In identity management system, commonly used biometric recognition system needs attention
towards issue of biometric template protection as far as more reliable solution is concerned. In
view of this biometric template protection algorithm should satisfy security, discriminability and
cancelability. As no single template protection method is capable of satisfying the basic
requirements, a novel technique for face template generation and protection is proposed. The
novel approach is proposed to provide security and accuracy in new user enrollment as well as
authentication process. This novel technique takes advantage of both the hybrid approach and
the binary discriminant analysis algorithm. This algorithm is designed on the basis of random
projection, binary discriminant analysis and fuzzy commitment scheme. Three publicly available
benchmark face databases are used for evaluation. The proposed novel technique enhances the
discriminability and recognition accuracy by 80% in terms of matching score of the face images
and provides high security.
A novel approach to generate face biometric template using binary discriminat...sipij
In identity management system, commonly used biometric recognition system needs attention towards issue
of biometric template protection as far as more reliable solution is concerned. In view of this biometric
template protection algorithm should satisfy security, discriminability and cancelability. As no single
template protection method is capable of satisfying the basic requirements, a novel technique for face
biometric template generation and protection is proposed. The novel approach is proposed to provide
security and accuracy in new user enrolment as well as verification process. This novel technique takes
advantage of both the hybrid approach and the binary discriminant analysis algorithm. This algorithm is
designed on the basis of random projection, binary discriminant analysis and fuzzy commitment scheme.
Three publicly available benchmark face databases (FERET, FRGC, CMU-PIE) are used for evaluation.
The proposed novel technique enhances the discriminability and recognition accuracy in terms of matching
score of the face images and provides high security. This paper discusses the corresponding results.
Pattern recognition using context dependent memory model (cdmm) in multimodal...ijfcstjournal
Pattern recognition is one of the prime concepts in current technologies in both private and public sectors.
The analysis and recognition of two or more patterns is a complex task due to several factors. The
consideration of two or more patterns requires huge space for keeping the storage media as well as
computational aspect. Vector logic gives very good strategy for recognition of patterns. This paper
proposes pattern recognition in multimodal authentication system with the use of vector logic and makes
the computation model hard and less error rate. Using PCA two to three biometric patterns will be fusion
and then various key sizes will be extracted using LU factorization approach. The selected keys will be
combined using vector logic, which introduces a memory model often called Context Dependent Memory
Model (CDMM) as computational model in multimodal authentication system that gives very accurate and
very effective outcome for authentication as well as verification. In the verification step, Mean Square
Error (MSE) and Normalized Correlation (NC) as metrics to minimize the error rate for the proposed
model and the performance analysis will be presented.
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.
AN EVALUATION OF FINGERPRINT SECURITY USING NONINVERTIBLE BIOHASHIJNSA Journal
Biometric analysis for identifying verification is becoming a widespread reality. It is a very challenging and tedious task to develop a biometric template protection scheme which is anonymous, revocable and noninvertible while maintaining decent performance. Cancellable biometrics is one of the best methods used to resolve this problem. In this paper, a new method called as BioHashing which follows the technique of cancellable biometrics in the fingerprint domain is proposed. This proposed method does not require the re-alignment of fingerprints as all the minutiae are translated into a pre-defined two dimensional space based on a reference minutia. After that, the proposed Biohashing method is used to enforce the one-way property (non-invertibility) of the biometric template. The proposed approach is very much resistant to minor translation error and rotation distortion. An Equal Error Rates (EER) of less than 1% is achieved in this approach and performance of the approach is also significant.
A novel approach to generate face biometric template using binary discriminat...sipij
In identity management system, commonly used biometric recognition system needs attention towards issue
of biometric template protection as far as more reliable solution is concerned. In view of this biometric
template protection algorithm should satisfy security, discriminability and cancelability. As no single
template protection method is capable of satisfying the basic requirements, a novel technique for face
biometric template generation and protection is proposed. The novel approach is proposed to provide
security and accuracy in new user enrolment as well as verification process. This novel technique takes
advantage of both the hybrid approach and the binary discriminant analysis algorithm. This algorithm is
designed on the basis of random projection, binary discriminant analysis and fuzzy commitment scheme.
Three publicly available benchmark face databases (FERET, FRGC, CMU-PIE) are used for evaluation.
The proposed novel technique enhances the discriminability and recognition accuracy in terms of matching
score of the face images and provides high security. This paper discusses the corresponding results.
Pattern recognition using context dependent memory model (cdmm) in multimodal...ijfcstjournal
Pattern recognition is one of the prime concepts in current technologies in both private and public sectors.
The analysis and recognition of two or more patterns is a complex task due to several factors. The
consideration of two or more patterns requires huge space for keeping the storage media as well as
computational aspect. Vector logic gives very good strategy for recognition of patterns. This paper
proposes pattern recognition in multimodal authentication system with the use of vector logic and makes
the computation model hard and less error rate. Using PCA two to three biometric patterns will be fusion
and then various key sizes will be extracted using LU factorization approach. The selected keys will be
combined using vector logic, which introduces a memory model often called Context Dependent Memory
Model (CDMM) as computational model in multimodal authentication system that gives very accurate and
very effective outcome for authentication as well as verification. In the verification step, Mean Square
Error (MSE) and Normalized Correlation (NC) as metrics to minimize the error rate for the proposed
model and the performance analysis will be presented.
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.
AN EVALUATION OF FINGERPRINT SECURITY USING NONINVERTIBLE BIOHASHIJNSA Journal
Biometric analysis for identifying verification is becoming a widespread reality. It is a very challenging and tedious task to develop a biometric template protection scheme which is anonymous, revocable and noninvertible while maintaining decent performance. Cancellable biometrics is one of the best methods used to resolve this problem. In this paper, a new method called as BioHashing which follows the technique of cancellable biometrics in the fingerprint domain is proposed. This proposed method does not require the re-alignment of fingerprints as all the minutiae are translated into a pre-defined two dimensional space based on a reference minutia. After that, the proposed Biohashing method is used to enforce the one-way property (non-invertibility) of the biometric template. The proposed approach is very much resistant to minor translation error and rotation distortion. An Equal Error Rates (EER) of less than 1% is achieved in this approach and performance of the approach is also significant.
