This document presents a bimodal biometric system that fuses fingerprint and iris features for identification. It extracts features from the iris using two-level discrete wavelet transformation and discrete cosine transformation. Fingerprint features are extracted using fast Fourier transformation and discrete wavelet transformation. The iris and fingerprint features are concatenated to form the final feature set. Experimental results on fingerprint and iris databases show that the proposed bimodal system has lower false rejection and false acceptance rates and higher total success rate compared to existing unimodal systems.
Multimodal Biometrics at Feature Level Fusion using Texture FeaturesCSCJournals
In recent years, fusion of multiple biometric modalities for personal authentication has received considerable attention. This paper presents a feature level fusion algorithm based on texture features. The system combines fingerprint, face and off-line signature. Texture features are extracted from Curvelet transform. The Curvelet feature dimension is selected based on d-prime number. The increase in feature dimension is reduced by using template averaging, moment features and by Principal component analysis (PCA). The algorithm is tested on in-house multimodal database comprising of 3000 samples and Chimeric databases. Identification performance of the system is evaluated using SVM classifier. A maximum GAR of 97.15% is achieved with Curvelet-PCA features.
A SURVEY ON MULTIMODAL BIOMETRIC AUTHENTICATION SYSTEM IN CLOUD COMPUTINGpharmaindexing
This document discusses a survey on multimodal biometric authentication systems in cloud computing. It begins with introducing the authors and purpose of studying multimodal biometrics. It then discusses how combining multiple biometric modalities can improve authentication by reducing errors. The document reviews different biometric traits like fingerprints, iris scans, and behavioral patterns. It also covers challenges of single biometric systems and how fusing modalities can help. The goal is to provide more secure authentication as a cloud service using multimodal biometrics.
Feature Level Fusion of Multibiometric Cryptosystem in Distributed SystemIJMER
ABSTRACT: Multibiometrics is the combination of one or more biometrics (e.g., Fingerprint, Iris, and Face). Researchers
are focusing on how to provide security to the system, the template which was generated from the biometric need to be
protected. The problems of unimodal biometrics are solved by multibiometrics. The main objective is to provide a security to
the biometric template by generating a secure sketch by making use of multibiometric cryptosystem and which is stored in a
database. Once the biometric template is stolen it becomes a serious issue for the security of the system and also for user
privacy. In the existing approach, feature level fusion is used to combine the features securely with well-known biometric
cryptosystems namely fuzzy vault and fuzzy commitment. The drawbacks of existing system include accuracy of the biometric
need to be improved and the noises in the biometrics also need to be reduced. The proposed work is to enhance the security
using multibiometric cryptosystem in distributed system applications like e-commerce transactions, e-banking and ATM.
Keywords: Biometric Cryptosystem, Error correcting code, Fingerprint, Iris, Multibiometrics, Unimodal biometrics.
IJERD (www.ijerd.com) International Journal of Engineering Research and Devel...IJERD Editor
The document describes a proposed algorithm called Fusion of Hybrid Domain features for Iris Recognition (FHDIR).
The algorithm pre-processes iris images by resizing, binarization, cropping and splitting them. It then applies Fast Fourier Transform (FFT) to the left half of the iris image to extract features and applies Principal Component Analysis (PCA) to the right half to extract features. These feature sets are then fused using arithmetic addition to generate a final feature vector. Test iris features are compared to the database using Euclidean Distance for identification.
The proposed algorithm is evaluated on the CASIA iris database and is found to have better performance than existing algorithms in terms of false rejection rate, false acceptance rate, and true
This document summarizes a research paper that proposes a feature level fusion based bimodal biometric authentication system using fingerprint and face recognition with transformation domain techniques. The system extracts fingerprint features using Dual Tree Complex Wavelet Transforms and extracts face features using Discrete Wavelet Transforms. It then concatenates the fingerprint and face features into a single feature vector. Euclidean distance is used to match test biometrics to those stored in a database. The proposed algorithm is shown to achieve better equal error rates and true positive identification rates compared to individual transformation domain techniques.
MULTIMODAL BIOMETRICS RECOGNITION FROM FACIAL VIDEO VIA DEEP LEARNINGsipij
Biometrics identification using multiple modalities has attracted the attention of many researchers as it
produces more robust and trustworthy results than single modality biometrics. In this paper, we present a
novel multimodal recognition system that trains a Deep Learning Network to automatically learn features
after extracting multiple biometric modalities from a single data source, i.e., facial video clips. Utilizing
different modalities, i.e., left ear, left profile face, frontal face, right profile face, and right ear, present in
the facial video clips, we train supervised denoising auto-encoders to automatically extract robust and nonredundant
features. The automatically learned features are then used to train modality specific sparse
classifiers to perform the multimodal recognition. Experiments conducted on the constrained facial video
dataset (WVU) and the unconstrained facial video dataset (HONDA/UCSD), resulted in a 99.17% and
97.14% rank-1 recognition rates, respectively. The multimodal recognition accuracy demonstrates the
superiority and robustness of the proposed approach irrespective of the illumination, non-planar
movement, and pose variations present in the video clips.
This document discusses a proposed approach to fuse iris and fingerprint images for multimodal biometrics identification and cryptographic key generation. It involves extracting features from the iris and fingerprint images, fusing the features to create a multimodal biometric template, and then generating a cryptographic key from the fused features for added security. The approach aims to improve accuracy over unimodal biometrics and protect the biometric template from being hacked by an intruder.
Multi biometric cryptosystems based on feature-level fusionParag Tamhane
The document proposes a methodology for multi-biometric cryptosystems that performs feature-level fusion. It involves three main modules: 1) An embedding algorithm that transforms biometric features into a new representation. 2) A fusion module that combines multiple biometric features into a single fused representation. 3) A biometric cryptosystem that generates a secure sketch from the fused features and verifies users during authentication. The methodology aims to provide higher security and matching performance compared to single biometric systems. A security analysis of each module and their impact on the overall system is also discussed.
Multimodal Biometrics at Feature Level Fusion using Texture FeaturesCSCJournals
In recent years, fusion of multiple biometric modalities for personal authentication has received considerable attention. This paper presents a feature level fusion algorithm based on texture features. The system combines fingerprint, face and off-line signature. Texture features are extracted from Curvelet transform. The Curvelet feature dimension is selected based on d-prime number. The increase in feature dimension is reduced by using template averaging, moment features and by Principal component analysis (PCA). The algorithm is tested on in-house multimodal database comprising of 3000 samples and Chimeric databases. Identification performance of the system is evaluated using SVM classifier. A maximum GAR of 97.15% is achieved with Curvelet-PCA features.
A SURVEY ON MULTIMODAL BIOMETRIC AUTHENTICATION SYSTEM IN CLOUD COMPUTINGpharmaindexing
This document discusses a survey on multimodal biometric authentication systems in cloud computing. It begins with introducing the authors and purpose of studying multimodal biometrics. It then discusses how combining multiple biometric modalities can improve authentication by reducing errors. The document reviews different biometric traits like fingerprints, iris scans, and behavioral patterns. It also covers challenges of single biometric systems and how fusing modalities can help. The goal is to provide more secure authentication as a cloud service using multimodal biometrics.
Feature Level Fusion of Multibiometric Cryptosystem in Distributed SystemIJMER
ABSTRACT: Multibiometrics is the combination of one or more biometrics (e.g., Fingerprint, Iris, and Face). Researchers
are focusing on how to provide security to the system, the template which was generated from the biometric need to be
protected. The problems of unimodal biometrics are solved by multibiometrics. The main objective is to provide a security to
the biometric template by generating a secure sketch by making use of multibiometric cryptosystem and which is stored in a
database. Once the biometric template is stolen it becomes a serious issue for the security of the system and also for user
privacy. In the existing approach, feature level fusion is used to combine the features securely with well-known biometric
cryptosystems namely fuzzy vault and fuzzy commitment. The drawbacks of existing system include accuracy of the biometric
need to be improved and the noises in the biometrics also need to be reduced. The proposed work is to enhance the security
using multibiometric cryptosystem in distributed system applications like e-commerce transactions, e-banking and ATM.
Keywords: Biometric Cryptosystem, Error correcting code, Fingerprint, Iris, Multibiometrics, Unimodal biometrics.
IJERD (www.ijerd.com) International Journal of Engineering Research and Devel...IJERD Editor
The document describes a proposed algorithm called Fusion of Hybrid Domain features for Iris Recognition (FHDIR).
The algorithm pre-processes iris images by resizing, binarization, cropping and splitting them. It then applies Fast Fourier Transform (FFT) to the left half of the iris image to extract features and applies Principal Component Analysis (PCA) to the right half to extract features. These feature sets are then fused using arithmetic addition to generate a final feature vector. Test iris features are compared to the database using Euclidean Distance for identification.
