Cancelable Biometric Template Research Articles

Random Slope method for generation of cancelable biometric features

Cancelable biometric templates are transformed versions of original biometric templates used for authentication purposes. The transformation functions should fulfill the important template protection criteria of diversity, revocability, non-invertibility, and performance. Although there exists a number of transformation techniques, yet many of these techniques fail to meet security and privacy requirements in the stolen token scenario and tend to become invertible with degraded performance. The work proposes a novel cancelable biometric technique named as ‘Random Slope’ method for generating secure, revocable, and non-invertible templates. Two approaches (RS-V1 and RS-V2) developed using the proposed concept not only fulfill the important cancelability criteria, but also provide dimensionality reduction upto 75%. The performances of the proposed approaches are experimentally verified for various biometric modalities such as visible and thermal face, palmprint, palmvein, and fingervein. As compared to some state of the art template transformation schemes, the proposed RS-V1 and RS-V2 approaches establish their reliability and effectiveness by performing better than these existing techniques with significant reduction in dimensions.

Random permutation principal component analysis for cancelable biometric recognition

Although biometrics is being increasingly used across the world, it also raises concerns over privacy and security of the enrolled identities. This is due to the fact that biometrics are not cancelable and if compromised may give access to the intruder. To address these problems, in this paper, we suggest two simple and powerful techniques called (i) Random Permutation Principal Component Analysis (RP-PCA) and (ii) Random Permutation Two Dimensional Principal Component Analysis (RP-2DPCA). The proposed techniques are based on the idea of cancelable biometric which can be reissued if compromised. The proposed techniques work in a cryptic manner by accepting the cancelable biometric template and a key (called PIN) issued to a user. The identity of a person is recognized only if the combination of template and PIN is valid, otherwise the identity is rejected. The superiority of the proposed techniques is demonstrated on three freely available face (ORL), iris (UBIRIS) and ear (IITD) datasets against state-of-the-art methods. The key advantages of the proposed techniques are (i) classification accuracy remains unaffected due to cancelable biometric templates generated using random permutation (ii) robustness across different biometrics. In addition, no image registration is required for performing recognition.

Design of a cancelable biometric template protection scheme for fingerprints based on cryptographic hash functions

Enforcing security and privacy guarantees for biometric users via protecting their unique and personalized attributes is an important area of research. There are many properties desirable in a biometric template protection scheme, but unfortunately, all of the requirements are not simultaneously fulfilled. In our work, we have tried to address this issue by proposing a cancelable framework for fingerprints which simultaneously provides satisfactory system performance, strong security guarantees, and fast matching procedure. The core of our scheme essentially pivots around the use of cryptographic hash functions which provide the adequate levels of security in the framework. Prior to the hashing stage, we have employed an effective pre-alignment technique and a hexagonal grid based quantization scheme which allows us to overcome constraint such as intra-class variability. Finally, our scheme is made cancelable through traditional salting. We tested our framework on various fingerprint databases and found that the resulting system performances were comparable with other contemporary cancelable schemes (EERs of 5.8%, 5.3%, 15.8%, 14.5% were observed for FVC2002 DB1, DB2, FVC2004 DB1, DB2 databases under the stolen token scenario). Most importantly, we perfectly fulfill the unlinkability, cancelability and diversity requirements, which are verified both theoretically and empirically.

보안레벨 조절이 가능한 바이오메트릭 인증 기법

지문은 사람마다 고유하며 디지털 데이터로 표현할 수 있는 생체 정보이다. 지문은 사람 몸의 일부이기 때문에, 지문인식은 패스워드나 신분증을 이용한 방법보다 사용하기 편리하다. 더불어, 최근 보급되고 있는 스마트폰은 카메라 및 지문인식 센서가 내장되어 있어서, 바이오메트릭 인증에 대한 사용자의 수요가 증가하고 있다. 하지만 지문은 쉽게 복제가 가능하고 한 번 도용되면 해당 지문을 다시 사용할 수 없는 단점이 있다. 따라서, 바이오메트릭 데이터는 원본을 변형하여 등록 및 인증해야 한다. 기존의 패스코드 입력 방식은 지문인식 센서 외에 별도의 입력 모듈이 필요하기 때문에 경제성과 사용성이 떨어진다. 본 논문에서는 사용성과 경제성을 고려한 취소 가능한 바이오메트릭 인증 기법을 제안한다. 제안한 인증 기법은 취소 가능한 바이오메트릭 템플릿 생성, 바이오메트릭 템플릿 등록 그리고 사용자 인증 프로토콜로 구성되며, 사용된 지문 개수와 스캔 타임에 따라서 보안레벨을 조절할 수 있다. 더불어, 제안한 방법이 전사적 공격과 능동적 공격으로부터 안전함을 분석하였다. A fingerprint is unique to each person and can be represented as a digital form. As the fingerprint is the part of human body, fingerprint recognition is much more easy to use and secure rather than using password or resident card for user authentication. In addition, as the newly released smart phones have built-in camera and fingerprint sensors, the demand for biometric authentication is increasing rapidly. But, the drawback is that the fingerprint can be counterfeited easily and if it's exposed to the hacker, it cannot be reused. Thus, the original fingerprint template should be transformed for registration and authentication purposes. Existing transformation functions use passcode to transform the original template to the cancelable form. Additional module is needed to input the passcode, so it requires more cost and lowers the usability. In this paper, we propose biometric authentication scheme that is economic and easy to use. The proposed scheme is consisted of cancelable biometric template creation, registration and user authentication protocols, and can control several security levels by configuring the number of fingerprints and scan times. We also analyzed that our scheme is secure against the brute-force attack and the active attacks.

