A Behavioral Biometrics User Authentication Study Using Motion Data from Android Smartphones

2016 ◽  
Author(s):  
Javid Maghsoudi ◽  
Charles C. Tappert
Keyword(s):  
User Authentication ◽  
Behavioral Biometrics ◽  
Motion Data

Passive User Authentication Utilizing Behavioral Biometrics for IIoT Systems

2021 ◽  
pp. 1-1
Author(s):  
Guozhu Zhao ◽  
Pinchang Zhang ◽  
Yulong Shen ◽  
Xiaohong Jiang
Keyword(s):  
User Authentication ◽  
Behavioral Biometrics

Behavioral Biometrics

2010 ◽  
pp. 101-120 ◽  
Author(s):  
Kenneth Revett
Keyword(s):  
User Authentication ◽  
Error Rates ◽  
Keystroke Dynamics ◽  
Behavioral Biometrics ◽  
Authentication Mechanism ◽  
Computer Based ◽  
Authentication System ◽  
Novel Approaches ◽  
New Form ◽  
Minimal Effort

Behavioral biometrics is a relatively new form of authentication mechanism which relies on the way a person interacts with an authentication device. Traditional instances of this approach include voice, signature, and keystroke dynamics. Novel approaches to behavioral biometrics include biosignals, such as the electroencephalogram and the electrocardiogram. The biosignal approach to user authentication has been shown to produce equal error rates on par with more traditional behavioral biometric approaches. In addition, through a process similar to biofeedback, users can be trained with minimal effort to produce computer-based input via the manipulations of endogenous biosignal patterns. This chapter discusses the use of biosignal based biometrics, highlighting key studies and how this approach can be integrated into a multibiometric user authentication system.

Behavioral Biometrics for User Authentication Using Self-Refreshing SOM

2017 ◽  
Vol 23 (11) ◽  
pp. 11078-11082
Author(s):  
Chee Siong Teh ◽  
Juen Ching Wong ◽  
Ming Leong Yii
Keyword(s):  
User Authentication ◽  
Behavioral Biometrics

scholarly journals A User Authentication Scheme Using Physiological and Behavioral Biometrics for Multitouch Devices

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Chorng-Shiuh Koong ◽  
Tzu-I Yang ◽  
Chien-Chao Tseng
Keyword(s):  
User Authentication ◽  
Mobile Network ◽  
Authentication Scheme ◽  
Security Level ◽  
Behavioral Biometrics ◽  
Vending Machines ◽  
Privacy Leakage ◽  
Authentication Mechanism ◽  
User Authentication Scheme ◽  
Biometric Information

With the rapid growth of mobile network, tablets and smart phones have become sorts of keys to access personal secured services in our daily life. People use these devices to manage personal finances, shop on the Internet, and even pay at vending machines. Besides, it also helps us get connected with friends and business partners through social network applications, which were widely used as personal identifications in both real and virtual societies. However, these devices use inherently weak authentication mechanism, based upon passwords and PINs that is not changed all the time. Although forcing users to change password periodically can enhance the security level, it may also be considered annoyances for users. Biometric technologies are straightforward because of the simple authentication process. However, most of the traditional biometrics methodologies require diverse equipment to acquire biometric information, which may be expensive and not portable. This paper proposes a multibiometric user authentication scheme with both physiological and behavioral biometrics. Only simple rotations with fingers on multitouch devices are required to enhance the security level without annoyances for users. In addition, the user credential is replaceable to prevent from the privacy leakage.

A Preliminary Study on Non-Intrusive User Authentication Method Using Smartphone Sensors

2013 ◽  
Vol 284-287 ◽  
pp. 3270-3274 ◽  
Author(s):  
Chien Cheng Lin ◽  
Chin Chun Chang ◽  
De Ron Liang ◽  
Ching Han Yang
Keyword(s):  
Error Rate ◽  
User Authentication ◽  
Experimental Results ◽  
Equal Error Rate ◽  
Behavioral Biometrics ◽  
Reported Study ◽  
Smartphone Sensors ◽  
Preliminary Study ◽  
Orientation Sensor

This paper proposes a non-intrusive authentication method based on two sensitive apparatus of smartphones, namely, the orientation sensor and the touchscreen. We have found that these two sensors are capable of capturing behavioral biometrics of a user while the user is engaged in relatively stationary activities. The experimental results with respect to two types of flick operating have an equal error rate of about 3.5% and 5%, respectively. To the best of our knowledge, this work is the first publicly reported study that simultaneously adopts the orientation sensor and the touchscreen to build an authentication model for smartphone users. Finally, we show that the proposed approach can be used together with existing intrusive mechanisms, such as password and/or fingerprints, to build a more robust authentication framework for smartphone users.

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