Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 87

Search results for: biometric ATMs

87 ATM Location Problem and Cash Management in ATM's

Authors: M. Erol Genevois, D. Celik, H. Z. Ulukan

Abstract:

Automated teller machines (ATMs) can be considered among one of the most important service facilities in the banking industry. The investment in ATMs and the impact on the banking industry is growing steadily in every part of the world. The banks take into consideration many factors like safety, convenience, visibility, cost in order to determine the optimum locations of ATMs. Today, ATMs are not only available in bank branches but also at retail locations. Another important factor is the cash management in ATMs. A cash demand model for every ATM is needed in order to have an efficient cash management system. This forecasting model is based on historical cash demand data which is highly related to the ATMs location. So, the location and the cash management problem should be considered together. Although the literature survey on facility location models is quite large, it is surprising that there are only few studies which handle together ATMs location and cash management problem. In order to fulfill the gap, this paper provides a general review on studies, efforts and development in ATMs location and cash management problem.

Keywords: ATM location problem, cash management problem, ATM cash replenishment problem, literature review in ATMs

Procedia PDF Downloads 388
86 An Evaluation of the Impact of E-Banking on Operational Efficiency of Banks in Nigeria

Authors: Ibrahim Rabiu Darazo

Abstract:

The research has been conducted on the impact of E-banking on the operational efficiency of Banks in Nigeria, A case of some selected banks (Diamond Bank Plc, GTBankPlc, and Fidelity Bank Plc) in Nigeria. The research is a quantitative research which uses both primary and secondary sources of data collection. Questionnaire were used to obtained accurate data, where 150 Questionnaire were distributed among staff and customers of the three Banks , and the data collected where analysed using chi-square, whereas the secondary data where obtained from relevant text books, journals and relevant web sites. It is clear from the findings that, the use of e-banking by the banks has improved the efficiency of these banks, in terms of providing efficient services to customers electronically, using Internet Banking, Telephone Banking ATMs, reducing time taking to serve customers, e-banking allow new customers to open an account online, customers have access to their account at all the time 24/7.E-banking provide access to customers information from the data base and cost of check and postage were eliminated using e-banking. The recommendation at the end of the research include; the Banks should try to update their electronic gadgets, e-fraud(internal & external) should also be controlled, Banks shall employ qualified man power, Biometric ATMs shall be introduce to reduce fraud using ATM Cards, as it is use in other countries like USA.

Keywords: banks, electronic banking, operational efficiency of banks, biometric ATMs

Procedia PDF Downloads 226
85 A Biometric Template Security Approach to Fingerprints Based on Polynomial Transformations

Authors: Ramon Santana

Abstract:

The use of biometric identifiers in the field of information security, access control to resources, authentication in ATMs and banking among others, are of great concern because of the safety of biometric data. In the general architecture of a biometric system have been detected eight vulnerabilities, six of them allow obtaining minutiae template in plain text. The main consequence of obtaining minutia templates is the loss of biometric identifier for life. To mitigate these vulnerabilities several models to protect minutiae templates have been proposed. Several vulnerabilities in the cryptographic security of these models allow to obtain biometric data in plain text. In order to increase the cryptographic security and ease of reversibility, a minutiae templates protection model is proposed. The model aims to make the cryptographic protection and facilitate the reversibility of data using two levels of security. The first level of security is the data transformation level. In this level generates invariant data to rotation and translation, further transformation is irreversible. The second level of security is the evaluation level, where the encryption key is generated and data is evaluated using a defined evaluation function. The model is aimed at mitigating known vulnerabilities of the proposed models, basing its security on the impossibility of the polynomial reconstruction.

Keywords: fingerprint, template protection, bio-cryptography, minutiae protection

Procedia PDF Downloads 84
84 New Approach for Constructing a Secure Biometric Database

Authors: A. Kebbeb, M. Mostefai, F. Benmerzoug, Y. Chahir

Abstract:

The multimodal biometric identification is the combination of several biometric systems. The challenge of this combination is to reduce some limitations of systems based on a single modality while significantly improving performance. In this paper, we propose a new approach to the construction and the protection of a multimodal biometric database dedicated to an identification system. We use a topological watermarking to hide the relation between face image and the registered descriptors extracted from other modalities of the same person for more secure user identification.

