A Secure Framework to Preserve Privacy of Biometric Templates on Cloud using Deep Learning

Recent Advances in Computer Science and Communications ◽

10.2174/2666255813999200724172343 ◽

2020 ◽

Vol 13 ◽

Author(s):

Shefali Arora ◽

MPS Bhatia

Keyword(s):

Cloud Computing ◽

Deep Convolutional Neural Networks ◽

Biometric Data ◽

Template Security ◽

Biometric Template ◽

Matching Performance ◽

Remote Services ◽

Security And Reliability ◽

Biometric Templates ◽

Secure Framework

Introduction: Cloud computing involves the use of maximum remote services through a network using minimum resources via internet. There are various issues associated with cloud computing, such as privacy, security and reliability. Due to rapidly increasing information on the cloud, it is important to ensure security of user information. Biometric template security over cloud is one such concern. Leakage of unprotected biometric data can serve as a major risk for the privacy of individuals and security of real-world applications. Method: In this paper, we improvise a secure framework named DeepCrypt, that can be applied to protect biometric templates during authentication of biometric templates. We use deep Convolutional Neural Networks to extract features from these modalities. The resulting features are hashed using a secure combination of Blowcrypt (Bcrypt) and SHA-256 algorithm, which salts the templates by default before storing on the server. Results: Experiments conducted on the CASIA-Iris-M1-S1, CMU-PIE and FVC-2006 datasets achieve around 99% Genuine accept rates, proving that this technique helps to achieve better performance along with high template security. Discussion: The proposed method is robust and provides cancellable biometric templates, high security and better matching performance as compared to traditional techniques used to protect biometric template.

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Biometric template security: an overview

Sensor Review ◽

10.1108/sr-07-2017-0131 ◽

2018 ◽

Vol 38 (1) ◽

pp. 120-127 ◽

Cited By ~ 2

Author(s):

Naveed Riaz ◽

Ayesha Riaz ◽

Sajid Ali Khan

Keyword(s):

Provable Security ◽

Feature Transformation ◽

Transformation Techniques ◽

Content Type ◽

General Acceptance ◽

Biometric Security ◽

Template Security ◽

Biometric Template ◽

High Level ◽

Biometric Templates

Purpose The security of the stored biometric template is itself a challenge. Feature transformation techniques and biometric cryptosystems are used to address the concerns and improve the general acceptance of biometrics. The purpose of this paper is to provide an overview of different techniques and processes for securing the biometric templates. Furthermore, the paper explores current research trends in this area. Design/methodology/approach In this paper, the authors provide an overview and survey of different features transformation techniques and biometric cryptosystems. Findings Feature transformation techniques and biometric cryptosystems provide reliable biometric security at a high level. There are many techniques that provide provable security with practical viable recognition rates. However, there remain several issues and challenges that are being faced during the deployment of these technologies. Originality/value This paper provides an overview of currently used techniques for securing biometric templates and also outlines the related issues and challenges.

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Polynomial Based Fuzzy Vault Technique for Template Security in Fingerprint Biometrics

The International Arab Journal of Information Technology ◽

10.34028/iajit/17/6/11 ◽

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

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Task Scheduling for Multi-Cloud Computing Subject to Security and Reliability Constraints

IEEE/CAA Journal of Automatica Sinica ◽

10.1109/jas.2021.1003934 ◽

2021 ◽

Vol 8 (4) ◽

pp. 848-865

Author(s):

Qing-Hua Zhu ◽

Huan Tang ◽

Jia-Jie Huang ◽

Yan Hou

Keyword(s):

Cloud Computing ◽

Task Scheduling ◽

Security And Reliability ◽

Multi Cloud

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Towards Better Performance for Protected Iris Biometric System with Confidence Matrix

Symmetry ◽

10.3390/sym13050910 ◽

2021 ◽

Vol 13 (5) ◽

pp. 910

Author(s):

Tong-Yuen Chai ◽

Bok-Min Goi ◽

Wun-She Yap

Keyword(s):

