Biometric methods are used in many Domains and for many purposes. Biometric authentication serves an individual to prove his or her authenticity. Biometric characteristics are uniquely associated with each user and thus represent the strongest form of personally identifiable information. Obviously this strengthens the authentication process; on the other hand the possibility that a biometric template could be stolen or exchanged raises concerns on its possible uses and abuses. It may be likely to get information about the enrolled person from their biometric template. It’s also achievable to compromise any traditional biometricsystems in order to gain access without presenting a biometric sample. In the same way, the efficacy of access control mechanisms is inherently limited, e.g. against internal attacks or in the presence of software vulnerabilities. In conventional cryptography, user authentication is based on possession of secret keys (such as a token or possession of smart card or remembering a password); such keys can be forgotten, lost, stolen, or may be illegally shared. So the biometrics and the conventional cryptography have their own potential vulnerabilities, but the
In summary, we have demonstrated that the use of transformation functions usually pro- vides similar or better performance than unprotected biometric data, except in BioHashing function. In addition, the use of multiple protected templates processed by ensemble system outperformed the previous results in single classiﬁers and ensemble systems. Moreover, we showed that biometricsystems with cancelable templates preserves the user privacy, i.e, it provides lower False Acceptance and False Rejection Errors in Unknown Key attacks and similar performance to unprotected biometric samples in Known Key Attacks. Based on key length experiments, we observe a perceptible continuous improvement when the key increases in Interpolation and BioHashing method in both key knowledge attacks. In contrast, Double Sum has minor improvements but the importance is that the performance does not decrease when user key increases. In conclusion, based on our ﬁndings, we propose the use of a single user key generated by system to authenticate users in mobile devices using multiple cancelable biometric templates.
Biometrics is an emerging technology  that is used to identify people by their physical and/or behavioral characteristics and, so, inherently requires that the person to be identified is physically present at the point of identification. The physical characteristics of an individual that can be used in biometric identification/verification systems are fingerprint, hand geometry, palm print , face , iris, retina, and ear; the behavioral characteristics are signature, lip movement, speech, keystroke dynamics, gesture, and gait . Biometricsystems based on a single biometric characteristic are referred to as unimodal systems. They are usually more cost- efficient than multimodal biometricsystems. However, a single physical or behavioral characteristic of an individual can sometimes fail to be sufficient for identification. For this reason, multimodal biometricsystems that integrate two or more different biometric characteristics are being developed to provide an acceptable performance, to increase the reliability of decisions, and to increase robustness to fraudulent technologies . Hong et al.  developed a prototype multimodal biometric system, which integrates faces and fingerprints at the identification stage. Ribaric and Fratric  presented a multimodal biometric system based on features extracted from fingerprint and palmprint data.
Classification in multimodal-biometricsystems is done by fusing information from different biometric modalities. Information fusion can be done at different levels, broadly divided into feature-level, score-level  and rank/decision-level fusion. Due to preservation of raw information, feature-level fusion can be more discriminative than score or decision- level fusion. But, feature-level fusion methods are being explored in the biometric community only recently. This is because of the differences in features extracted from different sensors in terms of type and dimensions. Often features have large dimensions, and fusion becomes difficult at the feature level. The prevalent method is feature concatenation, which has been used for different multi-biometric settings. However, for high dimensional feature vectors, simple feature concatenation may be inefficient and non-robust. In recent years, a theory of Sparse Representation (SR) has emerged as powerful tools for efficient processing of data in non-traditional ways . The proposed methodology uses sparse representation for the fusion of extracted biometric features .
Abstract —In this paper, the authors present a hybrid multi- biometric authentication person system that integrates both multi modal and multi algorithmic. Multi-modal, the system using face and fingerprint features, has long been considered common in personal authentication. Multi-algorithm is the system which uses Circularly Orthogonal Moments, such as Zernike Moment (ZM), Pseudo Zernike Moment (PZM), Polar Cosine Transform (PCT) and Radial Basis Function (RBF) Neural Networks. These moments are widely used because their magnitudes are invariant to image rotation, scaling and noise. With such incorporation of multi-modal and multi- algorithms, our proposed system is expected to minimize the possibility of forge in authentication better than uni-biometricsystems. In reference to this expectation, the experimental results have demonstrated that our method can assure a higher level of forge resistance than that of the systems using single biometric traits.