Keywords: biometric databases, multimodal biometrics, security authentication, digital watermarking

Procedia PDF Downloads 273
83 A New Approach to Predicting Physical Biometrics from Behavioural Biometrics

Authors: Raid R. O. Al-Nima, S. S. Dlay, W. L. Woo

Abstract:

A relationship between face and signature biometrics is established in this paper. A new approach is developed to predict faces from signatures by using artificial intelligence. A multilayer perceptron (MLP) neural network is used to generate face details from features extracted from signatures, here face is the physical biometric and signatures is the behavioural biometric. The new method establishes a relationship between the two biometrics and regenerates a visible face image from the signature features. Furthermore, the performance efficiencies of our new technique are demonstrated in terms of minimum error rates compared to published work.

Keywords: behavioural biometric, face biometric, neural network, physical biometric, signature biometric

Procedia PDF Downloads 374
82 Biometric Recognition Techniques: A Survey

Authors: Shabir Ahmad Sofi, Shubham Aggarwal, Sanyam Singhal, Roohie Naaz

Abstract:

Biometric recognition refers to an automatic recognition of individuals based on a feature vector(s) derived from their physiological and/or behavioral characteristic. Biometric recognition systems should provide a reliable personal recognition schemes to either confirm or determine the identity of an individual. These features are used to provide an authentication for computer based security systems. Applications of such a system include computer systems security, secure electronic banking, mobile phones, credit cards, secure access to buildings, health and social services. By using biometrics a person could be identified based on 'who she/he is' rather than 'what she/he has' (card, token, key) or 'what she/he knows' (password, PIN). In this paper, a brief overview of biometric methods, both unimodal and multimodal and their advantages and disadvantages, will be presented.

Keywords: biometric, DNA, fingerprint, ear, face, retina scan, gait, iris, voice recognition, unimodal biometric, multimodal biometric

Procedia PDF Downloads 558
81 To Study the New Invocation of Biometric Authentication Technique

Authors: Aparna Gulhane

Abstract:

Biometrics is the science and technology of measuring and analyzing biological data form the basis of research in biological measuring techniques for the purpose of people identification and recognition. In information technology, biometrics refers to technologies that measure and analyze human body characteristics, such as DNA, fingerprints, eye retinas and irises, voice patterns, facial patterns and hand measurements. Biometric systems are used to authenticate the person's identity. The idea is to use the special characteristics of a person to identify him. These papers present a biometric authentication techniques and actual deployment of potential by overall invocation of biometrics recognition, with an independent testing of various biometric authentication products and technology.

Keywords: types of biometrics, importance of biometric, review for biometrics and getting a new implementation, biometric authentication technique

Procedia PDF Downloads 228
80 Biosignal Recognition for Personal Identification

Authors: Hadri Hussain, M.Nasir Ibrahim, Chee-Ming Ting, Mariani Idroas, Fuad Numan, Alias Mohd Noor

Abstract:

A biometric security system has become an important application in client identification and verification system. A conventional biometric system is normally based on unimodal biometric that depends on either behavioural or physiological information for authentication purposes. The behavioural biometric depends on human body biometric signal (such as speech) and biosignal biometric (such as electrocardiogram (ECG) and phonocardiogram or heart sound (HS)). The speech signal is commonly used in a recognition system in biometric, while the ECG and the HS have been used to identify a person’s diseases uniquely related to its cluster. However, the conventional biometric system is liable to spoof attack that will affect the performance of the system. Therefore, a multimodal biometric security system is developed, which is based on biometric signal of ECG, HS, and speech. The biosignal data involved in the biometric system is initially segmented, with each segment Mel Frequency Cepstral Coefficients (MFCC) method is exploited for extracting the feature. The Hidden Markov Model (HMM) is used to model the client and to classify the unknown input with respect to the modal. The recognition system involved training and testing session that is known as client identification (CID). In this project, twenty clients are tested with the developed system. The best overall performance at 44 kHz was 93.92% for ECG and the worst overall performance was ECG at 88.47%. The results were compared to the best overall performance at 44 kHz for (20clients) to increment of clients, which was 90.00% for HS and the worst overall performance falls at ECG at 79.91%. It can be concluded that the difference multimodal biometric has a substantial effect on performance of the biometric system and with the increment of data, even with higher frequency sampling, the performance still decreased slightly as predicted.

