Biometric Cryptosystems Research Articles

A New Biocryptosystem-Oriented Security Analysis Framework and Implementation of Multibiometric Cryptosystems Based on Decision Level Fusion

Biometric cryptosystems provide an innovative solution for cryptographic key generation, encryption as well as biometric template protection. Besides high authentication accuracy, a good biometric cryptosystem is expected to protect biometric templates effectively, which requires that helper data does not reveal significant information about the templates. Previous works predominantly follow an appropriate entropy definition to measure the security of biometric cryptosystems. In this paper, we point out limitations of entropy-based security analysis and propose a new security analysis framework that combines information-theoretic approach with computational security. In addition, we construct a fingerprint-based multibiometric cryptosystem (MBC) using decision level fusion. Hash functions are employed in our construction to further protect each single biometric trait. The experimental results and security analysis demonstrate that the proposed MBC provides stronger security and better authentication accuracy compared with a cryptosystem based on single biometric.

Fingerprint-based crypto-biometric system for network security

Abstract To ensure the secure transmission of data, cryptography is treated as the most effective solution. Cryptographic key is an important entity in this process. In general, randomly generated cryptographic key (of 256 bits) is difficult to remember. However, such a key needs to be stored in a protected place or transported through a shared communication line which, in fact, poses another threat to security. As an alternative to this, researchers advocate the generation of cryptographic key using the biometric traits of both sender and receiver during the sessions of communication, thus avoiding key storing and at the same time without compromising the strength in security. Nevertheless, the biometric-based cryptographic key generation has some difficulties: privacy of biometrics, sharing of biometric data between both communicating parties (i.e., sender and receiver), and generating revocable key from irrevocable biometric. This work addresses the above-mentioned concerns. We propose an approach to generate cryptographic key from cancelable fingerprint template of both communicating parties. Cancelable fingerprint templates of both sender and receiver are securely transmitted to each other using a key-based steganography. Both templates are combined with concatenation based feature level fusion technique and generate a combined template. Elements of combined template are shuffled using shuffle key and hash of the shuffled template generates a unique session key. In this approach, revocable key for symmetric cryptography is generated from irrevocable fingerprint and privacy of the fingerprints is protected by the cancelable transformation of fingerprint template. Our experimental results show that minimum, average, and maximum Hamming distances between genuine key and impostor’s key are 80, 128, and 168 bits, respectively, with 256-bit cryptographic key. This fingerprint-based cryptographic key can be applied in symmetric cryptography where session based unique key is required.

Alignment-free row-co-occurrence cancelable palmprint Fuzzy Vault

Texture coding approach of palmprint biometric enjoys several merits; however, palmprint texture code suffers from alignment problem during matching, which hinders it from being directly adopted in biometric cryptosystems, such as Fuzzy Vault. On the other hand, Fuzzy Vault itself is plagued by several security and privacy issues if biometric template is left unprotected. In this paper, we proposed two hybrid cancelable palmprint cryptosystems based on palmprint texture code, dubbed row-alone and row-co-occurrence Fuzzy Vaults. To be specific, we blend 2DPalmHash Code (2DPHC), a cancelable biometric scheme, and Fuzzy Vault primitive to jointly protect palmprint templates. In row-alone Fuzzy Vault, we leverage the horizontal displacement tolerance trait of 2DPHC to extract an alignment-free feature set for polynomial projection. We further generalize row-alone Fuzzy Vault to row-co-occurrence Fuzzy Vault to improve the key recovery rate. Besides that, we demonstrate that 2DPHC-based Fuzzy Vault enhances the robustness against several security attacks.