The proposed algorithm is evaluated on the CASIA iris database and is found to have better performance than existing algorithms in terms of false rejection rate, false acceptance rate, and true
This document summarizes a research paper that proposes a feature level fusion based bimodal biometric authentication system using fingerprint and face recognition with transformation domain techniques. The system extracts fingerprint features using Dual Tree Complex Wavelet Transforms and extracts face features using Discrete Wavelet Transforms. It then concatenates the fingerprint and face features into a single feature vector. Euclidean distance is used to match test biometrics to those stored in a database. The proposed algorithm is shown to achieve better equal error rates and true positive identification rates compared to individual transformation domain techniques.
MULTIMODAL BIOMETRICS RECOGNITION FROM FACIAL VIDEO VIA DEEP LEARNINGsipij
Biometrics identification using multiple modalities has attracted the attention of many researchers as it
produces more robust and trustworthy results than single modality biometrics. In this paper, we present a
novel multimodal recognition system that trains a Deep Learning Network to automatically learn features
after extracting multiple biometric modalities from a single data source, i.e., facial video clips. Utilizing
different modalities, i.e., left ear, left profile face, frontal face, right profile face, and right ear, present in
the facial video clips, we train supervised denoising auto-encoders to automatically extract robust and nonredundant
features. The automatically learned features are then used to train modality specific sparse
classifiers to perform the multimodal recognition. Experiments conducted on the constrained facial video
dataset (WVU) and the unconstrained facial video dataset (HONDA/UCSD), resulted in a 99.17% and
97.14% rank-1 recognition rates, respectively. The multimodal recognition accuracy demonstrates the
superiority and robustness of the proposed approach irrespective of the illumination, non-planar
movement, and pose variations present in the video clips.
This document discusses a proposed approach to fuse iris and fingerprint images for multimodal biometrics identification and cryptographic key generation. It involves extracting features from the iris and fingerprint images, fusing the features to create a multimodal biometric template, and then generating a cryptographic key from the fused features for added security. The approach aims to improve accuracy over unimodal biometrics and protect the biometric template from being hacked by an intruder.
Multi biometric cryptosystems based on feature-level fusionParag Tamhane
The document proposes a methodology for multi-biometric cryptosystems that performs feature-level fusion. It involves three main modules: 1) An embedding algorithm that transforms biometric features into a new representation. 2) A fusion module that combines multiple biometric features into a single fused representation. 3) A biometric cryptosystem that generates a secure sketch from the fused features and verifies users during authentication. The methodology aims to provide higher security and matching performance compared to single biometric systems. A security analysis of each module and their impact on the overall system is also discussed.
The Survey of Architecture of Multi-Modal (Fingerprint and Iris Recognition) ...IJERA Editor
Biometrics based individual identification is observed as an effective technique for automatically knowing, with a high confidence a person’s identity. Multi-modal biometric systems consolidate the evidence accessible by multiple biometric sources and normally better recognition performance associate to system based on a single biometric modality.Multi biometric systems are used to overcome this issue by providing multiple pieces of indication of the same identity. This system provides effective fusion structure that combines information provided by the multiple field experts based on decision-level and score-level fusion method, thereby increasing the efficiency which is not conceivable in uni-modal system.Multi-modal biometrics can be attained through a fusion of two or more images, where the subsequent fused image will be more protected. This paper discusses various fusion techniques, architecture of multi-modal biometric authentication and working of biometric fusion i.e. Iris and Fingerprint recognition that are used in multi-modal biometrics
2.human verification using multiple fingerprint texture 7 20Alexander Decker
This document presents a multimodal biometric verification system that uses multiple fingerprint matchers to improve accuracy. It combines two fingerprint matching techniques - Spatial Grey Level Dependence Method (SGLDM) and Filterbank-based matching. Matching scores from the two techniques are normalized and combined using sum rule fusion. The system was tested on a fingerprint database and experimental results showed the proposed fusion strategy reduces total error rate, improving overall system accuracy compared to single matcher systems.
11.0002www.iiste.org call for paper.human verification using multiple fingerp...Alexander Decker
This document presents a multimodal biometric verification system that uses multiple fingerprint matchers for human verification. It proposes combining two fingerprint matching techniques, the Spatial Grey Level Dependence Method (SGLDM) and a Filterbank-based technique, at the score level to generate a final matching score. The SGLDM extracts statistical texture features from fingerprints, while the Filterbank-based technique utilizes both global and local fingerprint features. The individual matching scores from each technique are normalized and combined using the sum rule. Experimental results on a fingerprint database demonstrate that the proposed fusion strategy improves overall accuracy by reducing total error rates compared to the individual matchers.
High Security Human Recognition System using Iris ImagesIDES Editor
In this paper, efficient biometric security
technique for Integer Wavelet Transform based Human
Recognition System (IWTHRS) using Iris images
verification is described. Human Recognition using Iris
images is one of the most secure and authentic among the
other biometrics. The Iris and Pupil boundaries of an Eye
are identified by Integro-Differential Operator. The features
of the normalized Iris are extracted using Integer Wavelet
Transform and Discrete Wavelet Transform. The Hamming
Distance is used for matching of two Iris feature vectors. It
is observed that the values of FAR, FRR, EER and
computation time required are improved in the case of
Integer Wavelet Transform based Human Recognition
System as compared to Discrete Wavelet Transform based
Human Recognition System (DWTHRS).
This document presents an overview of a student project on multimodal biometrics. It discusses combining fingerprint and iris recognition through feature-level fusion using a hybrid wavelet-based approach. The document outlines the presentation structure, importance and motivation of the project, related work in biometrics and multimodal biometrics, relevant theory, and applications of biometrics. It defines the problem of fusing fingerprint and iris modalities for improved identification performance.
Feature Extraction using Sparse SVD for Biometric Fusion in Multimodal Authen...IJNSA Journal
This document summarizes a research paper that proposes a novel multimodal biometric authentication system using face and fingerprint patterns. The system operates in three stages: 1) Fusion of face and fingerprint patterns using PCA to extract a joint feature vector, 2) Application of sparse SVD to the fusion data and face patterns separately to extract feature spaces, 3) Use of the Context-Sensitive Exponent Associative Memory Model (CSEAM) with exponential Kronecker product to encode the extracted feature vectors and allow for authentication/verification by comparing encoded vectors. The paper analyzes the performance of sparse SVD versus standard SVD for feature extraction and evaluates the proposed system in terms of mean square error rates.
Biometric Template Protection With Robust Semi – Blind Watermarking Using Ima...CSCJournals
This paper addresses a biometric watermarking technology sturdy towards image manipulations, like JPEG compression, image filtering, and additive noise. Application scenarios include information transmission between client and server, maintaining e-database and management of signatures through insecure distribution channels. Steps involved in this work are, a) generation of binary signature code for biometric, b) embedding of the binary signature to the host image using intrinsic local property, that ensures signature protection, c) host image is then made exposed to various attacks and d) signature is extracted and matched based on an empirical threshold to verify the robustness of proposed embedding method. Embedding relies on binary signature manipulating the lower order AC coefficients of Discrete Cosine Transformed sub-blocks of host image. In the prediction phase, DC values of the nearest neighbor DCT blocks is utilized to predict the AC coefficients of centre block. Surrounding DC values of a DCT blocks are adaptively weighed for AC coefficients prediction. Linear programming is used to calculate the weights with respect to the image content. Multiple times embedding of watermark ensures robustness against common signal processing operations (filtering, enhancement, rescaling etc.) and various attacks. The proposed algorithm is tested for 50 different types of host images and public data collection, DB3, FVC2002. FAR and FRR are compared with other methods to show the improvement.
MultiModal Identification System in Monozygotic TwinsCSCJournals
This document presents a multimodal biometric system for identifying identical twins using face, fingerprint, and iris recognition. It utilizes Fisher's linear discriminant analysis to extract features from faces, principal component analysis for fingerprints, and local binary pattern features for iris matching. These features are then fused for identification. The system is tested on a database of 50 pairs of identical twins and shows promising results compared to other techniques. Receiver operating characteristics also indicate the proposed method performs better than other studied techniques in distinguishing identical twins.
Robust Analysis of Multibiometric Fusion Versus Ensemble Learning Schemes: A ...CSCJournals
Identification of person using multiple biometric is very common approach used in existing user
validation of systems. Most of multibiometric system depends on fusion schemes, as much of the
fusion techniques have shown promising results in literature, due to the fact of combining multiple
biometric modalities with suitable fusion schemes. However, similar type of practices are found in
ensemble of classifiers, which increases the classification accuracy while combining different
types of classifiers. In this paper, we have evaluated comparative study of traditional fusion
methods like feature level and score level fusion with the well-known ensemble methods such as
bagging and boosting. Precisely, for our frame work experimentations, we have fused face and
palmprint modalities and we have employed probability model - Naive Bayes (NB), neural
network model - Multi Layer Perceptron (MLP), supervised machine learning algorithm - Support
Vector Machine (SVM) classifiers for our experimentation. Nevertheless, machine learning
ensemble approaches namely, Boosting and Bagging are statistically well recognized. From
experimental results, in biometric fusion the traditional method, score level fusion is highly
recommended strategy than ensemble learning techniques.