Keywords: electrocardiogram, phonocardiogram, hidden markov model, mel frequency cepstral coeffiecients, client identification

Procedia PDF Downloads 205
79 Gait Biometric for Person Re-Identification

Authors: Lavanya Srinivasan

Abstract:

Biometric identification is to identify unique features in a person like fingerprints, iris, ear, and voice recognition that need the subject's permission and physical contact. Gait biometric is used to identify the unique gait of the person by extracting moving features. The main advantage of gait biometric to identify the gait of a person at a distance, without any physical contact. In this work, the gait biometric is used for person re-identification. The person walking naturally compared with the same person walking with bag, coat, and case recorded using longwave infrared, short wave infrared, medium wave infrared, and visible cameras. The videos are recorded in rural and in urban environments. The pre-processing technique includes human identified using YOLO, background subtraction, silhouettes extraction, and synthesis Gait Entropy Image by averaging the silhouettes. The moving features are extracted from the Gait Entropy Energy Image. The extracted features are dimensionality reduced by the principal component analysis and recognised using different classifiers. The comparative results with the different classifier show that linear discriminant analysis outperforms other classifiers with 95.8% for visible in the rural dataset and 94.8% for longwave infrared in the urban dataset.

Keywords: biometric, gait, silhouettes, YOLO

Procedia PDF Downloads 73
78 Developing a Secure Iris Recognition System by Using Advance Convolutional Neural Network

Authors: Kamyar Fakhr, Roozbeh Salmani

Abstract:

Alphonse Bertillon developed the first biometric security system in the 1800s. Today, many governments and giant companies are considering or have procured biometrically enabled security schemes. Iris is a kaleidoscope of patterns and colors. Each individual holds a set of irises more unique than their thumbprint. Every single day, giant companies like Google and Apple are experimenting with reliable biometric systems. Now, after almost 200 years of improvements, face ID does not work with masks, it gives access to fake 3D images, and there is no global usage of biometric recognition systems as national identity (ID) card. The goal of this paper is to demonstrate the advantages of iris recognition overall biometric recognition systems. It make two extensions: first, we illustrate how a very large amount of internet fraud and cyber abuse is happening due to bugs in face recognition systems and in a very large dataset of 3.4M people; second, we discuss how establishing a secure global network of iris recognition devices connected to authoritative convolutional neural networks could be the safest solution to this dilemma. Another aim of this study is to provide a system that will prevent system infiltration caused by cyber-attacks and will block all wireframes to the data until the main user ceases the procedure.

Keywords: biometric system, convolutional neural network, cyber-attack, secure

Procedia PDF Downloads 119
77 Preprocessing and Fusion of Multiple Representation of Finger Vein patterns using Conventional and Machine Learning techniques

Authors: Tomas Trainys, Algimantas Venckauskas

Abstract:

Application of biometric features to the cryptography for human identification and authentication is widely studied and promising area of the development of high-reliability cryptosystems. Biometric cryptosystems typically are designed for patterns recognition, which allows biometric data acquisition from an individual, extracts feature sets, compares the feature set against the set stored in the vault and gives a result of the comparison. Preprocessing and fusion of biometric data are the most important phases in generating a feature vector for key generation or authentication. Fusion of biometric features is critical for achieving a higher level of security and prevents from possible spoofing attacks. The paper focuses on the tasks of initial processing and fusion of multiple representations of finger vein modality patterns. These tasks are solved by applying conventional image preprocessing methods and machine learning techniques, Convolutional Neural Network (SVM) method for image segmentation and feature extraction. An article presents a method for generating sets of biometric features from a finger vein network using several instances of the same modality. Extracted features sets were fused at the feature level. The proposed method was tested and compared with the performance and accuracy results of other authors.

Keywords: bio-cryptography, biometrics, cryptographic key generation, data fusion, information security, SVM, pattern recognition, finger vein method.