Structure and Performance Analysis of Multi Stage Biometric Cryptosystem

The system aims to bind many biometric cryptosystem using a linker and to increase the matching accuracy at low threshold values. We demonstrate a two stage biometric cryptosystem in which each system uses two different biometric templates. Shielding functions is used to encrypt the biometric template. A One-Time Seed (OTS) generated by the OTS generator is used to link the two biometric cryptosystem. Hash algorithm principle is applied to generate OTS. Finally, the performance of the system is analyzed in terms of False Acceptance Rate (FAR) and False Reject Rate (FRR) for the biometric cryptosystem whereas many classic and contemporary biometric cryptosystem work well at high threshold values, but sharply falls when the threshold values are lowered in the matching process.

Gait authentication on mobile phone using biometric cryptosystem and fuzzy commitment scheme

Authentication systems using gait captured from inertial sensors have been recently developed to enhance the limitation of existing mechanisms on mobile devices and achieved promising results. However, most these systems employed pattern recognition and machine learning techniques in which biometric templates are stored insecurely, which could leave critical security and user privacy issues. Specifically, a compromise of original gait templates could result in everlasting forfeiture. In this paper, two main results will be presented. Firstly, we propose a novel gait authentication system on mobile devices in which the security and privacy are preserved by employing a fuzzy commitment scheme. Instead of storing original gait templates for user verification like in conventional approaches, we verify the user via a stored key which is biometrically encrypted by gait templates collected from a mobile accelerometer. Secondly, the discriminability of sensor-based gait templates are investigated to determine appropriate parameter values to construct an effective gait-based biometric cryptosystem. The performance of our proposed system is evaluated on the dataset including gait signals of 34 volunteers. We achieved the zeroFAR and the False Rejection Rate of approximately 16.18 % corresponding to the key length, as well as the system security level of 139 bits. The results from our experiment show that accelerometer-based gait could be further investigated to construct a biometric cryptosystem, as effective as other biometric traits such as iris, fingerprint, voice, and signature.

IARJSET - Science, Engineering and Technology

Crypto biometric system is widely used in many information security applications to generate cryptographic key using the human retina characteristics. Biometric features will improve the security of cryptographic system. In this paper three retina biometric features are used to generate the key. They include the end points, bifurcation points and islands. This work emphasizes upon unification of three features which enables to generate the secured cryptographic key. This work introduces a unique method to generate a more secured cryptographic key. This mode of operations in network security creates more complexity for hackers to crack. Thus, security is further enhanced using the above technique.

Chaotic Maps for Biometric Template Protection-A Proposal

Modern biometric technologies claim to provide alternative solution to traditional authentication processes. Even though there are various advantages of biometric process, it is vulnerable to attacks which can decline its security. Towards addressing these concerns and improving public confidence, Biometric Cryptosystems and Cancelable Biometrics represent emerging technologies. This paper presents a comprehensive survey of Biometric Cryptosystems and Cancelable Biometrics along with the open issues and challenges. A new approach is proposed to address these open issues and challenges based on Cancellable Biometrics using chaotic maps, which are known to posses desirable properties of pseudo randomness, high sensitivity to initial conditions and very large key space.

Hardware Accelerator Approach Towards Efficient Biometric Cryptosystems for Network Security

Protecting data and its communication is a critical part of the modern network. The science of protecting data, known as cryptography, uses secret keys to encrypt data in a format that is not easily decipherable. However, most commonly secure logons for a workstation connected to a network use passwords to perform user authentication. These passwords are a weak link in the security chain, and are a common point of attack on cryptography schemes. One alternative to password usage for network security is to use a person’s physical characteristics to verify who the person is and unlock the data correspondingly. This study focuses on the Cambridge biometric cryptosystem, a system for performing user authentication based on a user’s iris data. The implementation of this system expanded from a single-core software-only system to a collaborative system consisting of a single core and a hardware accelerator. The experiment takes place on a Xilinx Zynq-7000 All Programmable SoC. Software implementation is performed on one of the embedded ARM A9 cores while hardware implementation makes use of the programmable logic. Our hardware acceleration produced a speedup of 2.2X while reducing energy usage to 47.5 % of its original value for the combined enrolment and verification process. These results are also compared to a many-core acceleration of the same system, providing an analysis of different acceleration methods.

