrollment samples and input-text length. Although evaluated on input texts up to 650 keystrokes, we found that input of 300 keystrokes, roughly four lines of text, is sufficient for the important applications described.

A Keystroke Biometric System for Long-Text Input

2013 ◽  
pp. 609-634 ◽  
Author(s):  
Charles C. Tappert ◽  
Sung-Hyuk Cha ◽  
Mary Villani ◽  
Robert S. Zack
Keyword(s):  
Hierarchical Model ◽  
The Internet ◽  
Free Text ◽  
Biometric System ◽  
User Identification ◽  
Java Applet ◽  
Model Parameter ◽  
Text Input ◽  
Feature Extractor ◽  
Text Length

A novel keystroke biometric system for long-text input was developed and evaluated for user identification and authentication applications. The system consists of a Java applet to collect raw keystroke data over the Internet, a feature extractor, and pattern classifiers to make identification or authentication decisions. Experiments on more than 100 participants investigated two input modes—copy and free-text—and two keyboard types—desktop and laptop. The system can accurately identify or authenticate individuals if the same type of keyboard is used to produce the enrollment and questioned input samples. Longitudinal experiments quantified performance degradation over intervals of several weeks and two years. Additional experiments investigated the system’s hierarchical model, parameter settings, assumptions, and sufficiency of enrollment samples and input-text length. Although evaluated on input texts up to 650 keystrokes, the authors found that input of 300 keystrokes, roughly four lines of text, is sufficient for the important applications described.

A Keystroke Biometric Systemfor Long-Text Input

2010 ◽  
Vol 4 (1) ◽  
pp. 32-60 ◽  
Author(s):  
Charles C. Tappert ◽  
Sung-Hyuk Cha ◽  
Mary Villani ◽  
Robert S. Zack
Keyword(s):  
Hierarchical Model ◽  
The Internet ◽  
Biometric System ◽  
User Identification ◽  
Java Applet ◽  
Model Parameter ◽  
Text Input ◽  
Input Text ◽  
Feature Extractor ◽  
Text Length

A novel keystroke biometric system for long-text input was developed and evaluated for user identification and authentication applications. The system consists of a Java applet to collect raw keystroke data over the Internet, a feature extractor, and pattern classifiers to make identification or authentication decisions. Experiments on more than 100 participants investigated two input modes—copy and free-text—and two keyboard types—desktop and laptop. The system can accurately identify or authenticate individuals if the same type of keyboard is used to produce the enrollment and questioned input samples. Longitudinal experiments quantified performance degradation over intervals of several weeks and two years. Additional experiments investigated the system’s hierarchical model, parameter settings, assumptions, and sufficiency of enrollment samples and input-text length. Although evaluated on input texts up to 650 keystrokes, the authors found that input of 300 keystrokes, roughly four lines of text, is sufficient for the important applications described.

scholarly journals A heuristics for HTTP traffic identification in measuring user dissimilarity

2020 ◽  
Vol 2 (1-4) ◽  
pp. 17-28
Author(s):  
Adeyemi R. Ikuesan ◽  
Mazleena Salleh ◽  
Hein S. Venter ◽  
Shukor Abd Razak ◽  
Steven M. Furnell
Keyword(s):  
User Behavior ◽  
Recall Rate ◽  
Learning System ◽  
The Internet ◽  
Complex Nature ◽  
Web Traffic ◽  
User Identification ◽  
E Learning ◽  
Research Findings ◽  
Unit Of Measurement

AbstractThe prevalence of HTTP web traffic on the Internet has long transcended the layer 7 classification, to layers such as layer 5 of the OSI model stack. This coupled with the integration-diversity of other layers and application layer protocols has made identification of user-initiated HTTP web traffic complex, thus increasing user anonymity on the Internet. This study reveals that, with the current complex nature of Internet and HTTP traffic, browser complexity, dynamic web programming structure, the surge in network delay, and unstable user behavior in network interaction, user-initiated requests can be accurately determined. The study utilizes HTTP request method of GET filtering, to develop a heuristic algorithm to identify user-initiated requests. The algorithm was experimentally tested on a group of users, to ascertain the certainty of identifying user-initiated requests. The result demonstrates that user-initiated HTTP requests can be reliably identified with a recall rate at 0.94 and F-measure at 0.969. Additionally, this study extends the paradigm of user identification based on the intrinsic characteristics of users, exhibited in network traffic. The application of these research findings finds relevance in user identification for insider investigation, e-commerce, and e-learning system as well as in network planning and management. Further, the findings from the study are relevant in web usage mining, where user-initiated action comprises the fundamental unit of measurement.

scholarly journals CWM Global Search—The Internet Search Engine for Chemists and Biologists

