Cancelable Fingerprint Templates Research Articles

A secure fingerprint template generation mechanism using visual secret sharing with inverse halftoning

Fingerprints are the most popular and widely practiced biometric trait for human recognition and authentication. Due to the wide approval, reliable fingerprint template generation and secure saving of the generated templates are highly vital. Since fingers are permanently connected to the human body, loss of fingerprint data is irreversible. Cancelable fingerprint templates are used to overcome this problem. This paper introduces a novel cancelable fingerprint template generation mechanism using Visual Secret Sharing (VSS), data embedding, inverse halftoning, and super-resolution. During the fingerprint template generation, VSS shares with some hidden information are formulated as the secure cancelable template. Before authentication, the secret fingerprint image is reconstructed back from the VSS shares. The experimental results show that the proposed cancelable templates are simple, secure, and fulfill all the properties of the ideal cancelable templates, such as security, accuracy, non-invertibility, diversity, and revocability. The experimental analysis shows that the reconstructed fingerprint images are similar to the original fingerprints in terms of visual parameters and matching error rates.

One-Factor Cancellable Fingerprint Template Protection Based on Index Self-Encoding

The existing one-factor cancellable biometrics algorithms generally require random sequences to reorder the biometrics, which reduces the discrimination of the transformed biometrics. Some algorithms hide and transmit the random sequence by XORing the random sequence with original biometrics, which may cause the leakage of the original biometrics. Therefore, this paper proposes a one-factor cancellable fingerprint template protection based on index self-encoding. First, the integer sequence generated by the hash function is used as the index. The random sequence is automatically encoded directly by the index value, and the generated binary sequence retains the original biological characteristics to the greatest extent. Second, self-encoding binary sequence and random binary sequence are XORed to obtain the encoded key without directly storing binary factor sequences. Experiments are implemented on the fingerprint database of FVC2002 and FVC2004, the results show that the recognition rate is enhanced; meanwhile, it fits the design criteria of cancellable biometrics.

A Novel Length-Flexible Lightweight Cancelable Fingerprint Template for Privacy-Preserving Authentication Systems in Resource-Constrained IoT Applications

Fingerprint authentication techniques have been employed in various Internet of Things (IoT) applications for access control to protect private data, but raw fingerprint template leakage in unprotected IoT applications may render the authentication system insecure. Cancelable fingerprint templates can effectively prevent privacy breaches and provide strong protection to the original templates. However, to suit resource-constrained IoT devices, oversimplified templates would compromise authentication performance significantly. In addition, the length of existing cancelable fingerprint templates is usually fixed, making them difficult to be deployed in various memory-limited IoT devices. To address these issues, we propose a novel length-flexible lightweight cancelable fingerprint template for privacy-preserving authentication systems in various resource-constrained IoT applications. The proposed cancelable template design primarily consists of two components: 1) length-flexible partial-cancelable feature generation based on the designed reindexing scheme and 2) lightweight cancelable feature generation based on the designed encoding nested difference XOR scheme. Comprehensive experimental results on public databases FVC2002 DB1–DB4 and FVC2004 DB1–DB4 demonstrate that the proposed cancelable fingerprint template achieves equivalent authentication performance to state-of-the-art methods in IoT environments, but our design substantially reduces template storage space and computational cost. More importantly, the proposed length-flexible lightweight cancelable template is suitable for a variety of commercial smart cards (e.g., C5-M.O.S.T. Card Contact Microprocessor Smart Cards CLXSU064KC5). To the best of our knowledge, the proposed method is the first length-flexible lightweight, high-performing cancelable fingerprint template design for resource-constrained IoT applications.