An offline signature verification using pixels intensity levelsSalam Shah
Offline signature recognition has great importance in our day to day activities. Researchers are trying to use them as biometric identification in various areas like banks, security systems and for other identification purposes. Fingerprints, iris, thumb impression and face detection based biometrics are successfully used for identification of individuals because of their static nature. However, people’s signatures show variability that makes it difficult to recognize the original signatures correctly and to use them as biometrics. The handwritten signatures have importance in banks for cheque, credit card processing, legal and financial transactions, and the signatures are the main target of fraudulence. To deal with complex signatures, there should be a robust signature verification method in places such as banks that can correctly classify the signatures into genuine or forgery to avoid financial frauds. This paper, presents a pixels intensity level based offline signature verification model for the correct classification of signatures. To achieve the target, three statistical classifiers; Decision Tree (J48), probability based Naïve Bayes (NB tree) and Euclidean distance based k-Nearest Neighbor (IBk), are used.
For comparison of the accuracy rates of offline signatures with online signatures, three classifiers were applied on online signature database and achieved a 99.90% accuracy rate with decision tree (J48), 99.82% with Naïve Bayes Tree and 98.11% with K-Nearest Neighbor (with 10 fold cross validation). The results of offline signatures were 64.97% accuracy rate with decision tree (J48), 76.16% with Naïve Bayes Tree and 91.91% with k-Nearest Neighbor (IBk) (without forgeries). The accuracy rate dropped with the inclusion of forgery signatures as, 55.63% accuracy rate with decision tree (J48), 67.02% with Naïve Bayes Tree and 88.12% (with forgeries).
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.
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.
A Survey of Security of Multimodal Biometric SystemsIJERA Editor
A biometric system is essentially a pattern recognition system being used in adversarial environment. Since,
biometric system like any conventional security system is exposed to malicious adversaries, who can manipulate
data to make the system ineffective by compromising its integrity. Current theory and design methods of
biometric systems do not take into account the vulnerability to such adversary attacks. Therefore, evaluation of
classical design methods is an open problem to investigate whether they lead to design secure systems. In order
to make biometric systems secure it is necessary to understand and evaluate the threats and to thus develop
effective countermeasures and robust system designs, both technical and procedural, if necessary. Accordingly,
the extension of theory and design methods of biometric systems is mandatory to safeguard the security and
reliability of biometric systems in adversarial environments.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
An Indexing Technique Based on Feature Level Fusion of Fingerprint FeaturesIDES Editor
Personal identification system based on pass word
and other entities are ineffective. Nowadays biometric based
systems are used for human identification in almost many
real time applications. The current state-of-art biometric
identification focuses on accuracy and hence a good
performance result in terms of response time on small scale
database is achieved. But in today’s real life scenario biometric
database are huge and without any intelligent scheme the
response time should be high, but the existing algorithms
requires an exhaustive search on the database which increases
proportionally when the size of the database grows. This paper
addresses the problem of biometric indexing in the context of
fingerprint. Indexing is a technique to reduce the number of
candidate identities to be considered by the identification
algorithm. The fingerprint indexing methodology projected
in this work is based on a combination of Level 1, Level 2 and
Level-3 fingerprint features. The result shows the fusion of
level 1, level 2 and level 3 features gives better performance
and good indexing rate than with any one level of fingerprint
feature.
Analysis of the Iriscode Bioencoding SchemeCSCJournals
Cancelable biometrics is a technique used to enhance security and user privacy. These schemes are employed to generate multiple revocable data from the original biometric template. In this paper, the security of binary template transformations is evaluated, through a new transformation for iris templates, called bioencoding scheme. This transformation and its security is analyzed, using Boolean functions and non linear Boolean systems. A general discussion on binary template transformations is finally proposed.
A Fast and Accurate Palmprint Identification System based on Consistency Orie...IJTET Journal
Abstract — A palmprint identification system is a relatively most promising physiological biometric approach to identify the person. The numbers of palmprint recognition based biometric system have been successfully applied for real world access to control applications. A typical palmprint identification system identifies a query palmprint and matching it with the template stored in the database and comparing the similarity score with a pre-defined threshold. The Consistency Orientation Pattern (COP) hashing method is implemented in this work to enforce the fast search and to obtain the accurate result. Orientation pattern (OP) is defined as a collection of orientation features at arbitrary positions. The principal palm line is a kind of evident and stable features in palmprint images, and the orientation features in this region are expected to be more consistent than others. Using the orientation and response features extracted by steerable filter and gives an analysis on the consistency of orientation features, and then introduces a method to construct COP using the consistent features. Those features can be used as the indexes to the target template. Because the COP is very stable across the samples of the same subject, the COP hashing method can find the target template quickly. This method can lead to early termination of the searching process.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
A novel ensemble modeling for intrusion detection system IJECEIAES
Vast increase in data through internet services has made computer systems more vulnerable and difficult to protect from malicious attacks. Intrusion detection systems (IDSs) must be more potent in monitoring intrusions. Therefore an effectual Intrusion Detection system architecture is built which employs a facile classification model and generates low false alarm rates and high accuracy. Noticeably, IDS endure enormous amounts of data traffic that contain redundant and irrelevant features, which affect the performance of the IDS negatively. Despite good feature selection approaches leads to a reduction of unrelated and redundant features and attain better classification accuracy in IDS. This paper proposes a novel ensemble model for IDS based on two algorithms Fuzzy Ensemble Feature selection (FEFS) and Fusion of Multiple Classifier (FMC). FEFS is a unification of five feature scores. These scores are obtained by using feature-class distance functions. Aggregation is done using fuzzy union operation. On the other hand, the FMC is the fusion of three classifiers. It works based on Ensemble decisive function. Experiments were made on KDD cup 99 data set have shown that our proposed system works superior to well-known methods such as Support Vector Machines (SVMs), K-Nearest Neighbor (KNN) and Artificial Neural Networks (ANNs). Our examinations ensured clearly the prominence of using ensemble methodology for modeling IDSs, and hence our system is robust and efficient.
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.
Security remains to be an important aspect in the current age that is characterized with heavy internet usage. People as well as organizations are moving away from ancient authentication schemes like passwords to biometric authentication schemes as they provide better confidentiality and integrity of authentication information. Although biometrics are unique to an individual, they are still susceptible to attacks thus the need to secure them. Several techniques such as encryption, steganography, have been proposed with aim of achieving the security need brought about their use. This paper reviewed some proposed models for biometric template security and their limitation as well as provide recommendation to address some of the limitations outlined.