The idea behind biometricsystems is to recognize individuals, using pattern recognition algorithms on one or more biometric traits, being the latter called multimodal biometrics. Such systems can operate in verification or identification modes. In verification mode, the person presents the biometric to a sensor and claims an identity (via, e.g., a password); a one-to-one comparison with the stored template is performed to decide if the person is who she claims to be. In identification mode, the biometric presented to the sensor is tested by comparing the acquired template with all registered templates and the person is authenticated if a match is found.
Traditional Password and advanced biometricsystems are in authentication and identification systems. Biometrics is the science and technology which is measuring and analyzing biological data. According to information technology, biometrics is referred as technologies which measure and analyze characteristics of human (both physical and behavioral characteristics), such as fingerprints, iris, face, voice, traits and signatures. They are used for the authentication and identification purposes  . Authentication and identification through biometric confirmation are becoming famous and increasingly common in corporate and public security systems. But the security of the stored biometric data is theft. To prevent the identity theft, biometric data is generally encrypted when it is gathered and stored. Now-a-days, the cancelable biometric template or key generation techniques are emerging to meet these security issues and identity thefts. Biometric based applications guarantee numerous security risks . The brute-force attacks both the biometric based and password based systems .
As technology and services have developed in the mod- ern world, for human transactions, faster, reliable and more secured personal identification is required. Secure applica- tions requiring biometric authentication over distributed open networks are desired to be able to withstand attacks at two different levels, communication level attacks and database level attacks. The security framework design of biometricsystems should be able to address system level vulnerability issues and serves as the motivation for this work , .
Iris recognition is one of the biometricsystems which utilize iris texture patterns as a method of gathering unique information about an individual. It is considered to be one of the most reliable biometrics with some of the lowest false rejection and false acceptance rates and so it is less intrusive. Among the present biometric traits, iris is found to be the most reliable and accurate due to the rich iris texture patterns, persistence of features through the life time of an individual and it is neither duplicable nor imitable. The database used is CASIA. These characteristics make it more attractive for used as a biometric feature to identify individuals. The basic steps involved in iris recognition are as follows:
The Fig. 1 lists the current deployed biometric techniques in the computer security market. Although, biometrics authentication systems have overcome other traditional authentication schemes such as password or (pass codes) and PIN (Personal Identification Number). Till yet, there is no 100 percent guarantee about achieving highest level of performance regarding identification/verification of a person identity . The purpose of this study is to provide a brief review of existing physiological biometric authentication techniques along with highlighting some of their advantages and drawbacks/obstacles. In addition, a recent literature of current developments of the reviewed authentication systems is provided in this paper. This paper has an extension of the work in  by including the future improvement of discussed security authentication systems. The general organization of this paper is described as follows: Section 1 is the general introduction about biometrics technology. Section 2 provides a brief historical overview of biometric authentication techniques. In Section 3, the essential mechanism of biometric security systems is introduced. Section 4 discusses the most common physiological biometricsystems with more details for each method. At the end, Section 5 concludes the work of this paper and provides a future work.
A retrospective cross-sectional study was conducted between August 2006 and May 2013, including singleton pregnancies between 18 and 38 weeks’ gestation. The Internal Review Board of the Referral Center for Teaching of Diagnostic Imaging approved this study, and all fetal biometric parameters were obtained from our database without any patient identification. Each patient was included only once. All pregnant women who were scanned in our center were referred by the public health system of the metropolitan region of São Paulo. Inclusion criteria were singleton ges- tations with gestational age determined by the last men- strual period in patients with regular menstrual cycles and confirmed by sonographic examinations performed up to 13 weeks 6 days of pregnancy using the crown-rump length parameter, absence of maternal diseases, and absence of fetal malformations on sonography. When a difference of greater than 4 days between the gestational ages determined by the last menstrual period and sonography occurred, we used the gestational age determined by sonography.
Existing PKI deployments have limited customers. The use of PKI in ID card schemes for example, would enjoy larger customer base. It is our belief that such systems have the potential to raise the awareness of both governments and citizens trust levels in electronic transactions with such advanced technologies. These technologies are thought to pave the way for government transformation from service delivery perspectives and introduce new communication and service delivery channels that should replace government traditional physical counter interactions. Successful PKI implementation cases would put higher pressures on both government officials and private sector to develop killer applications to revolutinsie public service sectors. In brief, this article does not intend to explain detailed implementation questions, although it can serve as a primer for government officials and researchers who are interested in PKI implementations in government sectors.
Sufficient amount of dust pollution formed a layer on leaves than reduced light capturing ability of leaves which resulted in the declining of photosynthesis and ultimately plant growth (Farmer, 1993). Similar results were pragmatic in this study that dust had significant impact on leaf area of F. carica and non significant effect on P. guajava because there was +ive correlation between dust load and leaf area of F. carica while, negative correlation between dust accumulation Table 1: Correlation of dust accumulation with biometric and biochemical attributes of F.
