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Current mobile banking protocols simply are not as well guarded as their Internet counterparts during the transactions between a mobile device and a financial institution. Recently, many mobile banking protocols using public-key cryptography have been proposed. However, they are designed to provide a basic protection for traditional flow of payment data as they only rely on basic identification and verification mechanisms, which is vulnerable to attack and increase the user΄s risk. In this paper we propose a new secure mobile banking protocol that provides strong authentication mechanisms. These mechanisms rely on highly usable advanced multifactor authentication technologies i.e. (biometrics and smart cards). The proposed mobile banking protocol not only achieves a completely secure protection for the involved parties and their financial transactions but also minimizes the computational operations and the communication passes between them. An analysis and a proof of the proposed protocol security properties will be provided within this paper. [ABSTRACT FROM AUTHOR]

In this study, a new approach based on logic synthesis to match feature points from fingerprint images is developed and introduced. For fingerprint matching we propose logic minimization method to make matching process easy and fast. We think that use logic minimization method might be used as a reliable in fingerprint recognition. [ABSTRACT FROM AUTHOR]

This paper elucidates the social, ethical, cultural, technical, and legal implications / challenges around the implementation of a biometric based unique identification (UID) number project. The Indian government has undertaken a huge effort to issue UID numbers to its residents. Apart from possible challenges that are expected in the implementation of UID, the paper also draws parallels from Social Security Number system in the US. We discuss the setbacks of using the Social Security Number as a unique identifier and how to avoid them with the system being proposed in India. We discuss the various biometric techniques used and a few recommendations associated with the use of biometrics. [ABSTRACT FROM AUTHOR]

Telemedicine is the process by which electronic, visual and audio communications are used to support practitioners at remote sites with diagnosis and consultation procedures, such as remote clinical examinations and medical image transfers. Telemedicine is legally regulated by laws and constraints regarding the access of data contained in Personal Medical Files. These requirements are given by international entities such as IHE. They often specify the required functionalities to meet requirements of information exchange in the medical field. These functionalities are presented in this paper and outline some technical examples for their implementation in each level: authentication, communication, data storage, tracking and patient identification. [ABSTRACT FROM AUTHOR]

Newborn and infant personal authentication is a critical issue for hospital, birthing centers and other institutions where multiple births occur, which has not been well studied in the past. In this paper, we propose a novel online newborn personal authentication system for this issue based on footprint recognition. Compared with traditional offline footprinting scheme, the proposed system can capture digital footprint images with high quality. We also develop a preprocessing method for orientation and scale normalization. In this way, a coordinate system is defined to align the images and a region of interest (ROI) is cropped. In recognition stage, Band Limited Phase-Only Correlation (BLPOC) based method is exploited for feature extraction and matching. A newborn footprint database is established to examine the performance of the proposed system, and the promising experimental results demonstrated the effectiveness of proposed system. [ABSTRACT FROM AUTHOR]

The automatic person identification is a significant component in any security biometric system because of the challenges and the significant number of the applications that require a high safety. A biometric system based solely on one template (representation) is often not able to meet such desired performance requirements. Identification based on multiple representations represents a promising tendency. In this context, we propose here a multi-representation biometric system for person recognition using palm images and by integrating two different representations of the palmprint. Two ensembles of matchers that use two different feature representation schemes of the images are considered. The two different feature extraction methods are the block based 2D Discrete Cosine Transform (2D-DCT) and the phase information in 2D Discrete Fourier Transform (2D-DFT) that are complementing each other in terms of identification accuracy. Finally the two ensembles are combined and the fusion is applied at the matching-score level. Using the PolyU palmprint database, The results showed the effectiveness of the proposed multi-representation biometric system in terms of the recognition rate. [ABSTRACT FROM AUTHOR]

In this paper we have proposed a biometric-based authentication system based on rough set theory. The system employed signature for authentication purpose. The major functional blocks of the proposed system are presented. Information is extracted as time functions of various dynamic properties of the signatures. We apply our methodology to global features extracted from a 108-users database. Thirty-one features were identified and extracted from each signature. Rough set approach has resulted in a reduced set of nine features that were found to capture the essential characteristics required for signature identification. Low error rates obtained in experiments illustrate the feasibility of using Rough Set as a promising technique for online signature identification systems. [ABSTRACT FROM AUTHOR]

This paper evaluates the performance of face and speaker verification techniques in the context of a mobile environment. The mobile environment was chosen as it provides a realistic and challenging test-bed for biometric person verification techniques to operate. For instance the audio environment is quite noisy and there is limited control over the illumination conditions and the pose of the subject for the video. To conduct this evaluation, a part of a database captured during the ˵Mobile Biometry″ (MOBIO) European Project was used. In total there were nine participants to the evaluation who submitted a face verification system and five participants who submitted speaker verification systems. The results have shown that the best performing face and speaker verification systems obtained the same level of performance, respectively 10.9% and 10.6% of HTER. [ABSTRACT FROM AUTHOR]