International Journal of Engineering Research and Applications (IJERA) aims to cover the latest outstanding developments in the field of all Engineering Technologies & science.
International Journal of Engineering Research and Applications (IJERA) is a team of researchers not publication services or private publications running the journals for monetary benefits, we are association of scientists and academia who focus only on supporting authors who want to publish their work. The articles published in our journal can be accessed online, all the articles will be archived for real time access.
Our journal system primarily aims to bring out the research talent and the works done by sciaentists, academia, engineers, practitioners, scholars, post graduate students of engineering and science. This journal aims to cover the scientific research in a broader sense and not publishing a niche area of research facilitating researchers from various verticals to publish their papers. It is also aimed to provide a platform for the researchers to publish in a shorter of time, enabling them to continue further All articles published are freely available to scientific researchers in the Government agencies,educators and the general public. We are taking serious efforts to promote our journal across the globe in various ways, we are sure that our journal will act as a scientific platform for all researchers to publish their works online.
This document describes an iris recognition system implemented using National Instruments LabVIEW for secure voting. The system has four main stages: 1) image acquisition using an infrared camera, 2) iris localization by detecting circles in the iris image, 3) pattern matching to extract an iris code, and 4) authentication by matching the iris code to a database. The database stores voter information and iris codes in an encrypted format. On voting day, the system matches the voter's ID and captured iris image to the database to verify their identity before allowing them to vote. The system aims to provide more secure identity verification than traditional password or ID systems.
Sum Rule Based Matching Score Level Fusion of Fingerprint and Iris Images for...IRJET Journal
This document summarizes a research paper on multimodal biometrics identification using fingerprint and iris images. It discusses how a multimodal biometric system that fuses fingerprint and iris traits can improve identification accuracy over unimodal systems. The document outlines the architecture of multimodal biometric systems, including how different biometrics are acquired, processed independently, and then fused using techniques like score-level fusion. It also discusses related work on fingerprint and iris recognition individually, as well as previous research on multimodal biometrics fusion.
The document discusses multispectral palm image fusion for biometric authentication using ant colony optimization. It introduces intra-modal fusion of palmprint images from multiple spectra to improve accuracy. The key steps involve detecting the region of interest, fusing the images using wavelet transforms, extracting Gabor features, selecting optimal features using ant colony optimization, and classifying with support vector machines. Experimental results and conclusions are also presented.
Scale Invariant Feature Transform Based Face Recognition from a Single Sample...ijceronline
International Journal of Computational Engineering Research (IJCER) is dedicated to protecting personal information and will make every reasonable effort to handle collected information appropriately. All information collected, as well as related requests, will be handled as carefully and efficiently as possible in accordance with IJCER standards for integrity and objectivity.
Highly Secured Bio-Metric Authentication Model with Palm Print IdentificationIJERA Editor
The document presents a highly secured palm print authentication system using undecimated bi-orthogonal wavelet (UDBW) transform. The proposed system has three main modules: registration, testing, and palm matching. In the registration module, morphological operations and region of interest extraction are used to preprocess palm images. Distance transform and 3-level UDBW transform are then used to extract low-level features and create feature vectors for registered palm prints. In testing, low-level features are extracted from input palm prints using the same approach. Palm matching involves comparing feature vectors of registered and input palm prints to identify matches. Simulation results show the system provides accurate recognition rates for palm print authentication.
This document presents a technique for hand geometry recognition using feature extraction. It involves extracting features from hand images such as finger lengths, widths, and perimeter. The method uses reference points on the hand like finger tips and endpoints to calculate these features using mathematical calculations. The extracted features are then used for hand recognition by matching with features stored in a database. Experiments were conducted on 50 users, with features extracted from 6 images of each user's left and right hands. The extracted features were matched with the database, showing the potential of hand geometry for biometric identification applications.
Integrating Fusion levels for Biometric Authentication SystemIOSRJECE
— Recently a lot of works are presented in the literature for the multimodal biometric authentication. And such biometric systems have been widely accepted with increasing accuracy rates and population coverage, reducing the vulnerability to spoofing. This paper descripts about the proposed multimodal biometric system that combines the feature extraction level and the score level fusion of iris and face unimodal biometric systems in order to take advantage of both fusion techniques. The experimental results shows the performance of the multimodal and multilevel fusion techniques which are analysed using TRR and TAR to study the recognition behaviour of the approach system. From the ROC Curve plotted, the performance of the proposed system is better compared to the individual fusion techniques.
Feature Level Fusion Based Bimodal Biometric Using Transformation Domine Tec...IOSR Journals
This document proposes a feature level fusion approach for bimodal biometrics using fingerprint and face recognition. It extracts features from fingerprint images using Dual Tree Complex Wavelet Transforms and from face images using Discrete Wavelet Transforms. The fingerprint features are the log of DTCWT coefficients and the face features are the DWT approximation coefficients. These features are concatenated to create a final feature vector for each sample. During matching, the Euclidean distance between a test sample's feature vector and those in the database are calculated to determine a match. The proposed approach fuses fingerprint and face modalities at the feature level to leverage the strengths of multiple biometrics for improved identification accuracy.
The document discusses securing biometric templates when transmitted over non-secure channels by selecting partial fingerprint and iris data, encrypting it using AES with an iris hash as the key, and transmitting the encrypted data. It outlines the need to protect biometric data due to risks of identity theft if templates are compromised. Various attacks on biometric systems and methods of template protection including cryptography and cancelable biometrics are also reviewed.
Feature Extraction using Sparse SVD for Biometric Fusion in Multimodal Authen...IJNSA Journal
Token based security (ID Cards) have been used to restrict access to the Secured systems. The purpose of
Biometrics is to identify / verify the correctness of an individual by using certain physiological or
behavioural traits associated with the person. Current biometric systems make use of face, fingerprints,
iris, hand geometry, retina, signature, palm print, voiceprint and so on to establish a person’s identity.
Biometrics is one of the primary key concepts of real application domains such as aadhar card, passport,
pan card, etc. In this paper, we consider face and fingerprint patterns for identification/verification. Using
this data we proposed a novel model for authentication in multimodal biometrics often called ContextSensitive Exponent Associative Memory Model (CSEAM). It provides different stages of security for
biometrics fusion patterns. In stage 1, fusion of face and finger patterns using Principal Component
Analysis (PCA), in stage 2 by applying Sparse SVD decomposition to extract the feature patterns from the
fusion data and face pattern and then in stage 3, using CSEAM model, the extracted feature vectors can be
encoded. The final key will be stored in the smart cards as Associative Memory (M), which is often called
Context-Sensitive Associative Memory (CSAM). In CSEAM model, the CSEAM will be computed using
exponential kronecker product for encoding and verification of the chosen samples from the users. The
exponential of matrix can be computed in various ways such as Taylor Series, Pade Approximation and
also using Ordinary Differential Equations (O.D.E.). Among these approaches we considered first two
methods for computing exponential of a feature space. The result analysis of SVD and Sparse SVD for
feature extraction process and also authentication/verification process of the proposed system in terms of
performance measures as Mean square error rates will be presented.
This document summarizes a research paper on improving the performance of multimodal biometrics using cryptosystems. The paper proposes fusing iris and fingerprint biometrics at the feature level before applying encryption for enhanced security. It discusses extracting features from iris and fingerprint images, fusing the features, and then encrypting the fused template. This approach aims to improve accuracy over unimodal biometrics while enhancing security through encryption. The paper reviews related work on multimodal biometrics and cryptosystems, and presents results showing the proposed approach effectively extracts features and fuses the biometrics for identification.
The Survey of Architecture of Multi-Modal (Fingerprint and Iris Recognition) ...IJERA Editor
Biometrics based individual identification is observed as an effective technique for automatically knowing, with a high confidence a person’s identity. Multi-modal biometric systems consolidate the evidence accessible by multiple biometric sources and normally better recognition performance associate to system based on a single biometric modality.Multi biometric systems are used to overcome this issue by providing multiple pieces of indication of the same identity. This system provides effective fusion structure that combines information provided by the multiple field experts based on decision-level and score-level fusion method, thereby increasing the efficiency which is not conceivable in uni-modal system.Multi-modal biometrics can be attained through a fusion of two or more images, where the subsequent fused image will be more protected. This paper discusses various fusion techniques, architecture of multi-modal biometric authentication and working of biometric fusion i.e. Iris and Fingerprint recognition that are used in multi-modal biometrics
2.human verification using multiple fingerprint texture 7 20Alexander Decker
This document presents a multimodal biometric verification system that uses multiple fingerprint matchers to improve accuracy. It combines two fingerprint matching techniques - Spatial Grey Level Dependence Method (SGLDM) and Filterbank-based matching. Matching scores from the two techniques are normalized and combined using sum rule fusion. The system was tested on a fingerprint database and experimental results showed the proposed fusion strategy reduces total error rate, improving overall system accuracy compared to single matcher systems.