Voiceprint Recognition System also known as a Speaker Recognition System (SRS) is the best-known commercialized forms of voice Biometrics. Automated speaker recognition is the computing task of validating a user's claimed identity using characteristics extracted from their voices. In contrast to other biometric technologies which are mostly image based and require expensive proprietary hardware such as vendor’s fingerprint sensor or iris- scanning equipment, the speaker recognition systems are designed for use with virtually any standard telephone or on public telephone networks. The ability to work with standard telephone equipment makes it possible to support broad-based deployments of voice biometrics applications in a variety of settings. In automated speaker recognition the speech signal is processed to extract speaker-specific information. These speaker specific informations are used to generate voiceprint which cannot be replicated by any source except the original speaker. This makes speaker recognition a secure method for authenticating an individual since unlike passwords or tokens; it cannot be stolen, duplicated or forgotten.
The results of the statistical analysis of the biometric data of Sciades herzbergii are presented in Table 1. The mean total and fork length of the fish caught at the potentially contaminated site were smaller than those from the reference site. The total body and gonad weight were not significantly different between the two sites. However, the gonadosomatic index showed significant differences (p<0.05) between the two fish groups (Table 2).
The analyzed values of facial and dental parameters in our population are moving in the biometric standards con- tained in the relevant literature. The determined differences arise from ethnic and morphological characteristics. A mod- erate correlation between the interalar width and anterior teeth width and canine cusps width was established. A low correlation between the inner canthal distance and width of anterior teeth and canine cusps width was established. By testing the statistical significance between genders signifi- cant differences for all the parameters was found. The meas- ured facial distances and anterior teeth width had higher val- ues for men than for women.
Reading “Constraints to applying systems thinking concepts in health systems”, we are struck by the idea that using an ST approach to promoting the use of ST by key health system stakeholders might be the best way to proceed. There can be little doubt that achieving this objective – having ST endorsed and applied more often by health system policy- makers and administrators – involves complexity. And a significant risk to any effort at dealing with complexity is to become overwhelmed by the myriad possibilities for action, and paralyzed by questions of where to start and what to do in order to “solve” the issue (2). This is a common response to complexity and the conundrum faced by anyone looking to develop an ST-informed action plan – but to give up in the face of this challenge would be unfortunate given the opportunity at hand.
In the cluster analysis for tenera‑type E. guineensis, PCA revealed a proportion of total variability by the first two components of 76.6%. The first component shows a direct correlation among seed weight, kernel diameters (transverse and longitudinal), and seed diameters (transverse and longitudinal); these variables are indirectly related to embryo size (Table 4). In terms of accessions, this contrast differentiates groups A and B (Figure 1). The second component shows a direct relationship between the number of loci and the number of kernels, which are indirectly related to kernel weight and embryo size. Group B stands out regarding this component, having the highest values for seed weight (Table 4). Therefore, the division into groups follows biometric as well as origin‑related parameters. Group A had seeds with a more rounded shape and with very thin endocarps, which could be easily broken when squeezed between the fingers. Group B had heavier seeds with a slightly elongated shape, characterized by the presence of equally elongated kernels; whereas group C had heavier seeds, probably resulting from endocarps thicker than those found in groups A and B.
Introduction: The object of this study was to assess the tridimensional cerebellar volume between genders and its correlation to other fetal growth parameters indices. Methods: The author carried out a cross-sectional and prospective study involving 125 normal pregnant women from 22 to 36 weeks of gestation. The assessment of fetal cerebellar volume was performed through Virtual Organ Computer-aided Analysis. The author also assessed other biometric fetal growth indices: biparietal diameter, occipitofrontal diameter, abdominal circumference, head circumference, femur length, anteroposterior cisterna magna diameter, lateral ventricle atria width and estimated fetal weight and its correla- tion to cerebellar volume. The Mancova analysis and Pearson’s correlation coefficient were used with gestational age as independent variable and cerebellar volume as dependent variable. Results: The results showed highly correlating to gestational age, biparietal diameter, occipito- frontal diameter, head circumference, femur length and estimated fetal weight (r-value above 0.90 and p<0.0001). Comparison between gen- ders did not show any significant difference in fetal cerebellar volume throughout pregnancy. Conclusions: The assessment of tridimensional cerebellar volume showed no difference between genders, but there was increasing throughout the pregnancy (p<0.0001).