Biometrics was developed with the aim of improving the overall security level in all society contexts. A biometric system describes a set of techniques to analyze certain individual's biometric features, store and then using those patterns to identify or verify the identity of a person. The palmprint contains not only principal curves and wrinkles but also rich texture and miniscule points, so the palmprint identification is able to achieve a high accuracy because of available rich information in palmprint. Various palmprint identification methods, such as coding based methods and principal curve methods have been proposed in past decades. In addition to these methods, subspace based methods can also perform well for palmprint identification. Combining the left and right palmprint images to perform multibiometrics is easy to implement and can obtain better results.
Multimodal biometrics can provide higher identification accuracy than single or unimodal biometrics, so it is more suitable for some real-world personal identification applications that need high-standard security. A onetime password is included for higher security and accuracy.
One time passwords generally expire after using once. They are generated for using it within a certain time period after which it is useless. These passwords are set as a secondary security measure for the primary palmprint recognition.
Authentication Schemes for Session Passwords using Color and ImagesIJNSA Journal
Textual passwords are the most common method used for authentication. But textual passwords are vulnerable to eves dropping, dictionary attacks, social engineering and shoulder surfing. Graphical passwords are introduced as alternative techniques to textual passwords. Most of the graphical schemes are vulnerable to shoulder surfing. To address this problem, text can be combined with images or colors to generate session passwords for authentication. Session passwords can be used only once and every time a new password is generated. In this paper, two techniques are proposed to generate session passwords using text and colors which are resistant to shoulder surfing. These methods are suitable for Personal Digital Assistants.
Multibiometric Secure Index Value Code Generation for Authentication and Retr...ijsrd.com
The use of multiple biometric sources for human recognition, referred to as multibiometrics, mitigates some of the limitations of unimodal biometric systems by increasing recognition accuracy, improving population coverage, imparting fault-tolerance, and enhancing security. In a biometric identification system, the identity corresponding to the input data (probe) is typically determined by comparing it against the templates of all identities in a database (gallery). An alternative e approach is to limit the number of identities against which matching is performed based on criteria that are fast to evaluate. We propose a method for generating fixed-length codes for indexing biometric databases. An index code is constructed by computing match scores between a biometric image and a fixed set of reference images. Candidate identities are retrieved based on the similarity between the index code of the probe image and those of the identities in the database. The number of multibiometric systems deployed on a national scale is increasing and the sizes of the underlying databases are growing. These databases are used extensively, thereby requiring efficient ways for searching and retrieving relevant identities. Searching a biometric database for an identity is usually done by comparing the probe image against every enrolled identity in the database and generating a ranked list of candidate identities. Depending on the nature of the matching algorithm, the matching speed in some systems can be slow. The proposed technique can be easily extended to retrieve pertinent identities from multimodal databases. Experiments on a chimeric face and fingerprint bimodal database resulted in an 84% average reduction in the search space at a hit rate of 100%. These results suggest that the proposed indexing scheme has the potential to substantially reduce the response time without compromising the accuracy of identification. New representation schemes that allow for faster search and, therefore, shorter response time are needed.
Fingerprints are imprints formed by friction
ridges of the skin and thumbs. They have long been used for
identification because of their immutability and individuality.
Immutability refers to the permanent and unchanging character
of the pattern on each finger. Individuality refers to the
uniqueness of ridge details across individuals; the probability
that two fingerprints are alike is about 1 in 1.9x1015. In despite of
this improvement which is adopted by the Federal Bureau of
Investigation (FBI), the fact still is “The larger the fingerprint
files became, the harder it was to identify somebody from their
fingerprints alone. Moreover, the fingerprint requires one of the
largest data templates in the biometric field”. The finger data
template can range anywhere from several hundred bytes to over
1,000 bytes depending upon the level of security that is required
and the method that is used to scan one's fingerprint. For these
reasons this work is motivated to present another way to tackle
the problem that is relies on the properties of Vector
Quantization coding algorithm.
A Simple Segmentation Approach for Unconstrained Cursive Handwritten Words in...CSCJournals
This paper presents a new, simple and fast approach for character segmentation of unconstrained handwritten words. The developed segmentation algorithm over-segments in some cases due to the inherent nature of the cursive words. However the over segmentation is minimum. To increase the efficiency of the algorithm an Artificial Neural Network is trained with significant amount of valid segmentation points for cursive words manually. Trained neural network extracts incorrect segmented points efficiently with high speed. For fair comparison benchmark database IAM is used. The experimental results are encouraging.
An offline signature verification using pixels intensity levelsSalam Shah
Offline signature recognition has great importance in our day to day activities. Researchers are trying to use them as biometric identification in various areas like banks, security systems and for other identification purposes. Fingerprints, iris, thumb impression and face detection based biometrics are successfully used for identification of individuals because of their static nature. However, people’s signatures show variability that makes it difficult to recognize the original signatures correctly and to use them as biometrics. The handwritten signatures have importance in banks for cheque, credit card processing, legal and financial transactions, and the signatures are the main target of fraudulence. To deal with complex signatures, there should be a robust signature verification method in places such as banks that can correctly classify the signatures into genuine or forgery to avoid financial frauds. This paper, presents a pixels intensity level based offline signature verification model for the correct classification of signatures. To achieve the target, three statistical classifiers; Decision Tree (J48), probability based Naïve Bayes (NB tree) and Euclidean distance based k-Nearest Neighbor (IBk), are used.
For comparison of the accuracy rates of offline signatures with online signatures, three classifiers were applied on online signature database and achieved a 99.90% accuracy rate with decision tree (J48), 99.82% with Naïve Bayes Tree and 98.11% with K-Nearest Neighbor (with 10 fold cross validation). The results of offline signatures were 64.97% accuracy rate with decision tree (J48), 76.16% with Naïve Bayes Tree and 91.91% with k-Nearest Neighbor (IBk) (without forgeries). The accuracy rate dropped with the inclusion of forgery signatures as, 55.63% accuracy rate with decision tree (J48), 67.02% with Naïve Bayes Tree and 88.12% (with forgeries).
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.
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.