Eyelashes and reflections occluding the iris region are noise factors that degrade the performance of iris recognition. If these factors are not eliminated in iris segmentation phase, they are incorrectly considered as the iris region. Thus, produce false iris pattern information which decreases the recognition rate. In this paper a statistical approach is used to improve iris segmentation phase eliminating this noise from none constrain images, which is composed in three parts, finding the pupil and limbus boundary, reflection detection and eyelash detection. First an edge map is calculated using canny filter then the Circular Hough Transform is used to improve circle parameter finding. An intensity variation analysis is use to recognize a strong reflection. Eyelashes are classified in two categories, separable and multiple. Intensity variances are used to detect multiple eyelashes and an edge detector to localize separable eyelashes. The results show that statistics are useful to decide when is necessary applied the eyelash detector. [ABSTRACT FROM AUTHOR]

In this paper, we present a palmprint recognition method which combines local binary pattern (LBP) and cellular automata. The LBP descriptor is proposed as a unifying texture model that describes the formation of a texture with micro-textons and their statistical placement rules. Because texture is one of the most importent features in palmprint image, so we think the features based on LBP will be good discriminative for palmprint identification. Cellular automata can be generally described as discrete dynamic systems completely defined by a set of rules in a local neighborhood. In this paper, we use cellular automata to extract features as the part of feature vector. The experiments conducted on Polytechnic University Palmprint Database I demonstrates the effectiveness of proposed method. [ABSTRACT FROM AUTHOR]

In this paper, we propose a novel online newborn personal authentication system based on footprint recognition. Compared with traditional offline footprinting scheme, the proposed system can capture digital footprint images with high quality. We also develop a preprocessing method for orientation and scale normalization. In this way, a coordinate system is defined to align the images and a region of interest (ROI) is cropped. In recognition stage, several representative subspace learning methods such as PCA, LDA are exploited for recognition. A newborn footprint database is established to examine the performance of the proposed system, and the promising experimental results demonstrate the effectiveness of proposed system. [ABSTRACT FROM AUTHOR]

This paper reviews some exploratory research focused on developing a usability methodology based on objective biometrics computing using physiological data (ECG, respiration, and GSR sensors, as well as an infrared eye tracker) as well as behavior data (mouse and keystroke input). Following a high level literature review, various biometrics are discussed with the goal of motivating further study into the development of a methodology for usability testing, including the assessment of user satisfaction. Lessons learned and suggestions for future work were also discussed. [ABSTRACT FROM AUTHOR]

The selection of the optimal feature subset and the classification has become an important issue in the field of iris recognition. In this paper we propose several methods for iris feature subset selection and vector creation. In this paper we propose a new feature extraction method for iris recognition based on contourlet transform. Contourlet transform captures the intrinsic geometrical structures of iris image. For reducing the feature vector dimensions we use the method for extract only significant bit and information from normalized iris images. In this method we ignore fragile bits. At last, the feature vector is created by two methods: Co-occurrence matrix properties and contourlet coefficients. For analyzing the desired performance of our proposed method, we use the CASIA dataset, which is comprised of 108 classes with 7 images in each class and each class represented a person. Experimental results show that the proposed increase the classification accuracy and also the iris feature vector length is much smaller versus the other methods. [ABSTRACT FROM AUTHOR]

In different methods of Biometrics, recognition by iris images in recent years has been taken into consideration by researchers as one of the common methods of identification like passwords, credit cards or keys. Iris recognition a new biometric technology has great advantages such as variability, stability and security. In this paper we propose a new feature extraction method for iris recognition based on contourlet transform. Contourlet transform captures the intrinsic geometrical structures of iris image. It decomposes the iris image into a set of directional sub-bands with texture details captured in different orientations at various scales so for reducing the feature vector dimensions we use the method for extract only significant bit and information from normalized iris images. In this method we ignore fragile bits. At last the feature vector is approximated by non linear approximation coefficient. Experimental results show that the proposed method reduces processing time and increase the classification accuracy and outperforms the wavelet based method. [ABSTRACT FROM AUTHOR]

In this paper, we propose a novel approach for palmprint recognition, which combine band-limited phase-only correlation method and directional representation of palmprint. We also exploit peak-to-sidelobe ratio as the similarity measure. The results of experiments conducted on Hong Kong Polytechnic University Palmprint Database show that the proposed approach has higher accurate recognition rates and lower equal error rates than that of the approach, which combine band-limited phase-only correlation and original representation. [ABSTRACT FROM AUTHOR]

