scholarly journals A New Scheme for the Polynomial Based Biometric Cryptosystems

2014 ◽  
Vol 2014 ◽  
pp. 1-13 ◽  
Author(s):  
Amioy Kumar ◽  
M. Hanmandlu ◽  
Hari M. Gupta
Keyword(s):  
Feature Extraction ◽  
Gabor Filter ◽  
Error Rates ◽  
Experimental Results ◽  
Feature Points ◽  
Secret Key ◽  
Biometric Data ◽  
Fuzzy Vault ◽  
Palm Vein ◽  
Ordered Pairs

This paper presents a new scheme for the fuzzy vault based biometric cryptosystems which explore the feasibility of a polynomial based vault for the biometric traits like iris, palm, vein, and so forth. Gabor filter is used for the feature extraction from the biometric data and the extracted feature points are transformed into Eigen spaces using Karhunen Loeve (K-L) transform. A polynomial obtained from the secret key is used to generate projections from the transformed features and the randomly generated points, known as chaff points. The points and their corresponding projections form the ordered pairs. The union of the ordered pairs from the features and the chaff points creates a fuzzy vault. At the time of decoding, matching scores are computed by comparing the stored and the claimed biometric traits, which are further tested against a predefined threshold. The number of matched scores should be greater than a tolerance value for the successful decoding of the vault. The threshold and the tolerance value are learned from the transformed features at the encoding stage and chosen according to the tradeoff in the error rates. The proposed scheme is tested on a variety of biometric databases and error rates obtained from the experimental results confirm the utility of the new scheme.

scholarly journals Finger Knuckle Print Recognition using MMDA with Fuzzy Vault

2020 ◽  
Vol 17 (4) ◽  
pp. 554-561
Author(s):  
MuthuKumar Arunachalamand ◽  
Kavipriya Amuthan
Keyword(s):  
Gabor Filter ◽  
Personal Identification ◽  
Random Numbers ◽  
Secret Key ◽  
Fuzzy Vault ◽  
Eigen Value ◽  
Novel Method ◽  
Palm Print ◽  
Verification Process ◽  
Log Gabor

Currently frequent biometric scientific research such as with biometric applications like face, iris, voice, hand-based biometrics traits like palm print and fingerprint technique are utilized for spotting out the persons. These specific biometrics habits have their own improvement and weakness so that no particular biometrics can adequately opt for all terms like the accuracy and cost of all applications. In recent times, in addition, to distinct with the hand-based biometrics technique, Finger Knuckle Print (FKP) has been appealed to boom the attention among biometric researchers. The image template pattern formation of FKP embraces the report that is suitable for spotting the uniqueness of individuality. This FKP trait observes a person based on the knuckle print and the framework in the outer finger surface. This FKP feature determines the line anatomy and finger structures which are well established and persistent throughout the life of an individual. In this paper, a novel method for personal identification will be introduced, along with that data to be stored in a secure way has also been proposed. The authentication process includes the transformation of features using 2D Log Gabor filter and Eigen value representation of Multi-Manifold Discriminant Analysis (MMDA) of FKP. Finally, these features are grouped using k-means clustering for both identification and verification process. This proposed system is initialized based on the FKP framework without a template based on the fuzzy vault. The key idea of fuzzy vault storing is utilized to safeguard the secret key in the existence of random numbers as chaff pints

scholarly journals A Comparative Analysis of Different Feature Extraction Techniques for Palm-print Images

2020 ◽  
Author(s):  
Prateek Pratyasha ◽  
Bharati Swarnkar ◽  
Aditya Prasad Padhy
Keyword(s):  
Feature Extraction ◽  
Cyber Security ◽  
Gabor Filter ◽  
Individual Recognition ◽  
Research Work ◽  
Error Rates ◽  
Automatic Identification ◽  
Gaussian Filter ◽  
Extraction Techniques ◽  
Palm Print

AbstractIn this advanced decade, automatic identification of individuals is a significant achievement due to the high demand of security system. Hence, individual recognition using biometrics data is leading in the field of image processing. Although biometrics data analysis using thumb impression and finger-prints are very popular since many years, sometimes it leads to false acceptance and rejection if any physical change occurs in the finger ridges. There may be a high risk of hacking the biometrics data which is now a big challenge for cyber security employees. This paper captures the palm-print images of individuals as referred biometrics data for individual recognition. The research work is based on one of the prior issue that is feature extraction to extract the features of palm-print image such as principle lines, textures, ridges and pores etc. For this, some of the feature extraction techniques such as Derivatives of Gaussian filter (DoG), Discrete Cosine Transform (DCT), Fast Fourier Transform (FFT) and competitive coding. Two types of filters: Gaussian Filter and Gabor filter are combined with each of the feature extraction scheme for the matching of sampled image with testing image. In the result, the error rates of each of the feature extraction algorithms are compared to recognize the palm image of two different individuals.