A Survey of Security of Multimodal Biometric SystemsIJERA Editor
A biometric system is essentially a pattern recognition system being used in adversarial environment. Since,
biometric system like any conventional security system is exposed to malicious adversaries, who can manipulate
data to make the system ineffective by compromising its integrity. Current theory and design methods of
biometric systems do not take into account the vulnerability to such adversary attacks. Therefore, evaluation of
classical design methods is an open problem to investigate whether they lead to design secure systems. In order
to make biometric systems secure it is necessary to understand and evaluate the threats and to thus develop
effective countermeasures and robust system designs, both technical and procedural, if necessary. Accordingly,
the extension of theory and design methods of biometric systems is mandatory to safeguard the security and
reliability of biometric systems in adversarial environments.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
An Indexing Technique Based on Feature Level Fusion of Fingerprint FeaturesIDES Editor
Personal identification system based on pass word
and other entities are ineffective. Nowadays biometric based
systems are used for human identification in almost many
real time applications. The current state-of-art biometric
identification focuses on accuracy and hence a good
performance result in terms of response time on small scale
database is achieved. But in today’s real life scenario biometric
database are huge and without any intelligent scheme the
response time should be high, but the existing algorithms
requires an exhaustive search on the database which increases
proportionally when the size of the database grows. This paper
addresses the problem of biometric indexing in the context of
fingerprint. Indexing is a technique to reduce the number of
candidate identities to be considered by the identification
algorithm. The fingerprint indexing methodology projected
in this work is based on a combination of Level 1, Level 2 and
Level-3 fingerprint features. The result shows the fusion of
level 1, level 2 and level 3 features gives better performance
and good indexing rate than with any one level of fingerprint
feature.
Analysis of the Iriscode Bioencoding SchemeCSCJournals
Cancelable biometrics is a technique used to enhance security and user privacy. These schemes are employed to generate multiple revocable data from the original biometric template. In this paper, the security of binary template transformations is evaluated, through a new transformation for iris templates, called bioencoding scheme. This transformation and its security is analyzed, using Boolean functions and non linear Boolean systems. A general discussion on binary template transformations is finally proposed.
A Fast and Accurate Palmprint Identification System based on Consistency Orie...IJTET Journal
Abstract — A palmprint identification system is a relatively most promising physiological biometric approach to identify the person. The numbers of palmprint recognition based biometric system have been successfully applied for real world access to control applications. A typical palmprint identification system identifies a query palmprint and matching it with the template stored in the database and comparing the similarity score with a pre-defined threshold. The Consistency Orientation Pattern (COP) hashing method is implemented in this work to enforce the fast search and to obtain the accurate result. Orientation pattern (OP) is defined as a collection of orientation features at arbitrary positions. The principal palm line is a kind of evident and stable features in palmprint images, and the orientation features in this region are expected to be more consistent than others. Using the orientation and response features extracted by steerable filter and gives an analysis on the consistency of orientation features, and then introduces a method to construct COP using the consistent features. Those features can be used as the indexes to the target template. Because the COP is very stable across the samples of the same subject, the COP hashing method can find the target template quickly. This method can lead to early termination of the searching process.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
A novel ensemble modeling for intrusion detection system IJECEIAES
Vast increase in data through internet services has made computer systems more vulnerable and difficult to protect from malicious attacks. Intrusion detection systems (IDSs) must be more potent in monitoring intrusions. Therefore an effectual Intrusion Detection system architecture is built which employs a facile classification model and generates low false alarm rates and high accuracy. Noticeably, IDS endure enormous amounts of data traffic that contain redundant and irrelevant features, which affect the performance of the IDS negatively. Despite good feature selection approaches leads to a reduction of unrelated and redundant features and attain better classification accuracy in IDS. This paper proposes a novel ensemble model for IDS based on two algorithms Fuzzy Ensemble Feature selection (FEFS) and Fusion of Multiple Classifier (FMC). FEFS is a unification of five feature scores. These scores are obtained by using feature-class distance functions. Aggregation is done using fuzzy union operation. On the other hand, the FMC is the fusion of three classifiers. It works based on Ensemble decisive function. Experiments were made on KDD cup 99 data set have shown that our proposed system works superior to well-known methods such as Support Vector Machines (SVMs), K-Nearest Neighbor (KNN) and Artificial Neural Networks (ANNs). Our examinations ensured clearly the prominence of using ensemble methodology for modeling IDSs, and hence our system is robust and efficient.
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.
Security remains to be an important aspect in the current age that is characterized with heavy internet usage. People as well as organizations are moving away from ancient authentication schemes like passwords to biometric authentication schemes as they provide better confidentiality and integrity of authentication information. Although biometrics are unique to an individual, they are still susceptible to attacks thus the need to secure them. Several techniques such as encryption, steganography, have been proposed with aim of achieving the security need brought about their use. This paper reviewed some proposed models for biometric template security and their limitation as well as provide recommendation to address some of the limitations outlined.
Biometrics was developed with the aim of improving the overall security level in all society contexts. A biometric system describes a set of techniques to analyze certain individual's biometric features, store and then using those patterns to identify or verify the identity of a person. The palmprint contains not only principal curves and wrinkles but also rich texture and miniscule points, so the palmprint identification is able to achieve a high accuracy because of available rich information in palmprint. Various palmprint identification methods, such as coding based methods and principal curve methods have been proposed in past decades. In addition to these methods, subspace based methods can also perform well for palmprint identification. Combining the left and right palmprint images to perform multibiometrics is easy to implement and can obtain better results.
Multimodal biometrics can provide higher identification accuracy than single or unimodal biometrics, so it is more suitable for some real-world personal identification applications that need high-standard security. A onetime password is included for higher security and accuracy.
One time passwords generally expire after using once. They are generated for using it within a certain time period after which it is useless. These passwords are set as a secondary security measure for the primary palmprint recognition.
Authentication Schemes for Session Passwords using Color and ImagesIJNSA Journal
Textual passwords are the most common method used for authentication. But textual passwords are vulnerable to eves dropping, dictionary attacks, social engineering and shoulder surfing. Graphical passwords are introduced as alternative techniques to textual passwords. Most of the graphical schemes are vulnerable to shoulder surfing. To address this problem, text can be combined with images or colors to generate session passwords for authentication. Session passwords can be used only once and every time a new password is generated. In this paper, two techniques are proposed to generate session passwords using text and colors which are resistant to shoulder surfing. These methods are suitable for Personal Digital Assistants.