A novel cancelable fingerprint scheme based on random security sampling mechanism and relocation bloom filter

The existing cancellable fingerprint template based on the bloom filter either suffers from a lack of template security or low recognition performance. To solve the above problems, the paper proposes a novel cancelable fingerprint protection scheme based on a random sampling mechanism and relocation bloom filter. The security matrix is generated by a random sampling mechanism to increase the security and recognition accuracy of the scheme. The structure of a random sampling mechanism is as follows. Firstly, we use the key management system to generate keys and a chaotic matrix with randomness. Secondly, the key is used as a random initial address to extract overlapping feature sub-blocks from fingerprint features. Then the feature sub-blocks are combined to generate a feature matrix. Therefore, the feature matrix has richer fingerprint information than the original fingerprint features. Finally, a security matrix is generated by the XOR fusion of features matrix and chaotic matrix. Furthermore, we designed a relocation bloom filter with a parallel structure, which provides a way to avoid the decrease in performance caused by hash conflicts. What is more, it increased the security of the scheme that the relocatable bloom uses an irreversible function mapping function to transform the security matrix into a cancelable fingerprint template. The experimental results demonstrate that this scheme has state-of-the-art accuracy performance on benchmark FVC2002 and FVC2004 fingerprint databases. The security analysis shows that the scheme meets the cancellable biometrics protection scheme criteria and has higher security.

A Secure Online Fingerprint Authentication System for Industrial IoT Devices over 5G Networks.

The development of 5G networks has rapidly increased the use of Industrial Internet of Things (IIoT) devices for control, monitoring, and processing purposes. Biometric-based user authentication can prevent unauthorized access to IIoT devices, thereby safeguarding data security during production. However, most biometric authentication systems in the IIoT have no template protection, thus risking raw biometric data stored as templates in central databases or IIoT devices. Moreover, traditional biometric authentication faces slow, limited database holding capacity and data transmission problems. To address these issues, in this paper we propose a secure online fingerprint authentication system for IIoT devices over 5G networks. The core of the proposed system is the design of a cancelable fingerprint template, which protects original minutia features and provides privacy and security guarantee for both entity users and the message content transmitted between IIoT devices and the cloud server via 5G networks.Compared with state-of-the-art methods, the proposed authentication system shows competitive performance on six public fingerprint databases, while saving computational costs and achieving fast online matching.

Indexing-Min–Max Hashing: Relaxing the Security–Performance Tradeoff for Cancelable Fingerprint Templates

Cancelable biometrics is a powerful remedy for information leakage caused by the extensive usage of unprotected biometric data. Current measures usually suffer from deteriorated accuracy, which is known as the security–performance tradeoff. Motivated by these concerns, in this article, a novel cancelable fingerprint approach, i.e., Indexing-Min–Max (IMM) hashing, is proposed to securely transform a fixed-length fingerprint feature vector to a discrete index hashed code. IMM hashing is essentially established upon the min–max hash and further strengthened by the integration of the partial Hadamard transform, which alleviates performance deterioration while maintaining a high security level. Extensive experiments on FVC2002 and FVC2004 fingerprint datasets coupled with comprehensive theoretical analyses demonstrate the favorable accuracy and strong anti-attack resilience of the proposed method. Besides, compared to the unprotected counterpart, the matching precision of the protected templates yields little accuracy loss or even improved performance, which means the security–performance tradeoff is well handled. Furthermore, IMM hashing also meets the unlinkability and revocability requisites of cancelable biometrics.

An alignment-free non-invertible transformation-based method for generating the cancellable fingerprint template

An alignment-free non-invertible transformation-based method for generating the cancellable fingerprint template

Performance analysis of a parameterized minutiae-based approach for securing fingerprint templates in biometric authentication systems

The fingerprint templates include almost the entire information about an individual’s fingerprints, and the user validation is totally determined by the fingerprint minutiae features. Due to the sort of attacks, the most challenging task is to shield the fingerprint templates (or minutiae features). The paper is concerned with the development of a parameterized minutiae-based approach to generate the secure biometric templates from the fingerprint images. The minutiae features were extracted from the individual’s fingerprint images, and then their associated parameters were explored to hide the real minutiae information. A minutiae-based transformation algorithm was employed by adding extra chaffs (fake minutiae) and remodeling the real minutiae to generate a secure vault that leads to a cancelable fingerprint template. As a fingerprint template contains only the transformed and fake minutiae, it is almost impossible for the attacker to induce the real minutia information. The proposed method assisted to create multiple dissimilar fuzzy vaults for a single fingerprint; thereby, the correlation attacks would be resisted. The proposed method achieved the highest accuracy in verification phase compared to other methods, and provided a novel contribution in the field of biometric security for protecting the fingerprint templates.

