Biometric identity-based cryptography for e-Government environment

Government information is a vital asset that must be kept in a trusted environment and efficiently managed by authorised parties. Even though e-Government provides a number of advantages, it also introduces a range of new security risks. Sharing confidential and top-secret information in a secure manner among government sectors tend to be the main element that government agencies look for. Thus, developing an effective methodology is essential and it is a key factor for e-Government success. The proposed e-Government scheme in this paper is a combination of identity-based encryption and biometric technology. This new scheme can effectively improve the security in authentication systems, which provides a reliable identity with a high degree of assurance. In addition, this paper demonstrates the feasibility of using Finite-state machines as a formal method to analyse the proposed protocols

Modelling and simulation of a biometric identity-based cryptography

Government information is a vital asset that must be kept in a trusted environment and efficiently managed by authorised parties. Even though e-Government provides a number of advantages, it also introduces a range of new security risks. Sharing confidential and top-secret information in a secure manner among government sectors tend to be the main element that government agencies look for. Thus, developing an effective methodology is essential and it is a key factor for e-Government success. The proposed e-Government scheme in this paper is a combination of identity-based encryption and biometric technology. This new scheme can effectively improve the security in authentication systems, which provides a reliable identity with a high degree of assurance. In addition, this paper demonstrates the feasibility of using Finite-state machines as a formal method to analyse the proposed protocols

Human user authentication based on mouse dynamics: a feasibility study

Security problems have been discussed for a long time in the past recent decades in many fields such as communication, networking and user authentication. Security and authentication methods have also been explored for a long time by many researchers, and many ecient ways have been developed and used in modern society. Password and fingerprint based user authentication methods are most common user authentication methods being used in our daily lives. With computers and smart phones population growing vastly, we need to put more attention on the security methods. However, those traditional authentication methods are not safe and ecient enough. Passwords are stolen and revealed to hackers, while fingerprint can be easily got from an authenticated person. We moved our eyes on another way of security and authentication- biometric kinesiology. The muscle in our body can remember the movement if we practiced an action a lot, and that memory is built in the body, not in our brain memory, which means that we cannot forget a practiced action in the way we forget a password. We proposed to use the action with mouse from an authenticated user as the password of a system, in which only the user perform right action can be regarded as an authenticated user. Otherwise the system will reject the user. This movement is hard to mimic unless the hacker do a lot of practice of that certain movement and do exactly the same as an authenticated user. This is very difficult because we modified the normal mouse and the mouse will not move as the hacker expect. What’s more, only the authenticated user knows how was the mouse be modified and how to act to adjust to that modification. In this way our proposed approach is much safer than the above traditional security and authentication methods. However, this is a feasibility study and more experiment will be done to prove our proposal and we will discuss it in the future work chapter

Improving information security in e-banking by using biometric fingerprint : a case of major bank in Malaysia

In this paper biometric fingerprint technology will define and discuss as new best approach identification and authentication customers for online internet banking, and how biometric fingerprint will improve the internet banking protect its assets. Background will be produced to present how authentication and identification have developed and improved through the applications successful that have implemented biometric technology to protect its asset; then a case of major bank in Malaysia will be taken as a case study. By answering the question, why does biometric fingerprint need to come forefront as a great method of authentication in online banking environment? The findings have found that there are reasons and factors for higher security as a near perfect and biometric fingerprint authentication will be indicated to be the solution to answer this call

Study of Applicability of Virtual Users in Evaluating Multimodal Biometrics

Abstract. A new approach of enlarging fused biometric databases is presented. Fusion strategies based upon matching score are applied on active biometrics verification scenarios. Consistent biometric data of two traits are used in test scenarios of handwriting and speaker verification. The fusion strategies are applied on multimodal biometrics of two different user types. The real users represent two biometric traits captured from one person. The virtual users are considered as the combination of two traits captured from two discrete users. These virtual users are implemented for database enlargement. In order to investigate the impact of these virtual users, test scenarios using three different semantics of handwriting and speech are accomplished. The results of fused handwriting and speech of exclusively real users and additional virtual users are compared and discussed

Multiple classifiers in biometrics. Part 2: Trends and challenges

The present paper is Part 2 in this series of two papers. In Part 1 we provided an introduction to Multiple Classifier Systems (MCS) with a focus into the fundamentals: basic nomenclature, key elements, architecture, main methods, and prevalent theory and framework. Part 1 then overviewed the application of MCS to the particular field of multimodal biometric person authentication in the last 25 years, as a prototypical area in which MCS has resulted in important achievements. Here in Part 2 we present in more technical detail recent trends and developments in MCS coming from multimodal biometrics that incorporate context information in an adaptive way. These new MCS architectures exploit input quality measures and pattern-specific particularities that move apart from general population statistics, resulting in robust multimodal biometric systems. Similarly as in Part 1, methods here are described in a general way so they can be applied to other information fusion problems as well. Finally, we also discuss here open challenges in biometrics in which MCS can play a key roleThis work was funded by projects CogniMetrics (TEC2015-70627-R) from MINECO/FEDER and RiskTrakc (JUST-2015-JCOO-AG-1). Part of this work was conducted during a research visit of J.F. to Prof. Ludmila Kuncheva at Bangor University (UK) with STSM funding from COST CA16101 (MULTI-FORESEE

Determining the Personal identity based on Handwriting as a Biometric identification

This paper describes methods for off-line identification of the writer based on handwriting features. Different methods for extracting and combining features are reported in the literature for pattern recognition purposes. Many aspects have influence over the writer identification such as: symmetry, slant angle, percent of black and white pixels, height/width ratio of the letters, direction of the base line, the position of the horizontal and vertical lines in the segments, histograms, contour profiles, spots, etc. The method creates a feature-vector associated with a writing manner of an individual and computes the correlation measure to express the similarity with the previously stored handwritten samples of the Cyrillic letters. The presented system is based on image processing and pattern recognition methods. The approach analyses the handwriting as an image-texture, it is content independent and uses feature set based on the global statistical, structural and topological characteristics. An experiment was performed to discover the most reliable features that contribute to the identification of the writer. Handwritten biometric identification is applicable in many areas such as: security systems, forensics, financial etc

Visual identification by signature tracking

We propose a new camera-based biometric: visual signature identification. We discuss the importance of the parameterization of the signatures in order to achieve good classification results, independently of variations in the position of the camera with respect to the writing surface. We show that affine arc-length parameterization performs better than conventional time and Euclidean arc-length ones. We find that the system verification performance is better than 4 percent error on skilled forgeries and 1 percent error on random forgeries, and that its recognition performance is better than 1 percent error rate, comparable to the best camera-based biometrics