11.0002www.iiste.org call for paper.human verification using multiple fingerp...Alexander Decker
This document presents a multimodal biometric verification system that uses multiple fingerprint matchers for human verification. It proposes combining two fingerprint matching techniques, the Spatial Grey Level Dependence Method (SGLDM) and a Filterbank-based technique, at the score level to generate a final matching score. The SGLDM extracts statistical texture features from fingerprints, while the Filterbank-based technique utilizes both global and local fingerprint features. The individual matching scores from each technique are normalized and combined using the sum rule. Experimental results on a fingerprint database demonstrate that the proposed fusion strategy improves overall accuracy by reducing total error rates compared to the individual matchers.
High Security Human Recognition System using Iris ImagesIDES Editor
In this paper, efficient biometric security
technique for Integer Wavelet Transform based Human
Recognition System (IWTHRS) using Iris images
verification is described. Human Recognition using Iris
images is one of the most secure and authentic among the
other biometrics. The Iris and Pupil boundaries of an Eye
are identified by Integro-Differential Operator. The features
of the normalized Iris are extracted using Integer Wavelet
Transform and Discrete Wavelet Transform. The Hamming
Distance is used for matching of two Iris feature vectors. It
is observed that the values of FAR, FRR, EER and
computation time required are improved in the case of
Integer Wavelet Transform based Human Recognition
System as compared to Discrete Wavelet Transform based
Human Recognition System (DWTHRS).
This document presents an overview of a student project on multimodal biometrics. It discusses combining fingerprint and iris recognition through feature-level fusion using a hybrid wavelet-based approach. The document outlines the presentation structure, importance and motivation of the project, related work in biometrics and multimodal biometrics, relevant theory, and applications of biometrics. It defines the problem of fusing fingerprint and iris modalities for improved identification performance.
Feature Extraction using Sparse SVD for Biometric Fusion in Multimodal Authen...IJNSA Journal
This document summarizes a research paper that proposes a novel multimodal biometric authentication system using face and fingerprint patterns. The system operates in three stages: 1) Fusion of face and fingerprint patterns using PCA to extract a joint feature vector, 2) Application of sparse SVD to the fusion data and face patterns separately to extract feature spaces, 3) Use of the Context-Sensitive Exponent Associative Memory Model (CSEAM) with exponential Kronecker product to encode the extracted feature vectors and allow for authentication/verification by comparing encoded vectors. The paper analyzes the performance of sparse SVD versus standard SVD for feature extraction and evaluates the proposed system in terms of mean square error rates.
Biometric Template Protection With Robust Semi – Blind Watermarking Using Ima...CSCJournals
This paper addresses a biometric watermarking technology sturdy towards image manipulations, like JPEG compression, image filtering, and additive noise. Application scenarios include information transmission between client and server, maintaining e-database and management of signatures through insecure distribution channels. Steps involved in this work are, a) generation of binary signature code for biometric, b) embedding of the binary signature to the host image using intrinsic local property, that ensures signature protection, c) host image is then made exposed to various attacks and d) signature is extracted and matched based on an empirical threshold to verify the robustness of proposed embedding method. Embedding relies on binary signature manipulating the lower order AC coefficients of Discrete Cosine Transformed sub-blocks of host image. In the prediction phase, DC values of the nearest neighbor DCT blocks is utilized to predict the AC coefficients of centre block. Surrounding DC values of a DCT blocks are adaptively weighed for AC coefficients prediction. Linear programming is used to calculate the weights with respect to the image content. Multiple times embedding of watermark ensures robustness against common signal processing operations (filtering, enhancement, rescaling etc.) and various attacks. The proposed algorithm is tested for 50 different types of host images and public data collection, DB3, FVC2002. FAR and FRR are compared with other methods to show the improvement.
MultiModal Identification System in Monozygotic TwinsCSCJournals
This document presents a multimodal biometric system for identifying identical twins using face, fingerprint, and iris recognition. It utilizes Fisher's linear discriminant analysis to extract features from faces, principal component analysis for fingerprints, and local binary pattern features for iris matching. These features are then fused for identification. The system is tested on a database of 50 pairs of identical twins and shows promising results compared to other techniques. Receiver operating characteristics also indicate the proposed method performs better than other studied techniques in distinguishing identical twins.
Robust Analysis of Multibiometric Fusion Versus Ensemble Learning Schemes: A ...CSCJournals
Identification of person using multiple biometric is very common approach used in existing user
validation of systems. Most of multibiometric system depends on fusion schemes, as much of the
fusion techniques have shown promising results in literature, due to the fact of combining multiple
biometric modalities with suitable fusion schemes. However, similar type of practices are found in
ensemble of classifiers, which increases the classification accuracy while combining different
types of classifiers. In this paper, we have evaluated comparative study of traditional fusion
methods like feature level and score level fusion with the well-known ensemble methods such as
bagging and boosting. Precisely, for our frame work experimentations, we have fused face and
palmprint modalities and we have employed probability model - Naive Bayes (NB), neural
network model - Multi Layer Perceptron (MLP), supervised machine learning algorithm - Support
Vector Machine (SVM) classifiers for our experimentation. Nevertheless, machine learning
ensemble approaches namely, Boosting and Bagging are statistically well recognized. From
experimental results, in biometric fusion the traditional method, score level fusion is highly
recommended strategy than ensemble learning techniques.
International Journal of Engineering Research and Applications (IJERA) aims to cover the latest outstanding developments in the field of all Engineering Technologies & science.
International Journal of Engineering Research and Applications (IJERA) is a team of researchers not publication services or private publications running the journals for monetary benefits, we are association of scientists and academia who focus only on supporting authors who want to publish their work. The articles published in our journal can be accessed online, all the articles will be archived for real time access.
Our journal system primarily aims to bring out the research talent and the works done by sciaentists, academia, engineers, practitioners, scholars, post graduate students of engineering and science. This journal aims to cover the scientific research in a broader sense and not publishing a niche area of research facilitating researchers from various verticals to publish their papers. It is also aimed to provide a platform for the researchers to publish in a shorter of time, enabling them to continue further All articles published are freely available to scientific researchers in the Government agencies,educators and the general public. We are taking serious efforts to promote our journal across the globe in various ways, we are sure that our journal will act as a scientific platform for all researchers to publish their works online.
This document describes an iris recognition system implemented using National Instruments LabVIEW for secure voting. The system has four main stages: 1) image acquisition using an infrared camera, 2) iris localization by detecting circles in the iris image, 3) pattern matching to extract an iris code, and 4) authentication by matching the iris code to a database. The database stores voter information and iris codes in an encrypted format. On voting day, the system matches the voter's ID and captured iris image to the database to verify their identity before allowing them to vote. The system aims to provide more secure identity verification than traditional password or ID systems.
Sum Rule Based Matching Score Level Fusion of Fingerprint and Iris Images for...IRJET Journal
This document summarizes a research paper on multimodal biometrics identification using fingerprint and iris images. It discusses how a multimodal biometric system that fuses fingerprint and iris traits can improve identification accuracy over unimodal systems. The document outlines the architecture of multimodal biometric systems, including how different biometrics are acquired, processed independently, and then fused using techniques like score-level fusion. It also discusses related work on fingerprint and iris recognition individually, as well as previous research on multimodal biometrics fusion.
The document discusses multispectral palm image fusion for biometric authentication using ant colony optimization. It introduces intra-modal fusion of palmprint images from multiple spectra to improve accuracy. The key steps involve detecting the region of interest, fusing the images using wavelet transforms, extracting Gabor features, selecting optimal features using ant colony optimization, and classifying with support vector machines. Experimental results and conclusions are also presented.
Scale Invariant Feature Transform Based Face Recognition from a Single Sample...ijceronline
International Journal of Computational Engineering Research (IJCER) is dedicated to protecting personal information and will make every reasonable effort to handle collected information appropriately. All information collected, as well as related requests, will be handled as carefully and efficiently as possible in accordance with IJCER standards for integrity and objectivity.
Highly Secured Bio-Metric Authentication Model with Palm Print IdentificationIJERA Editor
The document presents a highly secured palm print authentication system using undecimated bi-orthogonal wavelet (UDBW) transform. The proposed system has three main modules: registration, testing, and palm matching. In the registration module, morphological operations and region of interest extraction are used to preprocess palm images. Distance transform and 3-level UDBW transform are then used to extract low-level features and create feature vectors for registered palm prints. In testing, low-level features are extracted from input palm prints using the same approach. Palm matching involves comparing feature vectors of registered and input palm prints to identify matches. Simulation results show the system provides accurate recognition rates for palm print authentication.