Multibiometric Secure Index Value Code Generation for Authentication and Retr...ijsrd.com
The use of multiple biometric sources for human recognition, referred to as multibiometrics, mitigates some of the limitations of unimodal biometric systems by increasing recognition accuracy, improving population coverage, imparting fault-tolerance, and enhancing security. In a biometric identification system, the identity corresponding to the input data (probe) is typically determined by comparing it against the templates of all identities in a database (gallery). An alternative e approach is to limit the number of identities against which matching is performed based on criteria that are fast to evaluate. We propose a method for generating fixed-length codes for indexing biometric databases. An index code is constructed by computing match scores between a biometric image and a fixed set of reference images. Candidate identities are retrieved based on the similarity between the index code of the probe image and those of the identities in the database. The number of multibiometric systems deployed on a national scale is increasing and the sizes of the underlying databases are growing. These databases are used extensively, thereby requiring efficient ways for searching and retrieving relevant identities. Searching a biometric database for an identity is usually done by comparing the probe image against every enrolled identity in the database and generating a ranked list of candidate identities. Depending on the nature of the matching algorithm, the matching speed in some systems can be slow. The proposed technique can be easily extended to retrieve pertinent identities from multimodal databases. Experiments on a chimeric face and fingerprint bimodal database resulted in an 84% average reduction in the search space at a hit rate of 100%. These results suggest that the proposed indexing scheme has the potential to substantially reduce the response time without compromising the accuracy of identification. New representation schemes that allow for faster search and, therefore, shorter response time are needed.
Fingerprints are imprints formed by friction
ridges of the skin and thumbs. They have long been used for
identification because of their immutability and individuality.
Immutability refers to the permanent and unchanging character
of the pattern on each finger. Individuality refers to the
uniqueness of ridge details across individuals; the probability
that two fingerprints are alike is about 1 in 1.9x1015. In despite of
this improvement which is adopted by the Federal Bureau of
Investigation (FBI), the fact still is “The larger the fingerprint
files became, the harder it was to identify somebody from their
fingerprints alone. Moreover, the fingerprint requires one of the
largest data templates in the biometric field”. The finger data
template can range anywhere from several hundred bytes to over
1,000 bytes depending upon the level of security that is required
and the method that is used to scan one's fingerprint. For these
reasons this work is motivated to present another way to tackle
the problem that is relies on the properties of Vector
Quantization coding algorithm.
A Simple Segmentation Approach for Unconstrained Cursive Handwritten Words in...CSCJournals
This paper presents a new, simple and fast approach for character segmentation of unconstrained handwritten words. The developed segmentation algorithm over-segments in some cases due to the inherent nature of the cursive words. However the over segmentation is minimum. To increase the efficiency of the algorithm an Artificial Neural Network is trained with significant amount of valid segmentation points for cursive words manually. Trained neural network extracts incorrect segmented points efficiently with high speed. For fair comparison benchmark database IAM is used. The experimental results are encouraging.
Cada día tomamos decisiones, y la mayoría de nosotros no las pensamos con detenimiento. No seas un bombero, apagando los incendios de tus malas decisiones. Sé el arquitecto de tu destino.
A NOVEL APPROACH FOR GENERATING FACE TEMPLATE USING BDA cscpconf
In identity management system, commonly used biometric recognition system needs attention towards issue of biometric template protection as far as more reliable solution is concerned. In view of this biometric template protection algorithm should satisfy security, discriminability and
cancelability. As no single template protection method is capable of satisfying the basic requirements, a novel technique for face template generation and protection is proposed. The
novel approach is proposed to provide security and accuracy in new user enrollment as well as authentication process. This novel technique takes advantage of both the hybrid approach and the binary discriminant analysis algorithm. This algorithm is designed on the basis of random projection, binary discriminant analysis and fuzzy commitment scheme. Three publicly available benchmark face databases are used for evaluation. The proposed novel technique enhances the discriminability and recognition accuracy by 80% in terms of matching score of the face images and provides high security
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.
Information Security using Cryptography and Image Processingijsrd.com
Meaning of Information security is protecting information and the systems from unauthorized access, use, disclosure, disruption, modification, inspection, recording or destruction. Therefore it is necessary to apply effective encryption/decryption methods to achieve data security. The user only needs to remember the short password to retrieve the key. The password can be forgotten and stolen. As Biometrics based authentication systems confirm an individual's identity based on the physiological and/or behavioral characteristics of the individual. It has advantages over password based methods. Biometrics based method provides direct link between the service and actual user. With biometrics, there is nothing to lose or forget, and it is relatively difficult to manipulate. Biometrics and cryptography are the two most prominent solutions for user authentication, data integrity preservation, and trustworthy verification. By combining biometrics with cryptography, high level of security can be achieved.
Comparison of convolutional neural network models for user’s facial recognitionIJECEIAES
This paper compares well-known convolutional neural networks (CNN) models for facial recognition. For this, it uses its database created from two registered users and an additional category of unknown persons. Eight different base models of convolutional architectures were compared by transfer of learning, and two additional proposed models called shallow CNN and shallow directed acyclic graph with CNN (DAG-CNN), which are architectures with little depth (six convolution layers). Within the tests with the database, the best results were obtained by the GoogLeNet and ResNet-101 models, managing to classify 100% of the images, even without confusing people outside the two users. However, in an additional real-time test, in which one of the users had his style changed, the models that showed the greatest robustness in this situation were the Inception and the ResNet-101, being able to maintain constant recognition. This demonstrated that the networks of greater depth manage to learn more detailed features of the users' faces, unlike those of shallower ones; their learning of features is more generalized. Declare the full term of an abbreviation/acronym when it is mentioned for the first time.
Biometrics, this presentation talks about the security using biometrics. Having a security using your constant and doesn't change over time it will be a big help for your security.
A Study of Approaches and Measures aimed at Securing Biometric Fingerprint Te...Editor IJCATR
The need for fool proof authentication procedures away from traditional authentication mechanisms like passwords, security PINS has led to the advent of biometric authentication in information systems. Biometric data extracted from physiological features of a person including but not limited to fingerprints, palm prints, face or retina for purpose of verification & identification is saved as biometric templates. The inception of biometrics in access control systems has not been without its own hitches & like other systems it has its fair share of challenges. Biometric fingerprints being the most mature of all biometric spheres are the most widely adopted biometric authentication systems. Biometric systems effectiveness lies on how secure they are at preventing inadvertent disclosure of biometric templates in an information system‟s archive. This however has not been the case as biometric templates have been fraudulently accessed to gain unauthorized access in identification and verification systems. In order to achieve strong and secure biometric systems, biometric systems developers need to build biometric systems that properly secure biometric templates. Several biometric template protection schemes and approaches have been proposed and used to safeguard stored biometric templates. Despite there being various biometric template protection schemes and approaches in existence, none of them has provided the most authentic, reliable, efficient and deterrent means to totally secure biometric fingerprint templates. This research sought to establish status of the current biometric template protection techniques and methods by conducting a survey and analyzing data gathered from a sample of seventy-eight (78) respondents. We will report these results and give our conclusion based on findings of the survey in this paper.