Approach to cryptographic key generation from fingerprint biometrics

In crypto-biometric system CBS, biometric is combined with cryptography. In CBS, either accessing a cryptographic key is controlled with biometric or the key is generated from biometric features. This work is related to the latter approach in CBS. In such a system, protecting the privacy of the biometric data is an important concern. Further, there is a need to generate different cryptographic keys from the same biometric template of a user. Cancellable transformation of biometric data prior to the key generation is known as a solution. In this paper, we propose an approach to generate cryptographic key from cancellable fingerprint templates C

Multimodal Biometric Cryptosystem for Face and Ear Recognition Based on Fuzzy Vault

Multimodal biometrics technology that uses more than two sorts of biometrics data has been universally applied for person certification and proof. Researchers have advised that the ear may have benefits over the face for biometric recognition. In this study, a technique for face and ear recognition has suggested. The face image and ear images are prearranged as input. From the pre-processed input images, the shape and texture characteristics are removed. The shape of ear and face is attained by suggesting modified region growing algorithm and texture characteristic by Local Gabor XOR Pattern (LGXP) method. To produce the fuzzy vault, the multi-modal biometric template and the input key are employed. For working out, the multi-modal biometric template from face and ear will be erected and it is united with the stored fuzzy vault to produce the final key. Experimental results of suggested method explain promising development in multimodal biometric validation.

A New Scheme for the Polynomial Based Biometric Cryptosystems

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.

Secure and privacy enhanced gait authentication on smart phone.

Smart environments established by the development of mobile technology have brought vast benefits to human being. However, authentication mechanisms on portable smart devices, particularly conventional biometric based approaches, still remain security and privacy concerns. These traditional systems are mostly based on pattern recognition and machine learning algorithms, wherein original biometric templates or extracted features are stored under unconcealed form for performing matching with a new biometric sample in the authentication phase. In this paper, we propose a novel gait based authentication using biometric cryptosystem to enhance the system security and user privacy on the smart phone. Extracted gait features are merely used to biometrically encrypt a cryptographic key which is acted as the authentication factor. Gait signals are acquired by using an inertial sensor named accelerometer in the mobile device and error correcting codes are adopted to deal with the natural variation of gait measurements. We evaluate our proposed system on a dataset consisting of gait samples of 34 volunteers. We achieved the lowest false acceptance rate (FAR) and false rejection rate (FRR) of 3.92% and 11.76%, respectively, in terms of key length of 50 bits.

Palmprint based multidimensional fuzzy vault scheme.

Fuzzy vault scheme (FVS) is one of the most popular biometric cryptosystems for biometric template protection. However, error correcting code (ECC) proposed in FVS is not appropriate to deal with real-valued biometric intraclass variances. In this paper, we propose a multidimensional fuzzy vault scheme (MDFVS) in which a general subspace error-tolerant mechanism is designed and embedded into FVS to handle intraclass variances. Palmprint is one of the most important biometrics; to protect palmprint templates; a palmprint based MDFVS implementation is also presented. Experimental results show that the proposed scheme not only can deal with intraclass variances effectively but also could maintain the accuracy and meanwhile enhance security.

An Indirect Fingerprint Authentication Scheme in Cloud Computing

The cloud computing offers dynamically scalable online resources provisioned as a service over the Internet cheaply. However, the security challenges it poses are equally striking. The reliable user authentication techniques are required to combat the rising security threat in cloud communications. Due to the non-denial requirements of remote user authentication scheme, it is most commonly achieved using some form of biometrics-based method. Fingerprint authentication is one of the popular and effective approaches to allow the only authorized users to access the cryptographic keys. While the critical issue in remote biometric cryptosystem is to protect the template of a user stored in a database. The biometric template is not secure and the stolen templates cannot be revoked, which is easy to leak user identity information. To overcome these shortcomings, in this paper, an indirect fingerprint authentication scheme is proposed. Further, we apply this secure scheme to the cloud system combing with PKI mechanism. At last, a comprehensive and detailed security analysis of the proposed scheme in cloud computing is provided.