This document presents a technique for hand geometry recognition using feature extraction. It involves extracting features from hand images such as finger lengths, widths, and perimeter. The method uses reference points on the hand like finger tips and endpoints to calculate these features using mathematical calculations. The extracted features are then used for hand recognition by matching with features stored in a database. Experiments were conducted on 50 users, with features extracted from 6 images of each user's left and right hands. The extracted features were matched with the database, showing the potential of hand geometry for biometric identification applications.
Integrating Fusion levels for Biometric Authentication SystemIOSRJECE
— Recently a lot of works are presented in the literature for the multimodal biometric authentication. And such biometric systems have been widely accepted with increasing accuracy rates and population coverage, reducing the vulnerability to spoofing. This paper descripts about the proposed multimodal biometric system that combines the feature extraction level and the score level fusion of iris and face unimodal biometric systems in order to take advantage of both fusion techniques. The experimental results shows the performance of the multimodal and multilevel fusion techniques which are analysed using TRR and TAR to study the recognition behaviour of the approach system. From the ROC Curve plotted, the performance of the proposed system is better compared to the individual fusion techniques.
Feature Level Fusion Based Bimodal Biometric Using Transformation Domine Tec...IOSR Journals
This document proposes a feature level fusion approach for bimodal biometrics using fingerprint and face recognition. It extracts features from fingerprint images using Dual Tree Complex Wavelet Transforms and from face images using Discrete Wavelet Transforms. The fingerprint features are the log of DTCWT coefficients and the face features are the DWT approximation coefficients. These features are concatenated to create a final feature vector for each sample. During matching, the Euclidean distance between a test sample's feature vector and those in the database are calculated to determine a match. The proposed approach fuses fingerprint and face modalities at the feature level to leverage the strengths of multiple biometrics for improved identification accuracy.
The document discusses securing biometric templates when transmitted over non-secure channels by selecting partial fingerprint and iris data, encrypting it using AES with an iris hash as the key, and transmitting the encrypted data. It outlines the need to protect biometric data due to risks of identity theft if templates are compromised. Various attacks on biometric systems and methods of template protection including cryptography and cancelable biometrics are also reviewed.
Feature Extraction using Sparse SVD for Biometric Fusion in Multimodal Authen...IJNSA Journal
Token based security (ID Cards) have been used to restrict access to the Secured systems. The purpose of
Biometrics is to identify / verify the correctness of an individual by using certain physiological or
behavioural traits associated with the person. Current biometric systems make use of face, fingerprints,
iris, hand geometry, retina, signature, palm print, voiceprint and so on to establish a person’s identity.
Biometrics is one of the primary key concepts of real application domains such as aadhar card, passport,
pan card, etc. In this paper, we consider face and fingerprint patterns for identification/verification. Using
this data we proposed a novel model for authentication in multimodal biometrics often called ContextSensitive Exponent Associative Memory Model (CSEAM). It provides different stages of security for
biometrics fusion patterns. In stage 1, fusion of face and finger patterns using Principal Component
Analysis (PCA), in stage 2 by applying Sparse SVD decomposition to extract the feature patterns from the
fusion data and face pattern and then in stage 3, using CSEAM model, the extracted feature vectors can be
encoded. The final key will be stored in the smart cards as Associative Memory (M), which is often called
Context-Sensitive Associative Memory (CSAM). In CSEAM model, the CSEAM will be computed using
exponential kronecker product for encoding and verification of the chosen samples from the users. The
exponential of matrix can be computed in various ways such as Taylor Series, Pade Approximation and
also using Ordinary Differential Equations (O.D.E.). Among these approaches we considered first two
methods for computing exponential of a feature space. The result analysis of SVD and Sparse SVD for
feature extraction process and also authentication/verification process of the proposed system in terms of
performance measures as Mean square error rates will be presented.
This document summarizes a research paper on improving the performance of multimodal biometrics using cryptosystems. The paper proposes fusing iris and fingerprint biometrics at the feature level before applying encryption for enhanced security. It discusses extracting features from iris and fingerprint images, fusing the features, and then encrypting the fused template. This approach aims to improve accuracy over unimodal biometrics while enhancing security through encryption. The paper reviews related work on multimodal biometrics and cryptosystems, and presents results showing the proposed approach effectively extracts features and fuses the biometrics for identification.
Performance Enhancement Of Multimodal Biometrics Using CryptosystemIJERA Editor
Multimodal biometrics means the unification of two or more uni modal biometrics so as to make the system more reliable and secure. Such systems promise better security. This study is a blend of iris and fingerprint recognition technique and their fusion at feature level. Our work comprises of two main sections: feature extraction of both modalities and fusing them before matching and finally application of an encryption technique to enhance the security of the fused template.
Biometric Authentication Based on Hash Iris FeaturesCSCJournals
With an increasing emphasis on security, automated personal identification based on biometrics has been receiving extensive attention since its introduction in 1992. In this study, authentication system contained two parts: registration part and matching part. In both parts, iris image is used for personal identification. Localization of inner boundary only, extracted a region from the iris (without eyelashes problem), a feature vector is deduced from the texture of the image. The feature vector is used for classification of the iris texture, then it's treated by the hash function to produce the hash value (authentic value of a person). In matching part, produced hash value searched in the authorized person's database for taking a decision (success or fail) of the authentication. The method was evaluated on iris images takes from the CASIA iris image database version 1.0 [15]. The experimental results show that the vector extracted by the proposed method has very discriminating values that led to a recognition rate of over 100% on iris database. Also, authentication system is very accurate because it's used a secure method of authentication that iris-biometric and a hash function for avoiding stealing data from database.
Cancelable biometrics, a template transformation approach, attempts to provide robustness for authentication services based on biometrics. Several biometric template protection techniques represent the biometric information in binary form as it provides benefits in matching and storage. In this context, it becomes clear that often such transformed binary representations can be easily compromised and breached. In this paper, we propose an efficient non-invertible template transformation approach using random projection technique and Discrete Fourier transformation to shield the binary biometric representations. The cancelable fingerprint templates designed by the proposed technique meets the requirements of revocability, diversity, non-invertibility and performance. The matching performance of the cancelable fingerprint templates generated using proposed technique, have improved when compared with the state-of-art methods.
Software projects mostly exceeds budget, delivered late and does not meet with the customer’s satisfaction for years. In the past, many traditional development models like waterfall, spiral, iterative, and prototyping methods are used to build the software systems. In recent years, agile models are widely used in developing the software products. The major reasons are – simplicity, incorporating the requirement changes at any time, light-weight approach and delivering the working product early and in short duration. Whatever the development model used, it still remains a challenge for software engineer’s to accurately estimate the size, effort and the time required for developing the software system. This survey focuses on the existing estimation models used in traditional as well in agile software development.
Role of fuzzy in multimodal biometrics systemKishor Singh
This document summarizes a research paper on using fuzzy logic in a multimodal biometrics system combining face, ear, and foot recognition. It discusses how unimodal biometric systems have limitations that multimodal systems aim to overcome through data fusion. The methodology uses eigenfaces for face recognition, eigenimages for ear recognition, and sequential modified Haar transform for foot recognition. Scores are normalized and fused using fuzzy logic rules. Highest matching was found when fusing face and ear, lowest when fusing ear and foot. The fuzzy multimodal system enhanced identification accuracy over unimodal systems.
The researchers have been exploring methods to use biometric characteristics of the user as a replacement for using unforgettable pass-word, in an attempt to build robust cryptographic keys, because, human users detect difficulties to call up long cryptographic keys. Biometric recognition provides an authentic solution to the authentication of the user problem in the identity administration systems. With the extensive utilization of biometric methods in different applications, there is growing concern about the confidentiality and security of the biometric technologies. This paper proposes biometric based key recreation scheme. Since human ears are not correlated. Until now, the encryption keys are generated using a swarm intelligence approach. Collective intelligence of simple groups of autonomous agents have been emerged by swarm intelligence. The crow search algorithm which is known as (CSA) is a new meta-intuitive method assembled by the intelligent group behavior of crows. Despite that CSA demonstrates important features, its search approach poses excessive challenges while faced with great multimodal formularization.
Iris Biometric Based Person Identification Using Deep Learning TechniqueIRJET Journal
This document presents a person identification system based on iris recognition using deep learning. It uses the ResNet-50 model for feature extraction from iris images. The system first preprocesses iris images to remove noise and reflections. It then segments the iris region using Daugman's operator and normalizes it using his rubber sheet model. The normalized iris images are input to the pre-trained ResNet-50 model to extract features. Finally, multiclass SVM is used to perform person identification based on the extracted features. The system was tested on the VISA iris database and achieved 95% accuracy in identification.
This document summarizes research on combining face and fingerprint biometrics at the data level using fusion. Multimodal biometric systems that combine evidence from multiple sources can improve recognition accuracy, population coverage, and fault tolerance compared to unimodal systems. The document discusses related work on multimodal biometrics fusion and approaches like DWT coefficient selection. It also outlines the proposed approach of fusing face and fingerprint images using wavelet transform for feature extraction and similarity measures for the multimodal biometric system.