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.
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.
Ijaems apr-2016-1 Multibiometric Authentication System Processed by the Use o...INFOGAIN PUBLICATION
The present day authentication system is mostly uni-model i.e having only single authentication method which can be either finger print, iris , palm veins ,etc. Thus these models have to contend with a variety of problems such as absurd or unusual data, non-versatility; un authorized attempts, and huge amount of error rates. Some of these limitations can be reduced or stopped by the use of multimodal biometric systems that integrate the evidence presented by several sources of information. This paper converses a multi biometric based authentication system based on Fusion algorithm using a key. Our work mainly focuses on the fusion algorithm, i.e fusion of finger and palm print out of which the greatest features from the above two traits are taken into account. With minimum possible features the fusion of the both the traits is carried out. Then some key is generated for multi biometric authentication. By processing the test image of a person, the identity of the person is displayed with his/her own image. By the fusion algorithm, it is found that it has less computation time compared to the existing algorithms. By matching results, we validate and authenticate the particular individual.
Access Policy Management For OSN Using Network RelationshipsIJMTST Journal
In the online social networks (OSN) users and resources are interconnected via various types of
relationships. The relationships are one-to-one, one-to-many, many-to-one, and many-to-many like that. Now
a day’s online social networks plays crucial role to monitor and to control the access of the resources. In the
OSN, online provider should be enabled to specify which access permission can be granted in terms of
existing relationships. In this work we used user-to-user relationship based access control model. Access
control policies decide which permissions can be granted to the requested users based on their requests and
we are using two path checking algorithms namely DFS and BFS to determine the path existence between
users as well as the requested user is authenticated user or not.
Two level data security using steganography and 2 d cellular automataeSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
A Secure & Optimized Data Hiding Technique Using DWT With PSNR ValueIJERA Editor
Multimedia applications are becoming increasingly significant in modern world. The mushroom growth of multimedia data of these applications, particularly over the web has increased the demand for protection of copyright. Digital watermarking is much more acceptable as a solution to the problem of copyright protection and authentication of multimedia data while working in a networked environment. In this paper, a DWT based watermarking scheme is proposed. We have used Genetic Algorithm (GA) in order to make an optimum tradeoff between imperceptibility and robustness by choosing an optimum watermarking level for each coefficient of the cover image. In addition to the suitable watermarking strength, the selection of best block size is also necessary for superior perceptual shaping functions. To achieve this goal we have trained and used GA to pick the best block size to tailor the watermark in one of the coefficients of the DWT. The fitness function criterion for the genetic algorithm decision making is based on PSNR values
With the surge in modern research focus towards Pervasive Computing, lot of techniques and challenges
needs to be addressed so as to effectively create smart spaces and achieve miniaturization. In the process of
scaling down to compact devices, the real things to ponder upon are the Information Retrieval challenges.
In this work, we discuss the aspects of multimedia which makes information access challenging. An
Example Pattern Recognition scenario is presented and the mathematical techniques that can be used to
model uncertainty are also presented for developing a system that can sense, compute and communicate in
a way that can make human life easy with smart objects assisting from around his surroundings.
MULTIMODAL BIOMETRIC AUTHENTICATION: SECURED ENCRYPTION OF IRIS USING FINGERP...ijcisjournal
Securing data storage using biometrics is the current trend. Different physiological as well as behavioral biometrics like face, fingerprint, iris, Gait, voice etc.. is used in providing security to the data. The proposed work explains about the biometric encryption technology which will securely generate a digital key using two biometric modalities. Iris is encrypted using Fingerprint ID of 32-bit as the key in this work.
For encryption Blowfish algorithm is used and the encrypted template is stored in the database and one is given to the user. During the authentication time user input the template and the fingerprint. This template is then decrypted and verified with the original template taken from the database to check whether the user is genuine or an imposter. Hamming distance is used to measure the matching of the templates. CASIA Iris
database is used for experimentation and fingerprint images read through the R303 - fingerprint reader.
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2. 32
Computer Science & Information Technology (CS & IT)
An attack on a biometric system can occur because an individual wants to attain privileges that
another person has. The impostor, in this case, may forge biometric trait of genuine user in order
to gain the unauthorized access to systems such as person's bank account or to gain physical
access to a restricted region.
A benefit to sharing biometric trait may be the cause to attack the biometric systems. Someone,
for instance, can establish a new identity during enrollment using a synthetically generated
biometric trait. Thus, sharing the artificial biometric trait leads to sharing that fraudulent identity
with multiple people. To enhance the recognition performance as well as to provide the better
security, new system is to be proposed. The proposed system is designed
•
•
To enhance the discriminability of face template by using Binary discriminant analysis.
To provide the better security to binary template against smart attacks and brute force
attack.
2. EXISTING TEMPLATE PROTECTION SCHEME
Template Protection Scheme can be categorized into three main approaches: 1) the biometric
cryptosystem approach 2) the transform-based approach and 3) hybrid approach. Figure 1 shows
the categorization of template protection scheme. The basic idea of these approaches is that
instead of storing the original template, the transformed/encrypted template which is intended to
be more secure, is stored. In case the transformed/encrypted template is stolen or lost, it is
computationally hard to reconstruct the original template and to determine the original raw
biometric data simply from the transformed/encrypted template.
In the biometric cryptosystem approach, the error-correcting coding techniques are employed to
handle intra-class variations. Two popular techniques, namely fuzzy commitment scheme [7] and
fuzzy vault scheme [8], are discussed. The advantage of this approach is that, since the output is
an encrypted template, its security level is high. However, the error-correcting ability of these
schemes may not be strong enough to handle large intra-class variations such as face images
captured under different illuminations and poses. Also, this approach is not designed to be
revocable. Finally, the error-correcting coding techniques require input in certain format (e.g.,
binary strings or integer vectors with limited range), and it is hard to represent every biometric
template in this desired format. In the transform-based approach, a transformed template is
generated using a "one-way" transform and the matching is performed in the transformed domain.