A Two-Stage Feature Transformation-Based Fingerprint Authentication System for Privacy Protection in IoT

The significant and rapid development of the Internet of Things (IoT) in recent years has greatly benefited people's lives. However, there are serious security and privacy concerns that need to be addressed when using the IoT for distributed authentication. In this article, we propose a secure fingerprint authentication system to protect user privacy for authentication on IoT devices. The proposed system applies a two-stage feature transformation scheme. Specifically, a weight-based fusion mechanism is designed in the first stage, while the second stage is featured by a linear convolution-based transformation with element removal from the convolution output to increase the security and protection. The proposed authentication system satisfies all the requirements of cancelable biometrics: accuracy, revocability, and diversity, unlinkability, and noninvertibility. Evaluated over six public fingerprint databases, the proposed authentication system exhibits highly competitive performance when compared with the existing cancelable fingerprint templates. Moreover, its energy efficiency on savings in memory space and low computational costs make the proposed scheme a good fit for resource-limited IoT devices.

SPIN: A Blockchain-Based Framework for Sharing COVID-19 Pandemic Information across Nations

The COVID-19 pandemic has caused many countries around the globe to put strict policies and measures in place in an attempt to control the rapid spread of the virus. These measures have affected economic activities and have impacted a broad range of businesses, such as international traveling, restaurants, and shopping malls. As COVID-19 vaccination efforts progress, countries are starting to relax international travel constraints and permit passengers from certain destinations to cross the border. Moreover, travelers from those destinations are likely required to provide certificates of vaccination results or negative COVID-19 tests before crossing the borders. Implementing these travel guidelines requires sharing information between countries, such as the number of COVID-19 cases and vaccination certificates for travelers. In this paper, we introduce SPIN, a framework leveraging a permissioned blockchain for sharing COVID-19 information between countries. This includes public data, such as the number of vaccinated people, and private data, such as vaccination certificates for individuals. Additionally, we employ cancelable fingerprint templates to authenticate private information about travelers. We analyze the framework from scalability, efficiency, security, and privacy perspectives. To validate our framework, we provide a prototype implementation using the Hyperledger Fabric platform.

Design of cancelable MCC-based fingerprint templates using Dyno-key model

Minutia Cylinder Code (MCC) is an effective, high-quality representation of local minutia structures. MCC templates demonstrate fast and excellent fingerprint matching performance, but if compromised, they can be reverse-engineered to retrieve minutia information. In this paper, we propose alignment-free cancelable MCC-based templates by exploiting the MCC feature extraction and representation. The core component of our design is a dynamic random key model, called Dyno-key model. The Dyno-key model dynamically extracts elements from MCC’s binary feature vectors based on randomly generated keys. Those extracted elements are discarded after the block-based logic operations so as to increase security. Leveling with the performance of the unprotected, reproduced MCC templates, the proposed method exhibits competitive performance in comparison with state-of-the-art cancelable fingerprint templates, as evaluated over seven public databases, FVC2002 DB1-DB3, FVC2004 DB1 and DB2, and FVC2006 DB2 and DB3. The proposed cancelable MCC-based templates satisfy all the requirements of biometric template protection.