Security for Identity Based Identification using Water Marking and Visual Cry...IRJET Journal
This document discusses using watermarking and visual cryptography for secure identity-based authentication. It proposes embedding an iris image using a watermarking algorithm and visual cryptography techniques for protection. Feature extraction and binomial distribution analysis are used to evaluate false acceptance and rejection rates to validate two algorithms, MASEK and Ma, for iris recognition on noisy images. The document also discusses discrete cosine transform (DCT) and discrete wavelet transform (DWT) techniques for image processing and compression in iris recognition systems.
This document discusses personal identification and verification using multimodal biometrics. It begins by introducing biometrics and describing commonly used hand-based biometrics like fingerprints, palm prints, hand geometry, and palm vein patterns. It then discusses selecting biometrics based on characteristics like universality, distinctiveness, and permanence. The document focuses on palm prints and hand geometry as biometrics. It describes features that can be extracted from palm prints, like geometry, principal lines, wrinkles, datum points, delta points, and minutiae. It also discusses features used in hand geometry biometrics, like finger lengths, widths, and positions. Finally, it proposes a design for a multimodal system combining palm print and hand geometry biometrics for
The document describes a multimodal biometric identification system based on iris and fingerprint recognition. It discusses the individual steps of iris and fingerprint recognition including segmentation, feature extraction, and matching. For fingerprint recognition, minutiae points are extracted and matched. For iris recognition, the iris region is segmented from an eye image and normalized before feature extraction. The multimodal system fuses the matching scores from the individual iris and fingerprint recognition at the matching level to improve accuracy by reducing false acceptance and rejection rates compared to unimodal systems. Experimental results on standard databases show the proposed multimodal approach achieves better performance than unimodal biometrics.
This document discusses a proposed framework for securing biometric templates using encryption and error correction. It begins with an introduction to biometric systems and their use of templates to identify individuals. It then discusses existing issues with transmitting biometric templates due to noise and errors. The proposed framework encrypts biometric templates using a secret key generated from braid groups before transmission. It also uses fuzzy error correction codes to detect and correct any errors introduced during transmission. The framework aims to provide both security of biometric templates and accuracy of identification by addressing noise issues.
IOSR Journal of Electronics and Communication Engineering(IOSR-JECE) is an open access international journal that provides rapid publication (within a month) of articles in all areas of electronics and communication engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in electronics and communication engineering. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
IRDO: Iris Recognition by fusion of DTCWT and OLBPIJERA Editor
This document proposes a new iris recognition method called IRDO that fuses Dual Tree Complex Wavelet Transform (DTCWT) and Overlapping Local Binary Pattern (OLBP) features. DTCWT is used to extract micro-texture features from the iris, while OLBP enhances the extraction of edge features. Fusing these two methods results in improved matching performance and classification accuracy compared to state-of-the-the-art techniques. The proposed IRDO method achieves higher iris recognition rates as measured by Total Success Rate and Equal Error Rate.
This document summarizes a research paper on a multimodal biometric system using fingerprint and face for identification. The system uses two modalities - fingerprint and face - to achieve greater accuracy than single-feature systems. It extracts minutiae from fingerprints and uses eigenspace projection for face recognition. Matching scores from each modality are fused at the decision level to make the final identification. The system was tested on a database of 25 users, collecting multiple fingerprint and face images per user under controlled conditions. Experimental results showed the multimodal system achieved lower error rates than unimodal systems.
A survey paper on various biometric security system methodsIRJET Journal
This document summarizes various biometric security systems for identification. It discusses fingerprint recognition, iris recognition, and face recognition methods. It provides an overview of different approaches that have been proposed, including using watermarking, edge detection techniques, adaptive boosting algorithms, and fuzzy logic. The document also analyzes the drawbacks of previous methods and proposes using a multimodal biometric system that fuses fingerprints, iris, and face for more secure identification. Overall, the document surveys different biometric identification techniques and highlights that a multimodal approach can help overcome limitations of individual methods.
Similar to Bimodal Biometric System using Multiple Transformation Features of Fingerprint and Iris (20)
Power System State Estimation - A ReviewIDES Editor
This document provides a review of power system state estimation techniques. It discusses both static and dynamic state estimation algorithms. For static state estimation, it covers weighted least squares, decoupled, and robust estimation methods. Weighted least squares is commonly used but can have numerical instability issues. Decoupled state estimation approximates the gain matrix for faster computation. Robust estimation uses M-estimators and other techniques to handle outliers and bad data. Dynamic state estimation applies Kalman filtering, leapfrog algorithms, and other methods to continuously monitor system states over time.
Artificial Intelligence Technique based Reactive Power Planning Incorporating...IDES Editor
This document summarizes a research paper that proposes using artificial intelligence techniques and FACTS controllers for reactive power planning in real-time power transmission systems. The paper formulates the reactive power planning problem and incorporates flexible AC transmission system (FACTS) devices like static VAR compensators (SVC), thyristor controlled series capacitors (TCSC), and unified power flow controllers (UPFC). Evolutionary algorithms like evolutionary programming (EP) and differential evolution (DE) are applied to find the optimal locations and settings of the FACTS controllers to minimize losses and costs. Simulation results on IEEE 30-bus and 72-bus Indian test systems show that UPFC performs best in reducing losses compared to SVC and TCSC.
Design and Performance Analysis of Genetic based PID-PSS with SVC in a Multi-...IDES Editor
Damping of power system oscillations with the help
of proposed optimal Proportional Integral Derivative Power
System Stabilizer (PID-PSS) and Static Var Compensator
(SVC)-based controllers are thoroughly investigated in this
paper. This study presents robust tuning of PID-PSS and
SVC-based controllers using Genetic Algorithms (GA) in
multi machine power systems by considering detailed model
of the generators (model 1.1). The effectiveness of FACTSbased
controllers in general and SVC-based controller in
particular depends upon their proper location. Modal
controllability and observability are used to locate SVC–based
controller. The performance of the proposed controllers is
compared with conventional lead-lag power system stabilizer
(CPSS) and demonstrated on 10 machines, 39 bus New England
test system. Simulation studies show that the proposed genetic
based PID-PSS with SVC based controller provides better
performance.
Optimal Placement of DG for Loss Reduction and Voltage Sag Mitigation in Radi...IDES Editor
This paper presents the need to operate the power
system economically and with optimum levels of voltages has
further led to an increase in interest in Distributed
Generation. In order to reduce the power losses and to improve
the voltage in the distribution system, distributed generators
(DGs) are connected to load bus. To reduce the total power
losses in the system, the most important process is to identify
the proper location for fixing and sizing of DGs. It presents a
new methodology using a new population based meta heuristic
approach namely Artificial Bee Colony algorithm(ABC) for
the placement of Distributed Generators(DG) in the radial
distribution systems to reduce the real power losses and to
improve the voltage profile, voltage sag mitigation. The power
loss reduction is important factor for utility companies because
it is directly proportional to the company benefits in a
competitive electricity market, while reaching the better power
quality standards is too important as it has vital effect on
customer orientation. In this paper an ABC algorithm is
developed to gain these goals all together. In order to evaluate
sag mitigation capability of the proposed algorithm, voltage
in voltage sensitive buses is investigated. An existing 20KV
network has been chosen as test network and results are
compared with the proposed method in the radial distribution
system.
Line Losses in the 14-Bus Power System Network using UPFCIDES Editor
Controlling power flow in modern power systems
can be made more flexible by the use of recent developments
in power electronic and computing control technology. The
Unified Power Flow Controller (UPFC) is a Flexible AC
transmission system (FACTS) device that can control all the
three system variables namely line reactance, magnitude and
phase angle difference of voltage across the line. The UPFC
provides a promising means to control power flow in modern
power systems. Essentially the performance depends on proper
control setting achievable through a power flow analysis
program. This paper presents a reliable method to meet the
requirements by developing a Newton-Raphson based load
flow calculation through which control settings of UPFC can
be determined for the pre-specified power flow between the
lines. The proposed method keeps Newton-Raphson Load Flow
(NRLF) algorithm intact and needs (little modification in the
Jacobian matrix). A MATLAB program has been developed to
calculate the control settings of UPFC and the power flow
between the lines after the load flow is converged. Case studies
have been performed on IEEE 5-bus system and 14-bus system
to show that the proposed method is effective. These studies
indicate that the method maintains the basic NRLF properties
such as fast computational speed, high degree of accuracy and
good convergence rate.
Study of Structural Behaviour of Gravity Dam with Various Features of Gallery...IDES Editor
The size and shape of opening in dam causes the
stress concentration, it also causes the stress variation in the
rest of the dam cross section. The gravity method of the analysis
does not consider the size of opening and the elastic property
of dam material. Thus the objective of study is comprises of
the Finite Element Method which considers the size of
opening, elastic property of material, and stress distribution
because of geometric discontinuity in cross section of dam.