The transform-based approach has a good cancelability (revocability) property, but the drawback
of this approach is the trade-off between performance and security of the transformed template.
The hybrid approach retains the advantages of both the transform- based approach and biometric
cryptosystem approach, and overcomes the limitations of individual approaches [9] [10].
Figure 1. Categorization of template protection scheme
3. Computer Science & Information Technology (CS & IT)
33
Some of the existing biometric template protection schemes provide security to binary template
and rest of the other enhances the discriminability of the template. The available biometric
cryptosystem and transformed based template protection schemes are not yet sufficiently mature
for large scale deployment; they do not meet the requirements of diversity, revocability, security
and high recognition performance. So in order to take the benefits of both approaches while
eliminating their limitations, a hybrid approach for face biometric was developed only for the
verification process but not for the new user enrollment process.
This limitation imposed to develop a new system to generate secure and discriminant face
template for new user enrollment process as well as for the verification system.
3. ARCHITECTURE OF PROPOSED SYSTEM
A Novel Technique to generate discriminant and secure binary face template by using binary
discriminating analysis is proposed. In this novel technique DP transform section from hybrid
approach will replace by binary discriminant analysis. It is expected that this will enhance the
discriminability of binary template. Finally, encryption algorithm is applied to generate secure
template using fuzzy commitment. Figure 2 shows architecture flow of proposed system. Two
stages (enrollment and authentication) of proposed system follow some steps which are explained
in following section.
Figure 2. Architecture flow of proposed system
3.1. Random projection
Random projection is a popular dimensionality reduction technique and has been successfully
applied in many computer vision and pattern recognition applications. Recently, it has also been
employed as a cancelable transform for face biometric [9] [10]. The main purpose of the original
random projection is to project a set of vectors into a lower dimensional subspace while
preserving the Euclidean distances between vectors before and after the transformation, with a
certain probability. The idea was first developed by Johnson and Lindenstrauss.
4. 34
Computer Science & Information Technology (CS & IT)
It will preserve the structure of the data without introducing significant distortion. It will represent
faces in a random, low dimensional subspace. It uses random projection matrices to project data
into low dimensional spaces. The matrix will be calculated using the following steps.
Step 1: Set each entry of the matrix to an independent and identically distributed (i.i.d.) value.
Step 2: Apply Gram-Schmidt algorithm to orthogonalize the rows of the matrix.
Step 3: To preserve the similarities in the low dimensional space normalize the rows of the matrix
to unit length.
3.2. Binary discriminant analysis
BDA algorithm requires minimized within class variance and maximized between class variance.
Perceptron method is used to find the optimal linear discriminant function. In the training phase,
genuine label for each class is required by the perceptron method. The perceptron minimizes the
distance between binary templates to the corresponding target binary template. This binary
template is used as the reference for each class. This method is only used for minimization of
within-class variance not for the between-class variance. To maximize the discriminability of the
template between-class variance should be maximized.
But direct maximizing is difficult in binary space and conflicts with minimizing process of
within-class variance. If the transformed binary templates in the same class are close to each other
and binary templates of different class are far away then by using this new method it is possible to
maximize discriminability of the binary template. The perceptron is used to find the optimal
LDFs so that the output binary templates are closed to corresponding target binary template.
Therefore within-class variance of binary template is minimized. Now, to maximize the betweenclass variance of the transform binary templates, target binary templates are randomly choose
from the codeword of BCH codes having length, dimension with minimum distance. BCH
codeword is randomly selected as the reference binary templates.
3.3. Fuzzy commitment
Fuzzy commitment scheme is applied on binary face template to provide the better security.
Encryption algorithm is applied to encrypt the binary template and store binary template into
database or to match with stored template.
4. RESULTS
This section discusses the results related discriminability and accuracy, computation time and
security analysis for the hybrid approach and novel approach.
4.1. Discriminability and accuracy
Hybrid approach and novel approach generate there different face templates, namely cancelable
template, binary template and secure template. In this section we evaluated the discriminability of
each template in terms of the genuine and imposter histograms.
5. Computer Science & Information Technology (CS & IT)
35
Figure 3. Histogram of cancelable template
Figure 4. Histogram of binary template
In Particular, we illustrate that the cancelable template discriminability is enhanced in the binary
template and matching score of the templates at each stage of hybrid and novel approach. Table
number 1 and 2 shows the matching score of templates at each stage in hybrid as well as novel
approach respectively. Figure 3 and 4 show histogram of cancelable template and binary template
for imposter and genuine user. Matching score of feature vector is greater than cancelable
template score that means the accuracy and discriminability is degraded in random projection
stage. The degraded accuracy and discriminability is enhanced by the binary template generated
using DP transform. Figure 5 shows the graphical representation of this result.
Figure 5. Matching score for hybrid approach
Matching score of feature vector (from Table 2) is greater than cancelable template score that
means the accuracy and discriminability is degraded in random projection stage. The degraded
accuracy and discriminability is enhanced by the binary template generated using binary
discriminant analysis. Figure 6 shows the graphical representation of this result.
6. 36
Computer Science & Information Technology (CS & IT)
Figure 6. Matching Score for Novel Approach
Table 1 Matching score of five images for hybrid approach
Images
Feature Vector
Image1
Image2
Image3
Image4
Image5
Cancelable
Template
180
178
175
174
182
184
187
183
189
195
Binary Template Using
DP Transform
222
218
225
215
205
Hybrid
Algorithm
198
196
195
201
210
Table 2 Matching score of five images for a novel approach
Images
Feature Vector
Image1
Image2
Image3
Image4
Image5
184
187
183
189
195
Cancelable
Template
182
170
168
174
182
Binary Template
Using BDA
226
220
219
221
214
Novel
Algorithm
193
197
195
203
202
Table 3 Matching score for five images for DP transform and binary discriminant analysis
Images
Image1
Image2
Image3
Image4
Image5
Binary Template Using
DP Transform
222
218
225
215
205
Binary Template
Using BDA
226
220
219
221
214
The table no. 3 shows the matching score for five images for DP transform and binary
discriminant analysis. The comparison of both the stages shows matching score for templates
generated by binary discriminant analysis is greater than DP transform. This matching score is up
to 80%. Figure 7 shows the graphical representation of this result.