Fuzzy Commitment Scheme for Masked Iris Codes

The fuzzy commitment scheme is one of most popular biometric cryptosystems that aim at securing cryptographic keys using biometrics. Because of the high recognition accuracy exhibited by the iris, iris-based fuzzy commitment schemes, among other modalities, provide the most practical performance rates. Unfortunately, existing iris-based fuzzy commitment schemes do not incorporate noise masks, generated along with iris-codes to highlight unwanted regions of the iris, because there is no way to know the mask of the decoding iris sample in advance. Therefore, the decoding accuracy of iris-based fuzzy commitment schemes is much less than the recognition accuracy of the underlying iris recognition system. This paper presents an iris-based fuzzy commitment scheme that uses the noise mask of the encoding iris sample at both encoding and decoding stages. Experimental results show that the proposed scheme provides a remarkable improvement in the decoding accuracy of iris-based fuzzy commitment schemes.

Auto-aligned sharing fuzzy fingerprint vault

Recently, a cryptographic construct, called fuzzy vault, has been proposed for crypto-biometric systems, and some implementations for fingerprint have been reported to protect the stored fingerprint template by hiding the fingerprint features. However, all previous studies assumed that fingerprint features were pre-aligned, and automatic alignment in the fuzzy vault domain is a challenging issue. In this paper, an auto-aligned sharing fuzzy fingerprint vault based on a geometric hashing technique is proposed to address automatic alignment in the multiple-control fuzzy vault with a compartmented structure. The vulnerability analysis and experimental results indicate that, compared with original multiple-control fuzzy vault, the auto-aligned sharing fuzzy fingerprint vault can improve the security of the system.

Recognition Accuracy and Robustness of Fingerprint Templates Generated by Discrete Fractional Sine Transform

The fingerprint template which corresponds to the phase distributions (PDs) of the 1D discrete fractional sine transforms (DFSTs) with various transforms’ orders for the grayscale distributions in the transverse lines of the original fingerprint image is proposed. In addition the recognition accuracy and the robustness of the proposed fingerprint templates are evaluated statistically. The condition to realize the high accuracy of fingerprint recognition using the proposed templates has been made clear on the basis of the Receiver Operating Characteristic (ROC) curve and the minimum error rate (MER). The smallest value of the MER became 19 10 60 . 1   %. As for the robustness of the proposed templates, it has been evaluated statistically by use of the normalized cross-correlation function (NCF) between the original data and the inverse transformed data of the proposed template under the condition that the transforms’ orders are known by an adversary. As a result, the high security of the proposed templates could be indicated. Individual recognition using the biological information has been recently increasing everywhere, for example, in the automatic logging into a PC, the immigration at the airport, and so on. In particular, the fingerprint recognition system has been widely used because of its high reliability and reasonable price [1]. In general, the enrolled fingerprint images are stored as templates in the database referred in the fingerprint recognition process. The information of the templates should be hidden to keep individual biological information secret. Many methods have been recently proposed, for example, the biometric cryptosystems [2][5], cancellable fingerprint templates [6]-[10], and so on. However, in these methods, since the minutia-based templates are basically used, the recognition accuracy tends to become low in comparison with that of the image-based templates. In order to realize the fingerprint templates with high recognition accuracy and high robustness against attacks, we have proposed a new method for generating templates by use of the intensity distributions of the 1D fractional Fourier transforms (FRTs) [11] of original fingerprint images [12,13]. In our method, the FRTs with different transforms’ orders are applied to the 1D data extracted from the 2D original fingerprint image in a specific direction. However, there might be a possibility that the FRT’s order in each line of the fingerprint image is revealed, because the extent of the intensity FRT is dependent on the FRT’s order. In this paper, to solve this problem, we propose the fingerprint templates generated by the DFSTs, and indicate the accuracy of the fingerprint recognition by use of the proposed templates. Specifically, first, we compare the amplitude distribution (AD) and PD of the discrete FRTs (DFRTs), the discrete fractional cosine transforms (DFCTs) [14] and the DFSTs [14] of the fingerprint image, and decide the most appropriate distribution and transform used in the generation process of the proposed fingerprint templates. Next, we evaluate the recognition accuracy of the generated fingerprint templates from the viewpoints of the ROC curve, which denotes the relationship between the false acceptance rate (FAR) and the false rejection rate (FRR), and the MER, where the FAR and the FRR take the same value [15]. In the analysis, the effects of the misalignment in the recognition process are not considered. Finally, we quantitatively analyze the robustness of the templates. 2. DFRT, DFCT and DFST The FRT [11], which is regarded as the generalization of a conventional Fourier transform (FT), was introduced by Namias to solve the problem of a harmonic oscillator in quantum mechanics in 1980 [16]. The FRT of 1D input data u(x) is defined as [11]    ] tan / ) ( exp[ ) ( ) ( 2 2   s x x i x u x u p p p , ] sin / 2 exp[ dx s x ixp     (1)