2010 ◽  
Vol 2 (4) ◽  
pp. 635-644 ◽  
Author(s):  
Alexander Kos ◽  
Hans-Jürgen Himmler
Keyword(s):  
Search Engine ◽  
Web Application ◽  
Global Search ◽  
The Internet ◽  
Free Text ◽  
Biological Databases ◽  
Rich Internet Application ◽  
Meta Search Engine ◽  
Meta Search ◽  
Cas Registry

CWM Global Search is a meta-search engine allowing chemists and biologists to search the major chemical and biological databases on the Internet, by structure, synonyms, CAS Registry Numbers and free text. A meta-search engine is a search tool that sends user requests to several other search engines and/or databases and aggregates the results into a single list or displays them according to their source [1]. CWM Global Search is a web application that has many of the characteristics of desktop applications (also known as Rich Internet Application, RIA), and it runs on both Windows and Macintosh platforms. The application is one of the first RIA for scientists. The application can be started using the URL http://cwmglobalsearch.com/gsweb.

Web Based Shape Inspection System for the Forging Products Having Complicated Shapes

2007 ◽  
Vol 340-341 ◽  
pp. 719-724 ◽  
Author(s):  
K.S. Park ◽  
B.J. Kim ◽  
D.W. Kim ◽  
Young Hoon Moon
Keyword(s):  
Real Time ◽  
Measured Data ◽  
The Internet ◽  
Inspection System ◽  
Java Applet ◽  
Outer Race ◽  
Displacement Sensors ◽  
Efficient Data ◽  
Current Measuring ◽  
Shape Inspection

The outer race of the constant velocity(CV) joint is an important load-supporting automotive part, which transmits torque between the transmission and the wheel. The outer race is difficult to be forged, because its shape is very complex and the required dimensional tolerances are very stringent. Therefore, the internet based shape inspection system is developed in this study to provide quick and accurate measuring data. Proposed system uses mechanical displacement sensors to measure the shape of CV joint that has six inner ball grooves, and commercially available Lab- View program is used to process measured data into the dimensional shape. Developed program provides a simple user interface that enables users to have real-time access of data measured from industrial production lines. Furthermore, the measured data can be exchanged via the internet between users and forging system operators. A java applet helped the system connection via internet. A data, IP access, is transmitted to the packet by TCP/IP. Our proposed system has many advantages over current measuring systems including fast and efficient data processing by real-time measuring, and system flexibility.

scholarly journals Staying Active under Restrictions: Changes in Type of Physical Exercise during the Initial COVID-19 Lockdown

2021 ◽  
Vol 18 (22) ◽  
pp. 12015
Author(s):  
Valentin Benzing ◽  
Sanaz Nosrat ◽  
Alireza Aghababa ◽  
Vassilis Barkoukis ◽  
Dmitriy Bondarev ◽  
...  
Keyword(s):  
Risk Factors ◽  
Physical Exercise ◽  
Rural Areas ◽  
Muscular Strength ◽  
Online Survey ◽  
Free Text ◽  
Context Change ◽  
Text Input ◽  
Adult Participants ◽  
Type Of Exercise

The COVID-19 pandemic and the associated governmental restrictions suddenly changed everyday life and potentially affected exercise behavior. The aim of this study was to explore whether individuals changed their preference for certain types of physical exercise during the pandemic and to identify risk factors for inactivity. An international online survey with 13,881 adult participants from 18 countries/regions was conducted during the initial COVID-19 related lockdown (between April and May 2020). Data on types of exercise performed during and before the initial COVID-19 lockdown were collected, translated, and categorized (free-text input). Sankey charts were used to investigate these changes, and a mixed-effects logistic regression model was used to analyze risks for inactivity. Many participants managed to continue exercising but switched from playing games (e.g., football, tennis) to running, for example. In our sample, the most popular exercise types during the initial COVID-19 lockdown included endurance, muscular strength, and multimodal exercise. Regarding risk factors, higher education, living in rural areas, and physical activity before the COVID-19 lockdown reduced the risk for inactivity during the lockdown. In this relatively active multinational sample of adults, most participants were able to continue their preferred type of exercise despite restrictions, or changed to endurance type activities. Very few became physically inactive. It seems people can adapt quickly and that the constraints imposed by social distancing may even turn into an opportunity to start exercising for some. These findings may be helpful to identify individuals at risk and optimize interventions following a major context change that can disrupt the exercise routine.

User Identification by the Free-Text Keystroke Dynamics

2018 ◽  
Author(s):  
Evgeny Yurievich Kostyuchenko ◽  
Ivan Viktorovich ◽  
Botna Renko ◽  
Alexander Alexandrovich Shelupanov
Keyword(s):  
Free Text ◽  
Keystroke Dynamics ◽  
User Identification
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