Stress concentration inside the dam increases with the opening
in dam which results in the failure of dam. Hence it is
necessary to analyses large opening inside the dam. By making
the percentage area of opening constant and varying size and
shape of opening the analysis is carried out. For this purpose
a section of Koyna Dam is considered. Dam is defined as a
plane strain element in FEM, based on geometry and loading
condition. Thus this available information specified our path
of approach to carry out 2D plane strain analysis. The results
obtained are then compared mutually to get most efficient
way of providing large opening in the gravity dam.
Assessing Uncertainty of Pushover Analysis to Geometric ModelingIDES Editor
Pushover Analysis a popular tool for seismic
performance evaluation of existing and new structures and is
nonlinear Static procedure where in monotonically increasing
loads are applied to the structure till the structure is unable
to resist the further load .During the analysis, whatever the
strength of concrete and steel is adopted for analysis of
structure may not be the same when real structure is
constructed and the pushover analysis results are very sensitive
to material model adopted, geometric model adopted, location
of plastic hinges and in general to procedure followed by the
analyzer. In this paper attempt has been made to assess
uncertainty in pushover analysis results by considering user
defined hinges and frame modeled as bare frame and frame
with slab modeled as rigid diaphragm and results compared
with experimental observations. Uncertain parameters
considered includes the strength of concrete, strength of steel
and cover to the reinforcement which are randomly generated
and incorporated into the analysis. The results are then
compared with experimental observations.
Secure Multi-Party Negotiation: An Analysis for Electronic Payments in Mobile...IDES Editor
This document summarizes and analyzes secure multi-party negotiation protocols for electronic payments in mobile computing. It presents a framework for secure multi-party decision protocols using lightweight implementations. The main focus is on synchronizing security features to avoid agreement manipulation and reduce user traffic. The paper describes negotiation between an auctioneer and bidders, showing multiparty security is better than existing systems. It analyzes the performance of encryption algorithms like ECC, XTR, and RSA for use in the multiparty negotiation protocols.
Selfish Node Isolation & Incentivation using Progressive ThresholdsIDES Editor
The problems associated with selfish nodes in
MANET are addressed by a collaborative watchdog approach
which reduces the detection time for selfish nodes thereby
improves the performance and accuracy of watchdogs[1]. In
the related works they make use of credit based systems, reputation
based mechanisms, pathrater and watchdog mechanism
to detect such selfish nodes. In this paper we follow an approach
of collaborative watchdog which reduces the detection
time for selfish nodes and also involves the removal of such
selfish nodes based on some progressively assessed thresholds.
The threshold gives the nodes a chance to stop misbehaving
before it is permanently deleted from the network.
The node passes through several isolation processes before it
is permanently removed. Another version of AODV protocol
is used here which allows the simulation of selfish nodes in
NS2 by adding or modifying log files in the protocol.
Various OSI Layer Attacks and Countermeasure to Enhance the Performance of WS...IDES Editor
Wireless sensor networks are networks having non
wired infrastructure and dynamic topology. In OSI model each
layer is prone to various attacks, which halts the performance
of a network .In this paper several attacks on four layers of
OSI model are discussed and security mechanism is described
to prevent attack in network layer i.e wormhole attack. In
Wormhole attack two or more malicious nodes makes a covert
channel which attracts the traffic towards itself by depicting a
low latency link and then start dropping and replaying packets
in the multi-path route. This paper proposes promiscuous mode
method to detect and isolate the malicious node during
wormhole attack by using Ad-hoc on demand distance vector
routing protocol (AODV) with omnidirectional antenna. The
methodology implemented notifies that the nodes which are
not participating in multi-path routing generates an alarm
message during delay and then detects and isolate the
malicious node from network. We also notice that not only
the same kind of attacks but also the same kind of
countermeasures can appear in multiple layer. For example,
misbehavior detection techniques can be applied to almost all
the layers we discussed.
Responsive Parameter based an AntiWorm Approach to Prevent Wormhole Attack in...IDES Editor
The recent advancements in the wireless technology
and their wide-spread deployment have made remarkable
enhancements in efficiency in the corporate and industrial
and Military sectors The increasing popularity and usage of
wireless technology is creating a need for more secure wireless
Ad hoc networks. This paper aims researched and developed
a new protocol that prevents wormhole attacks on a ad hoc
network. A few existing protocols detect wormhole attacks but
they require highly specialized equipment not found on most
wireless devices. This paper aims to develop a defense against
wormhole attacks as an Anti-worm protocol which is based on
responsive parameters, that does not require as a significant
amount of specialized equipment, trick clock synchronization,
no GPS dependencies.
Cloud Security and Data Integrity with Client Accountability FrameworkIDES Editor
This document summarizes a proposed cloud security and data integrity framework that provides client accountability. The framework aims to address issues like lack of user control over cloud data, need for data transparency and tracking, and ensuring data integrity. It proposes using JAR (Java Archive) files for data sharing due to benefits like portability. The framework incorporates client-side verification using MD5 hashing, digital signature-based authentication of JAR files, and use of HMAC to ensure data integrity. It also uses password-based encryption of log files to keep them tamper-proof. The framework is intended to provide both accountability and security for data sharing in cloud environments.
Genetic Algorithm based Layered Detection and Defense of HTTP BotnetIDES Editor
A System state in HTTP botnet uses HTTP protocol
for the creation of chain of Botnets thereby compromising
other systems. By using HTTP protocol and port number 80,
attacks can not only be hidden but also pass through the
firewall without being detected. The DPR based detection
leads to better analysis of botnet attacks [3]. However, it
provides only probabilistic detection of the attacker and also
time consuming and error prone. This paper proposes a Genetic
algorithm based layered approach for detecting as well as
preventing botnet attacks. The paper reviews p2p firewall
implementation which forms the basis of filtering.
Performance evaluation is done based on precision, F-value
and probability. Layered approach reduces the computation
and overall time requirement [7]. Genetic algorithm promises
a low false positive rate.
Enhancing Data Storage Security in Cloud Computing Through SteganographyIDES Editor
This document summarizes a research paper that proposes a method for enhancing data security in cloud computing through steganography. The method hides user data in digital images stored on cloud servers. When data needs to be accessed, it is extracted from the images. The document outlines the cloud architecture and security issues addressed. It then describes the proposed system architecture, security model, and data storage and retrieval process. Data is partitioned and hidden in multiple images to improve security. The goal is to prevent unauthorized access to user data stored on cloud servers.
The main tasks of a Wireless Sensor Network
(WSN) are data collection from its nodes and communication
of this data to the base station (BS). The protocols used for
communication among the WSN nodes and between the WSN
and the BS, must consider the resource constraints of nodes,
battery energy, computational capabilities and memory. The
WSN applications involve unattended operation of the network
over an extended period of time. In order to extend the lifetime
of a WSN, efficient routing protocols need to be adopted. The
proposed low power routing protocol based on tree-based
network structure reliably forwards the measured data towards
the BS using TDMA. An energy consumption analysis of the
WSN making use of this protocol is also carried out. It is
found that the network is energy efficient with an average
duty cycle of 0:7% for the WSN nodes. The OmNET++
simulation platform along with MiXiM framework is made
use of.
Permutation of Pixels within the Shares of Visual Cryptography using KBRP for...IDES Editor
The security of authentication of internet based
co-banking services should not be susceptible to high risks.
The passwords are highly vulnerable to virus attacks due to
the lack of high end embedding of security methods. In order
for the passwords to be more secure, people are generally
compelled to select jumbled up character based passwords
which are not only less memorable but are also equally prone
to insecurity. Multiple use of distributed shares has been
studied to solve the problem of authentication by algorithms
based on thresholding of pixels in image processing and visual
cryptography concepts where the subset of shares is considered
for the recovery of the original image for authentication using
correlation function[1][2].The main disadvantage in the above
study is the plain storage of shares and also one of the shares
is being supplied to the customer, which will lead to the
possibility of misuse by a third party. This paper proposes a
technique for scrambling of pixels by key based random
permutation (KBRP) within the shares before the
authentication has been attempted. Total number of shares to
be created is dependent on the multiplicity of ownership of
the account. By this method the problem of uncertainty among
the customers with regard to security, storage, retrieval of
holding of half of the shares is minimized.
This paper presents a trifocal Rotman Lens Design
approach. The effects of focal ratio and element spacing on
the performance of Rotman Lens are described. A three beam
prototype feeding 4 element antenna array working in L-band
has been simulated using RLD v1.7 software. Simulated
results show that the simulated lens has a return loss of –
12.4dB at 1.8GHz. Beam to array port phase error variation
with change in the focal ratio and element spacing has also
been investigated.