Generate an Encryption Key by using Biometric Cryptosystems to secure transferring of Data over a Network

Our modern day era faces an inevitable problem of securing our most integrated data and messages. The chief problem is to protect our data in a unique way that could only be worked upon by the sender and the recipient. Most of the traditional techniques probably in-use today, emphasizes on keys that are generated by generic function, algorithms or in random key generators. But question remains whether this key is unique and authentic in nature. Moreover how can these keys be unique to one and one person only? The answer to this would be Biometric Cryptosystems. Biometric Cryptosystems are the newest members in the field of security. The very basis of this Biometric Cryptosystem lies on the very fact that some features of human body are significantly unique to each and every human in the world, such as fingerprint, DNA sequence, Iris, etc. Using those biometric we can generate an exclusive key that will be unique for each and every individual. Now having generated these keys we can use them for encrypting our message. And as because these keys are uniquely generated for individual persons there’s no chance of there will be a matching keys. Moreover as we use RSA algorithm based encryption technique so the encryption lies on two basic sets of keys to decrypt the message. Hence, eavesdropper or third unwanted parties have to acquire two set of keys which adds up to security level of the encryption and hence protect the message from unwanted third parties from acquiring our secret message.

Security performance evaluation for biometric template protection techniques

Biometric template protection techniques are able to provide a solution for vulnerability which compromises biometric template. These are expected to be useful for remote biometric authentication. However, there were no supported standard evaluation method, thus making these technology not fully trusted. The draft Recommendation ITU-T X.gep: 'A guideline for evaluating telebiometric template protection techniques' which is currently under development at ITU-T SG 17 Question 9 (telebiometrics) aims to fill this need. ITU-T X.gep describes a general guideline for testing and reporting the performance of biometric template protection techniques based on biometric cryptosystem and cancellable biometrics. This guideline specifies two reference models for evaluation which use biometric template protection techniques in telebiometrics system. Then, it defines the metrics, procedures, and requirements for testing and evaluating the performance of the biometric template protection techniques. In addition, this Recommendation ITU-T X.gep has been approved at April 2012, and pre-published as ITU-T X.1091.

Biometric cryptosystem based on discretized fingerprint texture descriptors

This paper focuses on a biometric cryptosystem implementation and evaluation based on a number of fingerprint texture descriptors. The texture descriptors, namely, the Gabor filter-based FingerCode, a local binary pattern (LBP), and a local direction pattern (LDP), and their various combinations are considered. These fingerprint texture descriptors are binarized using a biometric discretization method and used in a fuzzy commitment scheme (FCS). We constructed the biometric cryptosystems, which achieve a good performance, by fusing discretized fingerprint texture descriptors and using effective error-correcting codes. We tested the proposed system on a FVC2000 DB2a fingerprint database, and the results demonstrate that the new system significantly improves the performance of the FCS for texture-based fingerprints.