Using an Active Shape Structural Model for Biometric Sketch Recognition

Govindaraju²

2008

IJBM

264

118

This study is a survey and classification of the state-of-the-art in behavioural biometrics which is based on skills, style, preference, knowledge, motor-skills or strategy used by people while accomplishing different everyday tasks such as driving an automobile, talking on the phone or using a computer. The authors examine current research in the field and analyse the types of features used to describe different types of behaviour. After comparing accuracy rates for verification of users using different behavioural biometric approaches, researchers address privacy issues which arise or might arise in the future with the use of behavioural biometrics.

Section: Behavioural Biometricsmentioning

confidence: 99%

Behavioural biometrics: a survey and classification

Govindaraju²

2008

IJBM

264

118

“…Bromme et al [7,3] proposed a biometric sketch authentication method based on sketch recognition and a user's personal knowledge about the drawings content. The system directs a user to create a simple sketch for example of three circles and each user is free to do so in any way he pleases.…”

Section: Biometric Sketchmentioning

confidence: 99%

Human Computer Interaction Based Intrusion Detection

Fourth International Conference on Information Technology (ITNG'07)

2007

In this paper we survey the state of the art in human computer interaction based biometrics which are based on abilities, style, preference, knowledge, or strategy used by people while working with a computer. We examine current research and analyze the types of features used to describe HCI behavior. After comparing accuracy rates for verification of users using different HCI-based biometric approaches we address privacy issues which arise with the use of HCI dependant biometrics. Finally, we present results of our experiments with behavior-based intrusion detection in online game networks based on the strategy utilized by the players.

“…This can be achieved by comparing new moves made by the player with predicted ones from models for different players and using the achieved accuracy scores as an indication of which profile models which player. 4) Biometric Sketch: Bromme et al [28,29] proposed a biometric sketch authentication method based on sketch recognition and a user's personal knowledge about the drawings content. The system directs a user to create a simple sketch for example of three circles and each user is free to do so in any way he pleases.…”

Section: B Software Interaction Based Biometricsmentioning

confidence: 99%

“…First group is made up of those biometrics which are based on direct human interaction with input devices such as keyboard [4][5][6][7][8][9][10], computer mouse [11][12][13][14][15], and haptics [16][17][18] which rely on supposedly innate, unique and stable muscle actions [19] and those biometrics which are based on advanced human behavior such as strategy, knowledge or skill exhibited by the user during interaction with different software [3]. Examples of such high level HCI-based behavioral biometrics include: email behavior [20,21], programming style [22][23][24], utilized online game strategy [25][26][27], biometric sketch [28,29], and command line lexicon [30][31][32][33].…”

Section: Introductionmentioning

confidence: 99%

Direct and Indirect Human Computer Interaction Based Biometrics

Govindaraju

2007

JCP

In this paper we survey the state of the art in direct and indirect human computer interaction based biometrics. Direct HCI biometrics are based on abilities, style, preference, knowledge, or strategy used by people while working with a computer. The indirect HCI-based biometrics are events that can be obtained by monitoring users’ HCI behavior indirectly via observable low-level actions of computer software. We examine current research and analyze the types of features used to describe HCI behavior. After comparing accuracy rates for verification of users using different HCI- based biometric approaches we address privacy issues which arise with the use of HCI dependant biometrics. Finally, we present results of our experiments with direct and indirect HCI-based behavioral biometrics employed as a part of an intrusion detection system.