Cancelable Biometrics: A review

Recent years have seen an exponential growth in the use of various biometric technologies for trusted automatic recognition of humans. With the rapid adaptation of biometric systems, there is a growing concern that biometric technologies may compromise the privacy and anonymity of individuals. Unlike credit cards and passwords, which can be revoked and reissued when compromised, biometrics are permanently associated with a user and cannot be replaced. To prevent the theft of biometric patterns, it is desirable to modify them through revocable and noninvertible transformations to produce cancelable biometric templates. In this article, we provide an overview of various cancelable biometric schemes for biometric template protection. We discuss the merits and drawbacks of available cancelable biometric systems and identify promising avenues of research in this rapidly evolving field.

Gaussian Random Projection Based Non-invertible Cancelable Biometric Templates

Abstract Wide spread use of biometric based authentication implies the need to secure biometric reference data. Various template protection schemes have been introduced to prevent biometric forgery and identity thefts. Cancelable biometrics is a recent approach introduced to address the concerns regarding privacy of biometric data, public confidence, and acceptance of biometric systems. It allows biometric templates to be cancelled and revoked like passwords innumerable times. The work proposes a novel cancelable biometric template generation algorithm using Gaussian random vectors and one way modulus hashing. Instead of using the original templates, the proposed system uses its transformed versions for storing and matching. The approach is tested on face and palmprint biometric modalities. A thorough analysis is performed to analyze the performance, non-invertibility, and distinctiveness of the proposed approach which reveals that the generated templates are non-invertible, easy to revoke, and also deliver good performance.

Novel Shift-Phase Transformation based Cancelable and Irrevocable Biometric Template Generation for Fingerprints

Novel Shift-Phase Transformation based Cancelable and Irrevocable Biometric Template Generation for Fingerprints

Situation awareness of cancelable biometric system

Recently, cancelable biometrics emerged as one of the highly effective methods of template protection. The concept behind the cancelable biometrics or cancelability is a transformation of a biometric data or extracted feature into an alternative form, which cannot be used by the imposter or intruder easily, and can be revoked if compromised. In this paper, we present a novel architecture for template generation in the context of situation awareness system in real and virtual applications. We develop a novel cancelable biometric template generation algorithm utilizing random biometric fusion, random projection and selection. Proposed random cross-folding method generate cancelable biometric template from multiple biometric traits. We further validate the performance of the proposed algorithm using a virtual multimodal face and ear database.

Cancelable Fusion of Face and Ear for Secure Multi-Biometric Template

Biometric fusion to achieve multimodality has emerged as a highly successful new approach to combat problems of unimodal biometric system such as intraclass variability, interclass similarity, data quality, non-universality, and sensitivity to noise. The authors have proposed new type of biometric fusion called cancelable fusion. The idea behind the cancelable biometric or cancelability is to transform a biometric data or feature into a new one so that the stored biometric template can be easily changed in a biometric security system. Cancelable fusion does the fusion of multiple biometric trait in addition it preserve the properties of cancelability. In this paper, the authors present a novel architecture for template generation within the context of the cancelable multibiometric fusion. The authors develop a novel cancelable biometric template generation algorithm using cancelable fusion, random projection and transformation-based feature extraction and selection. The authors further validate the performance of the proposed algorithm on a virtual multimodal face and ear database.

A Novel Cross Folding Algorithm for Multimodal Cancelable Biometrics

Multimodal biometric systems have emerged as highly successful new approach to combat problems of unimodal biometric system such as intraclass variability, interclass similarity, data quality, non-universality, and sensitivity to noise. However, one major issue pertinent to unimodal system remains, which has to do with actual biometric characteristics of users being permanent and their number being limited. Thus, if a user’s biometric is compromised, it might be impossible or highly difficult to replace it in a particular system. The concept of cancelable biometric or cancelability is to transform a biometric data or feature into a new one so that the stored biometric template can be easily changed in a biometric security system. In this paper, the authors present a novel solution for cancelable biometrics in a multimodal system. They develop a new cancelable biometric template generation algorithm using random projection and transformation-based feature extraction and selection. Performance of the proposed algorithm is validated on a virtual multi-modal face and ear database.