7. Computer Science & Information Technology (CS & IT)
37
Figure 7. Comparison of matching score for novel approach and hybrid approach
4.2. Computation time
All the experiments are performed on typical personal computer having configuration as core i5
processor and both algorithms (hybrid and novel approach) are implemented using NetBeans
IDE. Table no 4 and 5 shows the computation time for one class training process and the time for
one input query template respectively. This time includes random projection, DP Transform and
fuzzy commitment for hybrid approach as well for novel approach that includes random
projection, BDA process and fuzzy commitment. Here we considered 10 sample images from
standard database FERET, FRGC database and other data sets. Analysis of computation time of
enrollment and verification stage is shown in Figure 8 and 9 respectively.
Table 4 Computation time for verification process for ten images (time in seconds)
Data Set
For Hybrid Approach
For Novel Approach
FERET
FRGC
CMUPIE
OTHER
348
366
342
372.6
335
370
340
365
Table 5 Computation time for verification process for single image (time in seconds)
Data Set
For Hybrid Approach
For Novel Approach
FERET
FRGC
CMUPIE
OTHER
44
40
41
43
48
39
43
43
8. 38
Computer Science & Information Technology (CS & IT)
Figure 8. Analysis of computation time of enrollment stage
Figure 9. Analysis of computation time of verification stage
4.3. Security analysis
This section analyzes the security strength of the hybrid approach, a novel approach at each stage
of these algorithms. Two types of potential attacks, namely brute force and "smart" attacks are
considered. Brute force attack tries to guess the biometric data without any information, such as
matching score, to attack the system. The smart attack viz. affine transformation attack is
considered. It can be seen that the security strength of random projection and DP transform are
low and medium respectively in smart attack, but full hybrid algorithm is secure against this
attack.
In case of novel approach, it can be observed that the security strength of random projection and
BDA process are low and medium respectively, but complete novel algorithm is highly secure.
Hybrid approach and a novel approach are highly secure against brute force attack. In this case
attacker requires number of trial of all possible combination of all alphanumerical character set.
Here we have assumed character set of length 40 (including alphabets, numerical characters and
other special characters). The attacker may try to guess the templates of each step.
4.3.1. Random projection
In hybrid algorithm, T1 is template generated at random projection step having length Kc (Kc is
3772). Therefore, it will cost the attacker 2kc-1 operations to guess it. So this step is secure against
brute force attack.
4.3.2. DP transform
In this step, T2 is template generated at DP Transform having Kc distinguishing points and there
are totally 2kc combinations. Therefore, it will cost the attacker 2kc combinations to guess it. With
known distinguishing points it is hard to implement brute force attack against this step. So this
9. Computer Science & Information Technology (CS & IT)
39
step is secured against brute force attack. For the affine transformation attack, the real valued
template is very hard to be reconstructed from a binary template. Moreover matching score,
distinguishing points are not useful in this attack. Therefore, the DP transform is secured against
an affine transformation attack.
4.3.3. Binary discriminant analysis
In this step, T2 is template generated at BDA having Kc length and there are totally 2kc-1
combinations. Therefore, it will cost the attacker 2kc-1 combinations to guess it. So this step is
secure against brute force attack.
For the affine transformation attack, the real valued template is very had to be reconstructed from
a binary template. Moreover matching score is not useful in this attack. Therefore, the BDA
process is very secure against an affine transformation attack.
4.3.4. Fuzzy commitment scheme
B1 is template generated in this step having length Kc (Kc is 11340). Therefore, it will cost the
attacker 2kc-1 operations to guess it. So this step is highly secured against brute force attack. Fuzzy
Commitment Scheme performs matching operation between two hashed data. Because of
property of the hash function, the distance between these two hash data will not reveal distance
information. Therefore matching score is useless for affine transformation attack. Therefore, the
Fuzzy Commitment Scheme is secured against an affine transformation attack.
4.3.5. Full algorithm
Since the three steps are integrated together to form hybrid algorithm, the attacker cannot get the
output from these steps. Thus this algorithm does not reveal any information to attackers. In this
algorithm, we have encrypted binary template which cannot be easily accessible to the attackers.
The output of each step is combined into one string in specific sequence is arranged. After this,
the resultant string is converted into bytes which reduce the string length to store into database.
Finally, this converted template is stored or matched with stored database template. Recovery of
this stored template from brute force attack requires 2kc-1 (Kc is 6810) operations. Therefore,
binary template recovery is not possible using affine transformation attack. So this full algorithm
has high security strength against both attacks.
As the three steps are integrated together to form novel algorithm, the attacker cannot get the
output from these steps. Thus this algorithm does not reveal any information to attackers. In this
algorithm, we have encrypted binary template which cannot be easily accessible to the attackers.
The output of each step is combined into one string in specific sequence is arranged. After this,
this string is converted into bytes which reduce the string length to store into database. Finally,
this converted template is stored or matched with stored database template. Recovery of this
stored template from brute force attack requires 2kc-1 (Kc is 6800) operations.
Table 6 Security strength of the hybrid algorithm as well as each step in the full algorithm
Attack
Brute Force
Affine
Transformation
Random
Projection
High
Low
DP
transform
High
High
Fuzzy
Commitment
High
High
Full
Algorithm
High
High
10. 40
Computer Science & Information Technology (CS & IT)
Table 7 Security strength of the novel algorithm as well as each step in the full algorithm
Attack
Brute Force
Affine
Transformation
Random
Projection
High
Low
BDA
High
High
Fuzzy
Commitment
High
High
Full Algorithm
High
High
Therefore, binary template recovery is not possible using affine transformation attack. So this full
algorithm has high security strength against both attacks. Table no. 6 and 7 show the security
strength of hybrid algorithm and a novel approach at each stage.
4. CONCLUSIONS
A novel approach using BDA was designed, implemented and rigorously tested on the standard
benchmark FERET, FRGC and CMU PIE database. Before developing this novel approach,
hybrid approach was also tested on the similar database. The results of both the methods viz.
novel approach and hybrid approach are compared in terms of discriminabilty and security. The
proposed novel technique enhances the discriminability and recognition accuracy by 80% in
terms of matching score of the face images and provides high security. This clearly indicates the
performance improvement in novel approach against hybrid approach.
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