Band Clustering for the Lossless Compression of AVIRIS Hyperspectral ImagesIDES Editor
Hyperspectral images can be efficiently compressed
through a linear predictive model, as for example the one
used in the SLSQ algorithm. In this paper we exploit this
predictive model on the AVIRIS images by individuating,
through an off-line approach, a common subset of bands, which
are not spectrally related with any other bands. These bands
are not useful as prediction reference for the SLSQ 3-D
predictive model and we need to encode them via other
prediction strategies which consider only spatial correlation.
We have obtained this subset by clustering the AVIRIS bands
via the clustering by compression approach. The main result
of this paper is the list of the bands, not related with the
others, for AVIRIS images. The clustering trees obtained for
AVIRIS and the relationship among bands they depict is also
an interesting starting point for future research.
Microelectronic Circuit Analogous to Hydrogen Bonding Network in Active Site ...IDES Editor
A microelectronic circuit of block-elements
functionally analogous to two hydrogen bonding networks is
investigated. The hydrogen bonding networks are extracted
from â-lactamase protein and are formed in its active site.
Each hydrogen bond of the network is described in equivalent
electrical circuit by three or four-terminal block-element.
Each block-element is coded in Matlab. Static and dynamic
analyses are performed. The resultant microelectronic circuit
analogous to the hydrogen bonding network operates as
current mirror, sine pulse source, triangular pulse source as
well as signal modulator.
Texture Unit based Monocular Real-world Scene Classification using SOM and KN...IDES Editor
In this paper a method is proposed to discriminate
real world scenes in to natural and manmade scenes of similar
depth. Global-roughness of a scene image varies as a function
of image-depth. Increase in image depth leads to increase in
roughness in manmade scenes; on the contrary natural scenes
exhibit smooth behavior at higher image depth. This particular
arrangement of pixels in scene structure can be well explained
by local texture information in a pixel and its neighborhood.
Our proposed method analyses local texture information of a
scene image using texture unit matrix. For final classification
we have used both supervised and unsupervised learning using
K-Nearest Neighbor classifier (KNN) and Self Organizing
Map (SOM) respectively. This technique is useful for online
classification due to very less computational complexity.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/how-axelera-ai-uses-digital-compute-in-memory-to-deliver-fast-and-energy-efficient-computer-vision-a-presentation-from-axelera-ai/
Bram Verhoef, Head of Machine Learning at Axelera AI, presents the “How Axelera AI Uses Digital Compute-in-memory to Deliver Fast and Energy-efficient Computer Vision” tutorial at the May 2024 Embedded Vision Summit.
As artificial intelligence inference transitions from cloud environments to edge locations, computer vision applications achieve heightened responsiveness, reliability and privacy. This migration, however, introduces the challenge of operating within the stringent confines of resource constraints typical at the edge, including small form factors, low energy budgets and diminished memory and computational capacities. Axelera AI addresses these challenges through an innovative approach of performing digital computations within memory itself. This technique facilitates the realization of high-performance, energy-efficient and cost-effective computer vision capabilities at the thin and thick edge, extending the frontier of what is achievable with current technologies.
In this presentation, Verhoef unveils his company’s pioneering chip technology and demonstrates its capacity to deliver exceptional frames-per-second performance across a range of standard computer vision networks typical of applications in security, surveillance and the industrial sector. This shows that advanced computer vision can be accessible and efficient, even at the very edge of our technological ecosystem.
"Frontline Battles with DDoS: Best practices and Lessons Learned", Igor IvaniukFwdays
At this talk we will discuss DDoS protection tools and best practices, discuss network architectures and what AWS has to offer. Also, we will look into one of the largest DDoS attacks on Ukrainian infrastructure that happened in February 2022. We'll see, what techniques helped to keep the web resources available for Ukrainians and how AWS improved DDoS protection for all customers based on Ukraine experience
Main news related to the CCS TSI 2023 (2023/1695)Jakub Marek
An English 🇬🇧 translation of a presentation to the speech I gave about the main changes brought by CCS TSI 2023 at the biggest Czech conference on Communications and signalling systems on Railways, which was held in Clarion Hotel Olomouc from 7th to 9th November 2023 (konferenceszt.cz). Attended by around 500 participants and 200 on-line followers.
The original Czech 🇨🇿 version of the presentation can be found here: https://www.slideshare.net/slideshow/hlavni-novinky-souvisejici-s-ccs-tsi-2023-2023-1695/269688092 .
The videorecording (in Czech) from the presentation is available here: https://youtu.be/WzjJWm4IyPk?si=SImb06tuXGb30BEH .
Essentials of Automations: Exploring Attributes & Automation ParametersSafe Software
Building automations in FME Flow can save time, money, and help businesses scale by eliminating data silos and providing data to stakeholders in real-time. One essential component to orchestrating complex automations is the use of attributes & automation parameters (both formerly known as “keys”). In fact, it’s unlikely you’ll ever build an Automation without using these components, but what exactly are they?
Attributes & automation parameters enable the automation author to pass data values from one automation component to the next. During this webinar, our FME Flow Specialists will cover leveraging the three types of these output attributes & parameters in FME Flow: Event, Custom, and Automation. As a bonus, they’ll also be making use of the Split-Merge Block functionality.
You’ll leave this webinar with a better understanding of how to maximize the potential of automations by making use of attributes & automation parameters, with the ultimate goal of setting your enterprise integration workflows up on autopilot.
How to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdfChart Kalyan
A Mix Chart displays historical data of numbers in a graphical or tabular form. The Kalyan Rajdhani Mix Chart specifically shows the results of a sequence of numbers over different periods.
Introduction of Cybersecurity with OSS at Code Europe 2024Hiroshi SHIBATA
I develop the Ruby programming language, RubyGems, and Bundler, which are package managers for Ruby. Today, I will introduce how to enhance the security of your application using open-source software (OSS) examples from Ruby and RubyGems.
The first topic is CVE (Common Vulnerabilities and Exposures). I have published CVEs many times. But what exactly is a CVE? I'll provide a basic understanding of CVEs and explain how to detect and handle vulnerabilities in OSS.
Next, let's discuss package managers. Package managers play a critical role in the OSS ecosystem. I'll explain how to manage library dependencies in your application.
I'll share insights into how the Ruby and RubyGems core team works to keep our ecosystem safe. By the end of this talk, you'll have a better understanding of how to safeguard your code.
Your One-Stop Shop for Python Success: Top 10 US Python Development Providersakankshawande
Simplify your search for a reliable Python development partner! This list presents the top 10 trusted US providers offering comprehensive Python development services, ensuring your project's success from conception to completion.
Digital Banking in the Cloud: How Citizens Bank Unlocked Their MainframePrecisely
Inconsistent user experience and siloed data, high costs, and changing customer expectations – Citizens Bank was experiencing these challenges while it was attempting to deliver a superior digital banking experience for its clients. Its core banking applications run on the mainframe and Citizens was using legacy utilities to get the critical mainframe data to feed customer-facing channels, like call centers, web, and mobile. Ultimately, this led to higher operating costs (MIPS), delayed response times, and longer time to market.
Ever-changing customer expectations demand more modern digital experiences, and the bank needed to find a solution that could provide real-time data to its customer channels with low latency and operating costs. Join this session to learn how Citizens is leveraging Precisely to replicate mainframe data to its customer channels and deliver on their “modern digital bank” experiences.
How information systems are built or acquired puts information, which is what they should be about, in a secondary place. Our language adapted accordingly, and we no longer talk about information systems but applications. Applications evolved in a way to break data into diverse fragments, tightly coupled with applications and expensive to integrate. The result is technical debt, which is re-paid by taking even bigger "loans", resulting in an ever-increasing technical debt. Software engineering and procurement practices work in sync with market forces to maintain this trend. This talk demonstrates how natural this situation is. The question is: can something be done to reverse the trend?
Discover top-tier mobile app development services, offering innovative solutions for iOS and Android. Enhance your business with custom, user-friendly mobile applications.
Fueling AI with Great Data with Airbyte WebinarZilliz
This talk will focus on how to collect data from a variety of sources, leveraging this data for RAG and other GenAI use cases, and finally charting your course to productionalization.
Generating privacy-protected synthetic data using Secludy and MilvusZilliz
During this demo, the founders of Secludy will demonstrate how their system utilizes Milvus to store and manipulate embeddings for generating privacy-protected synthetic data. Their approach not only maintains the confidentiality of the original data but also enhances the utility and scalability of LLMs under privacy constraints. Attendees, including machine learning engineers, data scientists, and data managers, will witness first-hand how Secludy's integration with Milvus empowers organizations to harness the power of LLMs securely and efficiently.
Ivanti’s Patch Tuesday breakdown goes beyond patching your applications and brings you the intelligence and guidance needed to prioritize where to focus your attention first. Catch early analysis on our Ivanti blog, then join industry expert Chris Goettl for the Patch Tuesday Webinar Event. There we’ll do a deep dive into each of the bulletins and give guidance on the risks associated with the newly-identified vulnerabilities.