Procedia PDF Downloads 73
76 Facial Biometric Privacy Using Visual Cryptography: A Fundamental Approach to Enhance the Security of Facial Biometric Data

Authors: Devika Tanna

Abstract:

'Biometrics' means 'life measurement' but the term is usually associated with the use of unique physiological characteristics to identify an individual. It is important to secure the privacy of digital face image that is stored in central database. To impart privacy to such biometric face images, first, the digital face image is split into two host face images such that, each of it gives no idea of existence of the original face image and, then each cover image is stored in two different databases geographically apart. When both the cover images are simultaneously available then only we can access that original image. This can be achieved by using the XM2VTS and IMM face database, an adaptive algorithm for spatial greyscale. The algorithm helps to select the appropriate host images which are most likely to be compatible with the secret image stored in the central database based on its geometry and appearance. The encryption is done using GEVCS which results in a reconstructed image identical to the original private image.

Keywords: adaptive algorithm, database, host images, privacy, visual cryptography

Procedia PDF Downloads 59
75 Low-Cost Embedded Biometric System Based on Fingervein Modality

Authors: Randa Boukhris, Alima Damak, Dorra Sellami

Abstract:

Fingervein biometric authentication is one of the most popular and accurate technologies. However, low cost embedded solution is still an open problem. In this paper, a real-time implementation of fingervein recognition process embedded in Raspberry-Pi has been proposed. The use of Raspberry-Pi reduces overall system cost and size while allowing an easy user interface. Implementation of a target technology has guided to opt some specific parallel and simple processing algorithms. In the proposed system, we use four structural directional kernel elements for filtering finger vein images. Then, a Top-Hat and Bottom-Hat kernel filters are used to enhance the visibility and the appearance of venous images. For feature extraction step, a simple Local Directional Code (LDC) descriptor is applied. The proposed system presents an Error Equal Rate (EER) and Identification Rate (IR), respectively, equal to 0.02 and 98%. Furthermore, experimental results show that real-time operations have good performance.

Keywords: biometric, Bottom-Hat, Fingervein, LDC, Rasberry-Pi, ROI, Top-Hat

Procedia PDF Downloads 131
74 Implementation of a Multimodal Biometrics Recognition System with Combined Palm Print and Iris Features

Authors: Rabab M. Ramadan, Elaraby A. Elgallad

Abstract:

With extensive application, the performance of unimodal biometrics systems has to face a diversity of problems such as signal and background noise, distortion, and environment differences. Therefore, multimodal biometric systems are proposed to solve the above stated problems. This paper introduces a bimodal biometric recognition system based on the extracted features of the human palm print and iris. Palm print biometric is fairly a new evolving technology that is used to identify people by their palm features. The iris is a strong competitor together with face and fingerprints for presence in multimodal recognition systems. In this research, we introduced an algorithm to the combination of the palm and iris-extracted features using a texture-based descriptor, the Scale Invariant Feature Transform (SIFT). Since the feature sets are non-homogeneous as features of different biometric modalities are used, these features will be concatenated to form a single feature vector. Particle swarm optimization (PSO) is used as a feature selection technique to reduce the dimensionality of the feature. The proposed algorithm will be applied to the Institute of Technology of Delhi (IITD) database and its performance will be compared with various iris recognition algorithms found in the literature.

Keywords: iris recognition, particle swarm optimization, feature extraction, feature selection, palm print, the Scale Invariant Feature Transform (SIFT)

Procedia PDF Downloads 122
73 Development of a Secured Telemedical System Using Biometric Feature

Authors: O. Iyare, A. H. Afolayan, O. T. Oluwadare, B. K. Alese

Abstract:

Access to advanced medical services has been one of the medical challenges faced by our present society especially in distant geographical locations which may be inaccessible. Then the need for telemedicine arises through which live videos of a doctor can be streamed to a patient located anywhere in the world at any time. Patients’ medical records contain very sensitive information which should not be made accessible to unauthorized people in order to protect privacy, integrity and confidentiality. This research work focuses on a more robust security measure which is biometric (fingerprint) as a form of access control to data of patients by the medical specialist/practitioner.

Keywords: biometrics, telemedicine, privacy, patient information

Procedia PDF Downloads 210
72 Minimum Data of a Speech Signal as Special Indicators of Identification in Phonoscopy

Authors: Nazaket Gazieva

Abstract:

Voice biometric data associated with physiological, psychological and other factors are widely used in forensic phonoscopy. There are various methods for identifying and verifying a person by voice. This article explores the minimum speech signal data as individual parameters of a speech signal. Monozygotic twins are believed to be genetically identical. Using the minimum data of the speech signal, we came to the conclusion that the voice imprint of monozygotic twins is individual. According to the conclusion of the experiment, we can conclude that the minimum indicators of the speech signal are more stable and reliable for phonoscopic examinations.