In this paper we propose a new biometric-based Iris feature extraction system. The system automatically acquires the biometric data in numerical format (Iris Images) by using a set of properly located sensors. We are considering camera as a high quality sensor. Iris Images are typically color images that are processed to gray scale images. Then the Feature extraction algorithm is used to detect ˵IRIS Effective Region (IER)″ and then extract features from ˵IRIS Effective Region (IER)″ that are numerical characterization of the underlying biometrics. Later on this work will be helping to identify an individual by comparing the feature obtained from the feature extraction algorithm with the previously stored feature by producing a similarity score. This score will be indicating the degree of similarity between a pair of biometrics data under consideration. Depending on degree of similarity, individual can be identified. [ABSTRACT FROM AUTHOR]

An information theoretic framework is established to analyze the performance of biometric security systems. Two performance metrics, namely privacy, measured by the normalized equivocation rate of the biometric measurements, and security, measured by the rate of the key generated from the biometric measurements, are first defined. A fundamental tradeoff between these two metrics is then identified. The scenario in which a potential attacker does not have side information is considered first. The privacy-security region, which characterizes the above-noted tradeoff, is derived for this case. An important role of common information among random variables is revealed in perfect privacy biometric security systems. The scenario in which the attacker has side information is then considered. Inner and outer bounds on the privacy-security tradeoff are derived in this case. [ABSTRACT FROM AUTHOR]

Most biometric authentication algorithms make use of a similarity score that defines how similar two templates are according to a threshold and the accuracy of the results are expressed in terms of a False Reject Rate (FRR) or False Accept Rate (FAR) that is estimated using the training data set. A confidence interval is assigned to any claim of accuracy with 90% being commonly assumed for biometric-based authentication systems. However, these confidence intervals may not be as accurate as is presumed. In this paper, we report the results of experiments measuring the performance of the widely-used subset bootstrap approach to estimating the confidence interval of FAR. We find that the coverage of the FAR confidence intervals estimated by the subset bootstrap approach is reduced by the dependence between two similarities when they come from two individual pairs shared with a common individual. This is because subset bootstrap requires the independence of different subsets. To deal with this, we present a second-level partition to the similarity score set between different individuals, producing what we call a subset false accept rate (SFAR) bootstrap estimation. The experimental results show that the proposed procedures greatly increase the coverage of the FAR confidence intervals. [ABSTRACT FROM AUTHOR]

In recent years there has been a rapid increase in the need for accurate and reliable personal identification so biometrics has received more and more attention. Iris recognition as a biometrics has a satisfying performance due to its high reliability and non-invasion. The iris recognition system consists of four processes: image acquisition, preprocessing, feature extraction and matching. In an iris recognition system, preprocessing, especially iris localization plays a very important role. The speed and performance of an iris recognition system is crucial and it is limited by the results of iris localization to a great extent. In this paper, we propose new pupil localization for finding the iris inner boundary based on wavelet transform and analytic geometry relations. Extensive experimental results show that the proposed algorithm in addition to higher speed and lower calculation cost and simplicity, has got an acceptable accuracy for internal boundary localization. [ABSTRACT FROM AUTHOR]

We propose a biometrics-based(fingerprint)Encryption / Decryption Scheme, in which unique key is generated using partial portion of combined sender΄s and receiver΄s fingerprints. From this unique key a random sequence is generated, which is used as an asymmetric key for both Encryption and Decryption. Above unique Key is send by the sender after Watermaking it in sender΄s fingerprint along with Encrypted Message. The computational requirement and network security features are addressed. Proposed system has a advantage that for public key, it has not to search from a database and security is maintained. [ABSTRACT FROM AUTHOR]

Face recognition, fingerprint recognition and other biometric technology are used widely now, and requirement of safety and reliability of Access Control in the market is getting higher and higher. The paper designs and implements Intelligent Biometric Access Control System based on DSP and NIR technology. It mostly describes the overall design, embedded system design, near infrared camera design, face recognition and verification algorithm design in server. By using NIR technology the system fundamentally change the impact of illumination on face recognition and resolve the limitations of face recognition in applications. [ABSTRACT FROM AUTHOR]

Due to difficulty in monitoring the attendance of members in the higher education institution (HEI), the HEI management has recognized the need to conduct a study on the adoption of fingerprint system. The study identified the appropriate indexing model and developed a questionnaire that suits for the environment. The higher education institution selected for this study is International Islamic University Malaysia (IIUM). The target groups were selected across a sample of the organisation΄s members. The returned questionnaires were analyzed using a standard statistical tool. Reliability and normality testing were deployed to ensure that the data is reliable and normal for further testing. Spearman΄s correlation and Kruskal Wallis were used to find the relation between elements of innovativeness, optimism, discomfort and insecurity. The findings have revealed that the innovativeness and optimism have a positive relation with the users΄ readiness. Meanwhile, discomfort and insecurity gave a negative relation to the faculty members΄. This indicates that the faculty member is aware of the technology and optimist with the implementation of the technology in their organization. However, they still feel insecure and discomfort with the justification and impact of the implementation. [ABSTRACT FROM AUTHOR]