scholarly journals Combining Cryptography with EEG Biometrics

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Robertas Damaševičius ◽  
Rytis Maskeliūnas ◽  
Egidijus Kazanavičius ◽  
Marcin Woźniak
Keyword(s):  
Error Rate ◽  
User Authentication ◽  
Discrete Logarithm ◽  
Security Analysis ◽  
Experimental Results ◽  
Biometric Authentication ◽  
Equal Error Rate ◽  
Eeg Data ◽  
Authentication System ◽  
Biometric Cryptosystem

Cryptographic frameworks depend on key sharing for ensuring security of data. While the keys in cryptographic frameworks must be correctly reproducible and not unequivocally connected to the identity of a user, in biometric frameworks this is different. Joining cryptography techniques with biometrics can solve these issues. We present a biometric authentication method based on the discrete logarithm problem and Bose-Chaudhuri-Hocquenghem (BCH) codes, perform its security analysis, and demonstrate its security characteristics. We evaluate a biometric cryptosystem using our own dataset of electroencephalography (EEG) data collected from 42 subjects. The experimental results show that the described biometric user authentication system is effective, achieving an Equal Error Rate (ERR) of 0.024.

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.

Misuse Detection for Mobile Devices Using Behaviour Profiling

2011 ◽  
Vol 1 (1) ◽  
pp. 41-53 ◽  
Author(s):  
Fudong Li ◽  
Nathan Clarke ◽  
Maria Papadaki ◽  
Paul Dowland
Keyword(s):  
Mobile Devices ◽  
Error Rate ◽  
Text Message ◽  
Modern Society ◽  
Experimental Results ◽  
Equal Error Rate ◽  
Misuse Detection ◽  
General Application ◽  
Point Of Entry ◽  
Application Specific

Mobile devices have become essential to modern society; however, as their popularity has grown, so has the requirement to ensure devices remain secure. This paper proposes a behaviour-based profiling technique using a mobile user’s application usage to detect abnormal activities. Through operating transparently to the user, the approach offers significant advantages over traditional point-of-entry authentication and can provide continuous protection. The experiment employed the MIT Reality dataset and a total of 45,529 log entries. Four experiments were devised based on an application-level dataset containing the general application; two application-specific datasets combined with telephony and text message data; and a combined dataset that included both application-level and application-specific. Based on the experiments, a user’s profile was built using either static or dynamic profiles and the best experimental results for the application-level applications, telephone, text message, and multi-instance applications were an EER (Equal Error Rate) of 13.5%, 5.4%, 2.2%, and 10%, respectively.

scholarly journals A User Authentication Enabled Piezoelectric Force Touch System for the Internet of Things

2020 ◽  
Author(s):  
Anbiao Huang ◽  
Shuo Gao ◽  
Arokia Nathan
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Internet Of Things ◽  
Error Rate ◽  
User Authentication ◽  
The Internet ◽  
Equal Error Rate ◽  
High User ◽  
Iot Applications ◽  
The Internet Of Things

In Internet of Things (IoT) applications, among various authentication techniques, keystroke authentication methods based on a user’s touch behavior have received increasing attention, due to their unique benefits. In this paper, we present a technique for obtaining high user authentication accuracy by utilizing a user’s touch time and force information, which are obtained from an assembled piezoelectric touch panel. After combining artificial neural networks with the user’s touch features, an equal error rate (EER) of 1.09% is achieved, and hence advancing the development of security techniques in the field of IoT.

scholarly journals Security analysis and enhancements of an improved multi-factor biometric authentication scheme

2017 ◽  
Vol 13 (8) ◽  
pp. 155014771772430 ◽  
Author(s):  
YoHan Park ◽  
KiSung Park ◽  
KyungKeun Lee ◽  
Hwangjun Song ◽  
YoungHo Park
Keyword(s):  
User Authentication ◽  
Security Analysis ◽  
User Anonymity ◽  
Authentication Scheme ◽  
Biometric Authentication ◽  
Remote User Authentication ◽  
Dynamic Id ◽  
User Authentication Scheme ◽  
Guessing Attack ◽  
Remote User