Keywords: phonogram, speech signal, temporal characteristics, fundamental frequency, biometric fingerprints

Procedia PDF Downloads 61
71 Effect of Helium and Sulfur Hexafluoride Gas Inhalation on Voice Resonances

Authors: Pallavi Marathe

Abstract:

Voice is considered to be a unique biometric property of human beings. Unlike other biometric evidence, for example, fingerprints and retina scans, etc., voice can be easily changed or mimicked. The present paper talks about how the inhalation of helium and sulfur hexafluoride (SF6) gas affects the voice formant frequencies that are the resonant frequencies of the vocal tract. Helium gas is low-density gas; hence, the voice travels with a higher speed than that of air. On the other side in SF6 gas voice travels with lower speed than that of air due to its higher density. These results in decreasing the resonant frequencies of voice in helium and increasing in SF6. Results are presented with the help of Praat software, which is used for voice analysis.

Keywords: voice formants, helium, sulfur hexafluoride, gas inhalation

Procedia PDF Downloads 44
70 Application of Signature Verification Models for Document Recognition

Authors: Boris M. Fedorov, Liudmila P. Goncharenko, Sergey A. Sybachin, Natalia A. Mamedova, Ekaterina V. Makarenkova, Saule Rakhimova

Abstract:

In modern economic conditions, the question of the possibility of correct recognition of a signature on digital documents in order to verify the expression of will or confirm a certain operation is relevant. The additional complexity of processing lies in the dynamic variability of the signature for each individual, as well as in the way information is processed because the signature refers to biometric data. The article discusses the issues of using artificial intelligence models in order to improve the quality of signature confirmation in document recognition. The analysis of several possible options for using the model is carried out. The results of the study are given, in which it is possible to correctly determine the authenticity of the signature on small samples.

Keywords: signature recognition, biometric data, artificial intelligence, neural networks

Procedia PDF Downloads 56
69 Intelligent Recognition Tools for Industrial Automation

Authors: Amin Nazerzadeh, Afsaneh Nouri Houshyar , Azadeh Noori Hoshyar

Abstract:

With the rapid growing of information technology, the industry and manufacturing systems are becoming more automated. Therefore, achieving the highly accurate automatic systems with reliable security is becoming more critical. Biometrics that refers to identifying individual based on physiological or behavioral traits are unique identifiers provide high reliability and security in different industrial systems. As biometric cannot easily be transferred between individuals or copied, it has been receiving extensive attention. Due to the importance of security applications, this paper provides an overview on biometrics and discuss about background, types and applications of biometric as an effective tool for the industrial applications.

Keywords: Industial and manufacturing applications, intelligence and security, information technology, recognition; security technology; biometrics

Procedia PDF Downloads 65
68 A Machine Learning Framework Based on Biometric Measurements for Automatic Fetal Head Anomalies Diagnosis in Ultrasound Images

Authors: Hanene Sahli, Aymen Mouelhi, Marwa Hajji, Amine Ben Slama, Mounir Sayadi, Farhat Fnaiech, Radhwane Rachdi

Abstract:

Fetal abnormality is still a public health problem of interest to both mother and baby. Head defect is one of the most high-risk fetal deformities. Fetal head categorization is a sensitive task that needs a massive attention from neurological experts. In this sense, biometrical measurements can be extracted by gynecologist doctors and compared with ground truth charts to identify normal or abnormal growth. The fetal head biometric measurements such as Biparietal Diameter (BPD), Occipito-Frontal Diameter (OFD) and Head Circumference (HC) needs to be monitored, and expert should carry out its manual delineations. This work proposes a new approach to automatically compute BPD, OFD and HC based on morphological characteristics extracted from head shape. Hence, the studied data selected at the same Gestational Age (GA) from the fetal Ultrasound images (US) are classified into two categories: Normal and abnormal. The abnormal subjects include hydrocephalus, microcephaly and dolichocephaly anomalies. By the use of a support vector machines (SVM) method, this study achieved high classification for automated detection of anomalies. The proposed method is promising although it doesn't need expert interventions.