Data Privacy ◽

Recognition Performance ◽

Generalized Solution ◽

Performance Degradation ◽

Public Confidence ◽

Data Types ◽

Privacy And Security ◽

Biometric Data ◽

Biometric Template ◽

Template Protection

Biometric template protection (BTP) schemes are implemented to increase public confidence in biometric systems regarding data privacy and security in recent years. The introduction of BTP has naturally incurred loss of information for security, which leads to performance degradation at the matching stage. Although efforts are shown in the extended work of some iris BTP schemes to improve their recognition performance, there is still a lack of a generalized solution for this problem. In this paper, a trainable approach that requires no further modification on the protected iris biometric templates has been proposed. This approach consists of two strategies to generate a confidence matrix to reduce the performance degradation of iris BTP schemes. The proposed binary confidence matrix showed better performance in noisy iris data, whereas the probability confidence matrix showed better performance in iris databases with better image quality. In addition, our proposed scheme has also taken into consideration the potential effects in recognition performance, which are caused by the database-associated noise masks and the variation in biometric data types produced by different iris BTP schemes. The proposed scheme has reported remarkable improvement in our experiments with various publicly available iris research databases being tested.

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Acceleration of Inner-Pairing Product Operation for Secure Biometric Verification

Sensors ◽

10.3390/s21082859 ◽

2021 ◽

Vol 21 (8) ◽

pp. 2859

Author(s):

Seong-Yun Jeon ◽

Mun-Kyu Lee

Keyword(s):

Mobile Technologies ◽

Smart Devices ◽

Biometric Data ◽

Product Operation ◽

Biometric Verification ◽

Naive Method ◽

Biometric Template ◽

Need To Evaluate ◽

Time Required ◽

Pairing Product

With the recent advances in mobile technologies, biometric verification is being adopted in many smart devices as a means for authenticating their owners. As biometric data leakage may cause stringent privacy issues, many proposals have been offered to guarantee the security of stored biometric data, i.e., biometric template. One of the most promising solutions is the use of a remote server that stores the template in an encrypted form and performs a biometric comparison on the ciphertext domain, using recently proposed functional encryption (FE) techniques. However, the drawback of this approach is that considerable computation is required for the inner-pairing product operation used for the decryption procedure of the underlying FE, which is performed in the authentication phase. In this paper, we propose an enhanced method to accelerate the inner-pairing product computation and apply it to expedite the decryption operation of FE and for faster remote biometric verification. The following two important observations are the basis for our improvement—one of the two arguments for the decryption operation does not frequently change over authentication sessions, and we only need to evaluate the product of multiple pairings, rather than individual pairings. From the results of our experiments, the proposed method reduces the time required to compute an inner-pairing product by 30.7%, compared to the previous best method. With this improvement, the time required for biometric verification is expected to decrease by up to 10.0%, compared to a naive method.

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Biometric template security

SPIE Newsroom ◽

10.1117/2.1200911.001590 ◽

2009 ◽

Cited By ~ 2

Author(s):

Abhishek Nagar

Keyword(s):

Template Security ◽

Biometric Template

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An Efficient and Privacy-Preserving Biometric Identification Scheme Based on the FITing-Tree

Security and Communication Networks ◽

10.1155/2021/2313389 ◽

2021 ◽

Vol 2021 ◽

pp. 1-15

Author(s):

Xiaopeng Yang ◽

Hui Zhu ◽

Songnian Zhang ◽

Rongxing Lu ◽

Xuesong Gao

Keyword(s):

Homomorphic Encryption ◽

Security Analysis ◽

Privacy Preserving ◽

Biometric Identification ◽

Large Dataset ◽

Biometric Data ◽

Communication Costs ◽

Identification Scheme ◽

Biometric Template ◽

Cloud Servers

Biometric identification services have been applied to almost all aspects of life. However, how to securely and efficiently identify an individual in a huge biometric dataset is still very challenging. For one thing, biometric data is very sensitive and should be kept secure during the process of biometric identification. On the other hand, searching a biometric template in a large dataset can be very time-consuming, especially when some privacy-preserving measures are adopted. To address this problem, we propose an efficient and privacy-preserving biometric identification scheme based on the FITing-tree, iDistance, and a symmetric homomorphic encryption (SHE) scheme with two cloud servers. With our proposed scheme, the privacy of the user’s identification request and service provider’s dataset is guaranteed, while the computational costs of the cloud servers in searching the biometric dataset can be kept at an acceptable level. Detailed security analysis shows that the privacy of both the biometric dataset and biometric identification request is well protected during the identification service. In addition, we implement our proposed scheme and compare it to a previously reported M-Tree based privacy-preserving identification scheme in terms of computational and communication costs. Experimental results demonstrate that our proposed scheme is indeed efficient in terms of computational and communication costs while identifying a biometric template in a large dataset.

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