Many remote user authentication schemes have been designed and developed to establish secure and authorized communication between a user and server over an insecure channel. By employing a secure remote user authentication scheme, a user and server can authenticate each other and utilize advanced services. In 2015, Cao and Ge demonstrated that An’s scheme is also vulnerable to several attacks and does not provide user anonymity. They also proposed an improved multi-factor biometric authentication scheme. However, we review and cryptanalyze Cao and Ge’s scheme and demonstrate that their scheme fails in correctness and providing user anonymity and is vulnerable to ID guessing attack and server masquerading attack. To overcome these drawbacks, we propose a security-improved authentication scheme that provides a dynamic ID mechanism and better security functionalities. Then, we show that our proposed scheme is secure against various attacks and prove the security of the proposed scheme using BAN Logic.

scholarly journals Ratiometric Impedance Sensing of Fingers for Robust Identity Authentication

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Hyung Wook Noh ◽  
Chang-Geun Ahn ◽  
Hyoun-Joong Kong ◽  
Joo Yong Sim
Keyword(s):  
Error Rate ◽  
Classification Accuracy ◽  
Structural Information ◽  
Identity Authentication ◽  
Biometric Authentication ◽  
Impedance Sensing ◽  
Authentication System ◽  
The Difference ◽  
Spectral Patterns ◽  
Physiological Variations

Abstract We present a novel biometric authentication system enabled by ratiometric analysis of impedance of fingers. In comparison to the traditional biometrics that relies on acquired images of structural information of physiological characteristics, our biological impedance approach not only eliminates any practical means of making fake copies of the relevant physiological traits but also provides reliable features of biometrics using the ratiometric impedance of fingers. This study shows that the ratiometric features of the impedance of fingers in 10 different pairs using 5 electrodes at the fingertips can reduce the variation due to undesirable factors such as temperature and day-to-day physiological variations. By calculating the ratio of impedances, the difference between individual subjects was amplified and the spectral patterns were diversified. Overall, our ratiometric analysis of impedance improved the classification accuracy of 41 subjects and reduced the error rate of classification from 29.32% to 5.86% (by a factor of 5).

An Indirect Fingerprint Authentication Scheme in Cloud Computing

2014 ◽  
Vol 484-485 ◽  
pp. 986-990 ◽  
Author(s):  
Xing Chen Jiang ◽  
Jian De Zheng
Keyword(s):  
Cloud Computing ◽  
User Authentication ◽  
Security Analysis ◽  
Critical Issue ◽  
Authentication Scheme ◽  
Security Threat ◽  
Biometric Template ◽  
Security Challenges ◽  
Cryptographic Keys ◽  
Biometric Cryptosystem

The cloud computing offers dynamically scalable online resources provisioned as a service over the Internet cheaply. However, the security challenges it poses are equally striking. The reliable user authentication techniques are required to combat the rising security threat in cloud communications. Due to the non-denial requirements of remote user authentication scheme, it is most commonly achieved using some form of biometrics-based method. Fingerprint authentication is one of the popular and effective approaches to allow the only authorized users to access the cryptographic keys. While the critical issue in remote biometric cryptosystem is to protect the template of a user stored in a database. The biometric template is not secure and the stolen templates cannot be revoked, which is easy to leak user identity information. To overcome these shortcomings, in this paper, an indirect fingerprint authentication scheme is proposed. Further, we apply this secure scheme to the cloud system combing with PKI mechanism. At last, a comprehensive and detailed security analysis of the proposed scheme in cloud computing is provided.

Palm Vein Recognition Algorithm Using Curvelet and Wavelet

2013 ◽  
Vol 710 ◽  
pp. 655-659
Author(s):  
Zhi Xian Jiu ◽  
Qiang Li
Keyword(s):  
Wavelet Transform ◽  
Error Rate ◽  
Minimum Distance ◽  
Image Database ◽  
Recognition System ◽  
Recognition Algorithm ◽  
Experimental Results ◽  
Equal Error Rate ◽  
Vein Recognition ◽  
Palm Vein

In this paper we report on a curvelet and wavelet based palm vein recognition algorithm. Using our palm vein image database, we employed minimum distance classifier to test the performance of the system. Experimental results show that the algorithm based on cuvelet transform can reach equal error rate of 1.7%, and the algorithm based on wavelet transform can only reach equal error rate of 2.3%, indicating that the curvelet based palm vein recognition system improves representation.

Sign in / Sign up

Export Citation Format

Share Document