Keywords: biometric measurements, fetal head malformations, machine learning methods, US images

Procedia PDF Downloads 195
67 A User Identification Technique to Access Big Data Using Cloud Services

Authors: A. R. Manu, V. K. Agrawal, K. N. Balasubramanya Murthy

Abstract:

Authentication is required in stored database systems so that only authorized users can access the data and related cloud infrastructures. This paper proposes an authentication technique using multi-factor and multi-dimensional authentication system with multi-level security. The proposed technique is likely to be more robust as the probability of breaking the password is extremely low. This framework uses a multi-modal biometric approach and SMS to enforce additional security measures with the conventional Login/password system. The robustness of the technique is demonstrated mathematically using a statistical analysis. This work presents the authentication system along with the user authentication architecture diagram, activity diagrams, data flow diagrams, sequence diagrams, and algorithms.

Keywords: design, implementation algorithms, performance, biometric approach

Procedia PDF Downloads 387
66 Multi Biomertric Personal Identification System Based On Hybird Intellegence Method

Authors: Laheeb M. Ibrahim, Ibrahim A. Salih

Abstract:

Biometrics is a technology that has been widely used in many official and commercial identification applications. The increased concerns in security during recent years (especially during the last decades) have essentially resulted in more attention being given to biometric-based verification techniques. Here, a novel fusion approach of palmprint, dental traits has been suggested. These traits which are authentication techniques have been employed in a range of biometric applications that can identify any postmortem PM person and antemortem AM. Besides improving the accuracy, the fusion of biometrics has several advantages such as increasing, deterring spoofing activities and reducing enrolment failure. In this paper, a first unimodel biometric system has been made by using (palmprint and dental) traits, for each one classification applying an artificial neural network and a hybrid technique that combines swarm intelligence and neural network together, then attempt has been made to combine palmprint and dental biometrics. Principally, the fusion of palmprint and dental biometrics and their potential application has been explored as biometric identifiers. To address this issue, investigations have been carried out about the relative performance of several statistical data fusion techniques for integrating the information in both unimodal and multimodal biometrics. Also the results of the multimodal approach have been compared with each one of these two traits authentication approaches. This paper studies the features and decision fusion levels in multimodal biometrics. To determine the accuracy of GAR to parallel system decision-fusion including (AND, OR, Majority fating) has been used. The backpropagation method has been used for classification and has come out with result (92%, 99%, 97%) respectively for GAR, while the GAR) for this algorithm using hybrid technique for classification (95%, 99%, 98%) respectively. To determine the accuracy of the multibiometric system for feature level fusion has been used, while the same preceding methods have been used for classification. The results have been (98%, 99%) respectively while to determine the GAR of feature level different methods have been used and have come out with (98%).

Keywords: back propagation neural network BP ANN, multibiometric system, parallel system decision-fusion, practical swarm intelligent PSO

Procedia PDF Downloads 441
65 Identity Verification Using k-NN Classifiers and Autistic Genetic Data

Authors: Fuad M. Alkoot

Abstract:

DNA data have been used in forensics for decades. However, current research looks at using the DNA as a biometric identity verification modality. The goal is to improve the speed of identification. We aim at using gene data that was initially used for autism detection to find if and how accurate is this data for identification applications. Mainly our goal is to find if our data preprocessing technique yields data useful as a biometric identification tool. We experiment with using the nearest neighbor classifier to identify subjects. Results show that optimal classification rate is achieved when the test set is corrupted by normally distributed noise with zero mean and standard deviation of 1. The classification rate is close to optimal at higher noise standard deviation reaching 3. This shows that the data can be used for identity verification with high accuracy using a simple classifier such as the k-nearest neighbor (k-NN). 

Keywords: biometrics, genetic data, identity verification, k nearest neighbor

Procedia PDF Downloads 172
64 Heart-Rate Resistance Electrocardiogram Identification Based on Slope-Oriented Neural Networks

Authors: Tsu-Wang Shen, Shan-Chun Chang, Chih-Hsien Wang, Te-Chao Fang

Abstract:

For electrocardiogram (ECG) biometrics system, it is a tedious process to pre-install user’s high-intensity heart rate (HR) templates in ECG biometric systems. Based on only resting enrollment templates, it is a challenge to identify human by using ECG with the high-intensity HR caused from exercises and stress. This research provides a heartbeat segment method with slope-oriented neural networks against the ECG morphology changes due to high intensity HRs. The method has overall system accuracy at 97.73% which includes six levels of HR intensities. A cumulative match characteristic curve is also used to compare with other traditional ECG biometric methods.