Score Level Fusion of Palmprint, Face and Iris Using Adaptive PSO

2019 ◽  
Vol 10 (3) ◽  
pp. 175-194 ◽  
Author(s):  
Aldjia Boucetta ◽  
Kamal Eddine Melkemi
Keyword(s):  
Degrees Of Freedom ◽  
Gabor Filter ◽  
Fitness Function ◽  
Recognition Rate ◽  
Error Rates ◽  
Experimental Results ◽  
Reduction Techniques ◽  
Adaptive Pso ◽  
Dimensionality Reduction Techniques ◽  
Biometric Fusion

Systems that use unimodal biometrics often suffer from various drawbacks such as noise in sensed data, variations that are due to intra class, nonuniversality, spoof attacks, restricted degrees of freedom and high error rates. These limitations can be solved effectively by combining two or more biometric modalities. In this article, a multimodal biometric fusion system is presented that combines palmprint, face and iris traits. The biometric fusion is performed at the score level in order to improve the accuracy of the system. Scores obtained from the three classifiers are fused using adaptive particle swarm optimization (PSO). The PSO use new multi objective fitness function. This function has two objectives, improve the recognition rate and reduce the total equal error rates. The experimental results of the proposed method achieve a recognition accuracy of 100%, with EER of 0.00%, using Gabor filter combined with dimensionality reduction techniques PCA, LDA and KFA. Experimental results show that multimodal biometric systems are much more accurate than the unimodal counterparts.

AUTHENTICATION OF DIGITAL DOCUMENTS USING SECRET KEY BIOMETRIC WATERMARKING

2012 ◽  
pp. 5-11
Author(s):  
V. ANITHA ◽  
R.LEELA VELUSAMY
Keyword(s):  
Experimental Results ◽  
Direct Relation ◽  
Secret Key ◽  
Biometric Data ◽  
The Real ◽  
Digital Documents ◽  
Digital Document ◽  
Modern Era

Digital documents play a major role in modern era. They are easy to generate, modify and manage. The easy modifiable property of digital document makes it more vulnerable to forgery. It can be easily tampered or forged. So the challenge is to produce digital documents that are highly resistant to forgery and reliably confirms the real owner of the document. This can be resolved by biometric watermarking which make a direct relation between the document and its owner. A new biometric watermarking technique with secret key is proposed to digitize the authoritative documents issued by government / other organizations as a part of UID / Aadhar card project of India using biometric watermarking. Biometric code is generated from the biometric data collected from the owner of the document. The biometric code is watermarked in the document with a secret key to generate a biometric watermarked document that authenticates the real owner. Dewatermarking the document with the same key yields the biometric code that can be used for authentication of the document. If the document is tampered in any way it will be indicated in the extracted watermark. Experimental results show that 100% accuracy is obtained in authenticating the genuine documents.

Tensor Linear Discriminant Analysis

2011 ◽  
pp. 172-201
Author(s):  
David Zhang ◽  
Fengxi Song ◽  
Yong Xu ◽  
Zhizhen Liang
Keyword(s):  
Feature Extraction ◽  
Discriminant Analysis ◽  
Linear Discriminant Analysis ◽  
Computational Efficiency ◽  
Curse Of Dimensionality ◽  
Experimental Results ◽  
Singularity Problem ◽  
Biometric Data ◽  
Linear Discriminant ◽  
Important Method

Linear discriminant analysis is a very effective and important method for feature extraction. In general, image matrices are often transformed into vectors prior to feature extraction, which results in the curse of dimensionality when the dimensions of matrices are huge. In this chapter, classical LDA and its several variants are introduced. In some sense, the variants of LDA can avoid the singularity problem and achieve computational efficiency. Experimental results on biometric data show the usefulness of LDA and its variants in some cases.

scholarly journals Polynomial Based Fuzzy Vault Technique for Template Security in Fingerprint Biometrics

2020 ◽  
Vol 17 (6) ◽  
pp. 926-934
Author(s):  
Reza Mehmood ◽  
Arvind Selwal
Keyword(s):  
Secret Key ◽  
Biometric System ◽  
Biometric Data ◽  
Security Breaches ◽  
Fuzzy Vault ◽  
Template Security ◽  
Biometric Template ◽  
Great Consideration ◽  
Template Protection ◽  
Identity Cards

In recent years the security breaches and fraud transactions are increasing day by day. So there is a necessity for highly secure authentication technologies. The security of an authentication system can be strengthened by using Biometric system rather than the traditional method of authentication like Identity Cards (ID) and password which can be stolen easily. A biometric system works on biometric traits and fingerprint has the maximum share in market for providing biometric authentication as it is reliable, consistent and easy to capture. Although the biometric system is used to provide security to many applications but it is susceptible to different types of assaults too. Among all the modules of the biometric system which needs security, biometric template protection has received great consideration in the past years from the research community due to sensitivity of the biometric data stored in the form of template. A number of methods have been devised for providing template protection. Fuzzy vault is one of the cryptosystem based method of template security. The aim of fuzzy vault technique is to protect the precarious data with the biometric template in a way that only certified user can access the secret by providing valid biometric. In this paper, a modified version of fuzzy vault is presented to increase the level of security to the template and the secret key. The polynomial whose coefficients represent the key is transformed using an integral operator to hide the key where the key can no longer be derived if the polynomial is known to the attacker. The proposed fuzzy vault scheme also prevents the system from stolen key inversion attack. The results are achieved in terms of False Accept Rate (FAR), False Reject Rate (FRR), Genuine Acceptance Rate (GAR) by varying the degree of polynomial and number of biometric samples. It was calculated that for 40 users GAR was found to be 92%, 90%, 85% for degree of polynomial to be 3, 4 and 5 respectively. It was observed that increasing the degree of polynomial decreased the FAR rate, thus increasing the security