Alignment-free cancelable fingerprint templates with dual protection

Cancelable biometrics is an important biometric template protection technique. However, many existing cancelable fingerprint templates suffer post-transformation performance deterioration and the attacks via record multiplicity (ARM). In this paper, we design alignment-free cancelable fingerprint templates with dual protection, which is composed of the window-shift-XOR model and the partial discrete wavelet transform. The former defuses the ARM threat and is combined with the latter to provide dual protection and enhance matching performance. The designed cancelable templates meet the requirements of non-invertibility, diversity and revocability and demonstrate superior recognition accuracy, when evaluated over public databases; for example, the Equal Error Rate of the proposed method in the lost-key scenario under the 1vs1 protocol is 0% for both FVC2002 DB1 and DB2, 1.63% for FVC2002 DB3, 7.35% for FVC2004 DB1 and 4.69% for FVC2004DB2.

Non-Invertible cancellable fingerprint template for fingerprint biometric

Fingerprint biometric has emerged as a highly successful biometric recognition system and find its application in the diverse domain. The fingerprint template database needs to be protected from unauthorized access. If an adversary has acquired the unprotected fingerprint template, then he/she may reconstruct original fingerprint which can be used for unauthorized access of all the systems where the same fingerprint has been used. Hence, securing the fingerprint template is required. In this paper, a non-invertible cancellable fingerprint template based on information extracted from the Delaunay triangulation of minutiae points is proposed. For making the template cancellable a user-specific key of a random binary string is used. The proposed template is revocable, diverse, secure and also gives a good recognition accuracy. The proposed template is tested with a standard FVC2002 database and gives good results as compared with the latest methods.

Evaluating biometrics fingerprint template protection for an emergency situation

Biometric template protection approaches have been developed to secure the biometric templates against image reconstruction on the stored templates. Two cancellable fingerprint template protection approaches namely minutiae-based bit-string cancellable fingerprint template and modified minutiae-based bit-string cancellable fingerprint template, are selected to be evaluated. Both approaches include the geometric information of the fingerprint into the extracted minutiae. Six modified fingerprint data sets are derived from the original fingerprint images in FVC2002DB1_B and FVC2002DB2_B by conducting the rotation and changing the quality of original fingerprint images according to the environment conditions during an emergency situation such as wet or dry fingers and disoriented angle of fingerprint images. The experimental results show that the modified minutiae-based bit-string cancellable fingerprint template performs well on all conditions during an emergency situation by achieving the matching accuracy between 83% and 100% on FVC2002DB1_B data set and between 99% and 100% on FVC2002DB2_B data set.

A Cancelable Template for the Low-Quality Fingerprints from Wearable Devices

Biometric authentication in wearable devices is different from the common biometric authentication systems. First of all, sensitive information such as fingerprint and iris of a user is stored in a wearable device owned by the user rather than being stored in a remote database. Wearable devices are portable, and there is a risk that the devices might be lost or stolen. In addition, the quality of the extracted image from the wearable devices is lower than that of the common biometric acquisition sensor. In the paper, we propose a novel cancelable fingerprint template which is irreversible to the original biometrics and has excellent accuracy even in low quality images.

A cancelable fingerprint biometric based session key establishment protocol

Symmetric key cryptography needs the communicating parties to share a secret key. It is desired that a different shared key is established for each communication session. A trusted third party distributes these shared keys through a communication link between communicating parties. As the key is transferred through an insecure communication link attacker can guess the key easily. So maintenance and distribution of keys is a problem. Efficient and reliable techniques are needed that allow two or more remote parties to set up a shared secret key in a dynamic on-demand manner. As a probable solution to this problem, generation of the cryptographic key using the biometric traits of both communicating parties during the transmission session can be done. Thus avoiding key storing and key sharing in session key establishment protocols. However, this biometric based cryptographic key generation has some difficulties of maintaining the privacy of user’s biometric data, exchanging of biometric data and revocable key generation from irrevocable biometric. This present methodology addresses the mentioned concern and proposes a session key establishment protocol where communicating parties first transform their biometric template in cancelable one to preserve the privacy of biometric template and exchange transformed template with each other. After that generate a 128- bit session key in their end with the help of their combined cancelable fingerprint templates and a random shuffle key provided to them by a trusted authentication server. Authentication server works as a trusted third party and is located in between the communicating parties. As both parties generates the same session key in their end there is no need to share secret key through insecure channel. This generated biometric based session keys can be used in the session key establishment protocol for better security of data transmission.