Keywords: high-intensity heart rate, heart rate resistant, ECG human identification, decision based artificial neural network

Procedia PDF Downloads 306
63 Fusion of Finger Inner Knuckle Print and Hand Geometry Features to Enhance the Performance of Biometric Verification System

Authors: M. L. Anitha, K. A. Radhakrishna Rao

Abstract:

With the advent of modern computing technology, there is an increased demand for developing recognition systems that have the capability of verifying the identity of individuals. Recognition systems are required by several civilian and commercial applications for providing access to secured resources. Traditional recognition systems which are based on physical identities are not sufficiently reliable to satisfy the security requirements due to the use of several advances of forgery and identity impersonation methods. Recognizing individuals based on his/her unique physiological characteristics known as biometric traits is a reliable technique, since these traits are not transferable and they cannot be stolen or lost. Since the performance of biometric based recognition system depends on the particular trait that is utilized, the present work proposes a fusion approach which combines Inner knuckle print (IKP) trait of the middle, ring and index fingers with the geometrical features of hand. The hand image captured from a digital camera is preprocessed to find finger IKP as region of interest (ROI) and hand geometry features. Geometrical features are represented as the distances between different key points and IKP features are extracted by applying local binary pattern descriptor on the IKP ROI. The decision level AND fusion was adopted, which has shown improvement in performance of the combined scheme. The proposed approach is tested on the database collected at our institute. Proposed approach is of significance since both hand geometry and IKP features can be extracted from the palm region of the hand. The fusion of these features yields a false acceptance rate of 0.75%, false rejection rate of 0.86% for verification tests conducted, which is less when compared to the results obtained using individual traits. The results obtained confirm the usefulness of proposed approach and suitability of the selected features for developing biometric based recognition system based on features from palmar region of hand.

Keywords: biometrics, hand geometry features, inner knuckle print, recognition

Procedia PDF Downloads 135
62 Eye Tracking: Biometric Evaluations of Instructional Materials for Improved Learning

Authors: Janet Holland

Abstract:

Eye tracking is a great way to triangulate multiple data sources for deeper, more complete knowledge of how instructional materials are really being used and emotional connections made. Using sensor based biometrics provides a detailed local analysis in real time expanding our ability to collect science based data for a more comprehensive level of understanding, not previously possible, for teaching and learning. The knowledge gained will be used to make future improvements to instructional materials, tools, and interactions. The literature has been examined and a preliminary pilot test was implemented to develop a methodology for research in Instructional Design and Technology. Eye tracking now offers the addition of objective metrics obtained from eye tracking and other biometric data collection with analysis for a fresh perspective.

Keywords: area of interest, eye tracking, biometrics, fixation, fixation count, fixation sequence, fixation time, gaze points, heat map, saccades, time to first fixation

Procedia PDF Downloads 53
61 Usability and Biometric Authentication of Electronic Voting System

Authors: Nighat Ayub, Masood Ahmad

Abstract:

In this paper, a new voting system is developed and its usability is evaluated. The main feature of this system is the biometric verification of the voter and then a few easy steps to cast a vote. As compared to existing systems available, e.g dual vote, the new system requires no training in advance. The security is achieved via multiple key concept (another part of this project). More than 100 student voters were participated in the election from University of Malakanad, Chakdara, PK. To achieve the reliability, the voters cast their votes in two ways, i.e. paper based and electronic based voting using our new system. The results of paper based and electronic voting system are compared and it is concluded that the voters cast their votes for the intended candidates on the electronic voting system. The voters were requested to fill a questionnaire and the results of the questionnaire are carefully analyzed. The results show that the new system proposed in this paper is more secure and usable than other systems.