scholarly journals An Improved Fuzzy Vector Signature with Reusability

2020 ◽  
Vol 10 (20) ◽  
pp. 7141
Author(s):  
Ilhwan Lim ◽  
Minhye Seo ◽  
Dong Hoon Lee ◽  
Jong Hwan Park
Keyword(s):  
Sampling Method ◽  
Performance Comparison ◽  
Error Rates ◽  
Efficiency Improvement ◽  
Fuzzy Extractor ◽  
Authentication Protocols ◽  
Biometric Data ◽  
Single User ◽  
Helper Data ◽  
Fuzzy Vector

Fuzzy vector signature (FVS) is a new primitive where a fuzzy (biometric) data w is used to generate a verification key (VKw), and, later, a distinct fuzzy (biometric) data w′ (as well as a message) is used to generate a signature (σw′). The primary feature of FVS is that the signature (σw′) can be verified under the verification key (VKw) only if w is close to w′ in a certain predefined distance. Recently, Seo et al. proposed an FVS scheme that was constructed (loosely) using a subset-based sampling method to reduce the size of helper data. However, their construction fails to provide the reusability property that requires that no adversary gains the information on fuzzy (biometric) data even if multiple verification keys and relevant signatures of a single user, which are all generated with correlated fuzzy (biometric) data, are exposed to the adversary. In this paper, we propose an improved FVS scheme which is proven to be reusable with respect to arbitrary correlated fuzzy (biometric) inputs. Our efficiency improvement is achieved by strictly applying the subset-based sampling method used before to build a fuzzy extractor by Canetti et al. and by slightly modifying the structure of the verification key. Our FVS scheme can still tolerate sub-linear error rates of input sources and also reduce the signing cost of a user by about half of the original FVS scheme. Finally, we present authentication protocols based on fuzzy extractor and FVS scheme and give performance comparison between them in terms of computation and transmission costs.

scholarly journals Relative Total Variation Structure Analysis-Based Fusion Method for Hyperspectral and LiDAR Data Classification

2021 ◽  
Vol 13 (6) ◽  
pp. 1143
Author(s):  
Yinghui Quan ◽  
Yingping Tong ◽  
Wei Feng ◽  
Gabriel Dauphin ◽  
Wenjiang Huang ◽  
...  
Keyword(s):  
Feature Extraction ◽  
Total Variation ◽  
Structure Analysis ◽  
Hyperspectral Image ◽  
Gabor Filter ◽  
Heterogeneous Data ◽  
Lidar Data ◽  
Fusion Method ◽  
Wide Range ◽  
Relative Total Variation

The fusion of the hyperspectral image (HSI) and the light detecting and ranging (LiDAR) data has a wide range of applications. This paper proposes a novel feature fusion method for urban area classification, namely the relative total variation structure analysis (RTVSA), to combine various features derived from HSI and LiDAR data. In the feature extraction stage, a variety of high-performance methods including the extended multi-attribute profile, Gabor filter, and local binary pattern are used to extract the features of the input data. The relative total variation is then applied to remove useless texture information of the processed data. Finally, nonparametric weighted feature extraction is adopted to reduce the dimensions. Random forest and convolutional neural networks are utilized to evaluate the fusion images. Experiments conducted on two urban Houston University datasets (including Houston 2012 and the training portion of Houston 2017) demonstrate that the proposed method can extract the structural correlation from heterogeneous data, withstand a noise well, and improve the land cover classification accuracy.

scholarly journals Path-encoded high-dimensional quantum communication over a 2-km multicore fiber

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Beatrice Da Lio ◽  
Daniele Cozzolino ◽  
Nicola Biagi ◽  
Yunhong Ding ◽  
Karsten Rottwitt ◽  
...  
Keyword(s):  
Quantum Key Distribution ◽  
Quantum Communication ◽  
Error Rates ◽  
Quantum States ◽  
High Dimensional ◽  
Secret Key ◽  
System A ◽  
Reliable Transmission ◽  
Multicore Fiber ◽  
Interferometric Detection

AbstractQuantum key distribution (QKD) protocols based on high-dimensional quantum states have shown the route to increase the key rate generation while benefiting of enhanced error tolerance, thus overcoming the limitations of two-dimensional QKD protocols. Nonetheless, the reliable transmission through fiber links of high-dimensional quantum states remains an open challenge that must be addressed to boost their application. Here, we demonstrate the reliable transmission over a 2-km-long multicore fiber of path-encoded high-dimensional quantum states. Leveraging on a phase-locked loop system, a stable interferometric detection is guaranteed, allowing for low error rates and the generation of 6.3 Mbit/s of a secret key rate.

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