Cancelable fingerprint template design with randomized non-negative least squares

Although biometrics is considered more competent than password-based or token-based approach in identity management, biometric templates are vulnerable to adversary attacks that may lead to irreversible identity loss. One of the promising remedies for biometric template protection is cancelable biometrics. In this paper, a novel binary cancelable fingerprint template design based on Partial Local Structure (PLS) descriptor and Permutated Randomized Non-Negative Least Square (PR-NNLS) is proposed. The PLS descriptor is an alignment-free minutia descriptor, which is conceived to be coupled with the PR-NNLS to derive a binary protected fingerprint template that satisfies non-invertibility, unlinkability, cancelability and performance criteria. The PR-NNLS formulation is unique in such a way that the noninvertible transformation is applied to the PLS descriptor dictionary instead of applying it to the minutiae descriptor, which often invites performance deterioration. The evaluations have been carried out with five subsets from FVC 2002 and 2004 databases where the proposed method is attested to fulfill the aforementioned four template protection criteria. We also analyze four privacy and security attacks targeted to cancelable biometrics.

Biometrics Based Privacy-Preserving Authentication and Mobile Template Protection

Smart mobile devices are playing a more and more important role in our daily life. Cancelable biometrics is a promising mechanism to provide authentication to mobile devices and protect biometric templates by applying a noninvertible transformation to raw biometric data. However, the negative effect of nonlinear distortion will usually degrade the matching performance significantly, which is a nontrivial factor when designing a cancelable template. Moreover, the attacks via record multiplicity (ARM) present a threat to the existing cancelable biometrics, which is still a challenging open issue. To address these problems, in this paper, we propose a new cancelable fingerprint template which can not only mitigate the negative effect of nonlinear distortion by combining multiple feature sets, but also defeat the ARM attack through a proposed feature decorrelation algorithm. Our work is a new contribution to the design of cancelable biometrics with a concrete method against the ARM attack. Experimental results on public databases and security analysis show the validity of the proposed cancelable template.

Random Projection-based Cancelable Template Generation for Sparsely Distributed Biometric Patterns

Cancelable biometrics, a template transformation approach, attempts to provide robustness for authentication services based on biometrics. Several biometric template protection techniques represent the biometric information in binary form as it provides benefits in matching and storage. In this context, it becomes clear that often such transformed binary representations can be easily compromised and breached. In this paper, we propose an efficient non-invertible template transformation approach using random projection technique and Discrete Fourier transformation to shield the binary biometric representations. The cancelable fingerprint templates designed by the proposed technique meets the requirements of revocability, diversity, non-invertibility and performance. The matching performance of the cancelable fingerprint templates generated using proposed technique, have improved when compared with the state-of-art methods.

Cancelable remote quantum fingerprint templates protection scheme**Project supported by the National Natural Science Foundation of China (Grant Nos. 61379153 and 61572529).

With the increasing popularity of fingerprint identification technology, its security and privacy have been paid much attention. Only the security and privacy of biological information are insured, the biological technology can be better accepted and used by the public. In this paper, we propose a novel quantum bit (qbit)-based scheme to solve the security and privacy problem existing in the traditional fingerprint identification system. By exploiting the properties of quantm mechanics, our proposed scheme, cancelable remote quantum fingerprint templates protection scheme, can achieve the unconditional security guaranteed in an information-theoretical sense. Moreover, this novel quantum scheme can invalidate most of the attacks aimed at the fingerprint identification system. In addition, the proposed scheme is applicable to the requirement of remote communication with no need to worry about its security and privacy during the transmission. This is an absolute advantage when comparing with other traditional methods. Security analysis shows that the proposed scheme can effectively ensure the communication security and the privacy of users’ information for the fingerprint identification.