Keywords: e-voting, security, usability, authentication

Procedia PDF Downloads 274
60 A Multimodal Approach to Improve the Performance of Biometric System

Authors: Chander Kant, Arun Kumar

Abstract:

Biometric systems automatically recognize an individual based on his/her physiological and behavioral characteristics. There are also some traits like weight, age, height etc. that may not provide reliable user recognition because of there common and temporary nature. These traits are called soft bio metric traits. Although soft bio metric traits are lack of permanence to uniquely and reliably identify an individual, yet they provide some beneficial evidence about the user identity and may improve the system performance. Here in this paper, we have proposed an approach for integrating the soft bio metrics with fingerprint and face to improve the performance of personal authentication system. In our approach we have proposed a combined architecture of three different sensors to elevate the system performance. The approach includes, soft bio metrics, fingerprint and face traits. We have also proven the efficiency of proposed system regarding FAR (False Acceptance Ratio) and total response time, with the help of MUBI (Multimodal Bio metrics Integration) software.

Keywords: FAR, minutiae point, multimodal bio metrics, primary bio metric, soft bio metric

Procedia PDF Downloads 231
59 Multimodal Biometric Cryptography Based Authentication in Cloud Environment to Enhance Information Security

Authors: D. Pugazhenthi, B. Sree Vidya

Abstract:

Cloud computing is one of the emerging technologies that enables end users to use the services of cloud on ‘pay per usage’ strategy. This technology grows in a fast pace and so is its security threat. One among the various services provided by cloud is storage. In this service, security plays a vital factor for both authenticating legitimate users and protection of information. This paper brings in efficient ways of authenticating users as well as securing information on the cloud. Initial phase proposed in this paper deals with an authentication technique using multi-factor and multi-dimensional authentication system with multi-level security. Unique identification and slow intrusive formulates an advanced reliability on user-behaviour based biometrics than conventional means of password authentication. By biometric systems, the accounts are accessed only by a legitimate user and not by a nonentity. The biometric templates employed here do not include single trait but multiple, viz., iris and finger prints. The coordinating stage of the authentication system functions on Ensemble Support Vector Machine (SVM) and optimization by assembling weights of base SVMs for SVM ensemble after individual SVM of ensemble is trained by the Artificial Fish Swarm Algorithm (AFSA). Thus it helps in generating a user-specific secure cryptographic key of the multimodal biometric template by fusion process. Data security problem is averted and enhanced security architecture is proposed using encryption and decryption system with double key cryptography based on Fuzzy Neural Network (FNN) for data storing and retrieval in cloud computing . The proposing scheme aims to protect the records from hackers by arresting the breaking of cipher text to original text. This improves the authentication performance that the proposed double cryptographic key scheme is capable of providing better user authentication and better security which distinguish between the genuine and fake users. Thus, there are three important modules in this proposed work such as 1) Feature extraction, 2) Multimodal biometric template generation and 3) Cryptographic key generation. The extraction of the feature and texture properties from the respective fingerprint and iris images has been done initially. Finally, with the help of fuzzy neural network and symmetric cryptography algorithm, the technique of double key encryption technique has been developed. As the proposed approach is based on neural networks, it has the advantage of not being decrypted by the hacker even though the data were hacked already. The results prove that authentication process is optimal and stored information is secured.

Keywords: artificial fish swarm algorithm (AFSA), biometric authentication, decryption, encryption, fingerprint, fusion, fuzzy neural network (FNN), iris, multi-modal, support vector machine classification

Procedia PDF Downloads 156
58 A Neuron Model of Facial Recognition and Detection of an Authorized Entity Using Machine Learning System

Authors: J. K. Adedeji, M. O. Oyekanmi

Abstract:

This paper has critically examined the use of Machine Learning procedures in curbing unauthorized access into valuable areas of an organization. The use of passwords, pin codes, user’s identification in recent times has been partially successful in curbing crimes involving identities, hence the need for the design of a system which incorporates biometric characteristics such as DNA and pattern recognition of variations in facial expressions. The facial model used is the OpenCV library which is based on the use of certain physiological features, the Raspberry Pi 3 module is used to compile the OpenCV library, which extracts and stores the detected faces into the datasets directory through the use of camera. The model is trained with 50 epoch run in the database and recognized by the Local Binary Pattern Histogram (LBPH) recognizer contained in the OpenCV. The training algorithm used by the neural network is back propagation coded using python algorithmic language with 200 epoch runs to identify specific resemblance in the exclusive OR (XOR) output neurons. The research however confirmed that physiological parameters are better effective measures to curb crimes relating to identities.

Keywords: biometric characters, facial recognition, neural network, OpenCV

Procedia PDF Downloads 181