Implementing FingerCode-based identity matching in the encrypted domain

Bianchi, Tiziano; Turchi, Stefano; Piva, Alessandro; Labati, Ruggero Donida; Piuri, Vincenzo; Scotti, Fabio

doi:10.1109/bioms.2010.5610445

Cited by 16 publications

(14 citation statements)

References 11 publications

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“…the quantization processes (12), (13), (31) and (32) will product no quantization error. Without loss of generality, we assume Q is equal to L for rational filter coefficients wavelets in the following.…”

Section: Rational Filter Coefficients Waveletsmentioning

confidence: 98%

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Implementation of the discrete wavelet transform and multiresolution analysis in the encrypted domain

Zheng

Huang

2011

Proceedings of the 19th ACM International Conference on Multimedia

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Signal processing in the encrypted domain is a new technology for protecting valuable signals from insecure signal processing. Although there has been some research in the area, this field of research is still in its infancy.In this paper, we propose a scheme for implementing discrete wavelet transform (DWT) and multi-resolution analysis (MRA) in a homomorphic encrypted domain. We first suggest a framework for performing DWT and inverse discrete wavelet transform (IDWT) in the encrypted domain and then conduct an analysis of data expansion and quantization errors on the framework. In order to solve the problem of data expansion, which is very important in practical applications, we then present a novel method for reducing data expansion in the case that both DWT and IDWT are performed. With the proposed method, multilevel DWT/IDWT can be performed with less data expansion in a homomorphic encrypted domain. We address the case of a two-dimensional Haar wavelet transform and give some experiments to demonstrate the advantages of our improved method. To the best of our knowledge, this is the first paper on the implementation of DWT and MRA in the encrypted domain.

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Section: Rational Filter Coefficients Waveletsmentioning

confidence: 98%

“…In [11] [12], the authors proposed schemes for privacy-preserving face recognition by using the Paillier cryptosystem. A finger code-based identity-matching algorithm in the encrypted domain is presented in [13].…”

Section: Introductionmentioning

confidence: 99%

Implementation of the discrete wavelet transform and multiresolution analysis in the encrypted domain

Zheng

Huang

2011

Proceedings of the 19th ACM International Conference on Multimedia

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“…However, the experimental result demonstrated that FingerCode of dimensions 96 (from tesselation reduction) and 8 (from PCA) can achieve a satisfactory accuracy compared to that of the original 640. We also note that the approaches in [3] quantized each entry in FingerCode resulting a reduced accuracy. However, our proposed TPE scheme can be directly utilized to real numbers.…”

Section: ) Dimension Reductionmentioning

confidence: 99%

PassBio: Privacy-Preserving User-Centric Biometric Authentication

Zhou

Ren

2018

IEEE Trans.Inform.Forensic Secur.

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The proliferation of online biometric authentication has necessitated security requirements of biometric templates. The existing secure biometric authentication schemes feature a server-centric model, where a service provider maintains a biometric database and is fully responsible for the security of the templates.The end-users have to fully trust the server in storing, processing and managing their private templates.As a result, the end-users' templates could be compromised by outside attackers or even the service provider itself. In this paper, we propose a user-centric biometric authentication scheme (PassBio) that enables end-users to encrypt their own templates with our proposed light-weighted encryption scheme.During authentication, all the templates remain encrypted such that the server will never see them directly. However, the server is able to determine whether the distance of two encrypted templates is within a pre-defined threshold. Our security analysis shows that no critical information of the templates can be revealed under both passive and active attacks. PassBio follows a "compute-then-compare" computational model over encrypted data. More specifically, our proposed Threshold Predicate Encryption (TPE) scheme can encrypt two vectors x and y in such a manner that the inner product of x and y can be evaluated and compared to a pre-defined threshold. TPE guarantees that only the comparison result is revealed and no key information about x and y can be learned. Furthermore, we show that TPE can be utilized as a flexible building block to evaluate different distance metrics such as Hamming distance and Euclidean distance over encrypted data. Such a compute-then-compare computational model, enabled by TPE, can be widely applied in many interesting applications such as searching over encrypted data while ensuring data security and privacy. Index TermsBiometric authentication, data security and privacy, computation over encrypted data, predicate encryption, inner product encryptionThe authors are with the

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“…Barni et al [22] present a way to protect fixed-length fingercodes [31] using homomorphic encryption. This system was modified in [32] to accelerate the process by reducing the size of the fingercode. However, a reduction of information also leads to a degradation of biometric recognition performance.…”

Section: Related Workmentioning

confidence: 99%

Homomorphic Encryption for Speaker Recognition: Protection of Biometric Templates and Vendor Model Parameters

Nautsch¹,

Isadskiy²,

Kolberg³

et al. 2018

The Speaker and Language Recognition Workshop (Odyssey 2018)

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Data privacy is crucial when dealing with biometric data. Accounting for the latest European data privacy regulation and payment service directive, biometric template protection is essential for any commercial application. Ensuring unlinkability across biometric service operators, irreversibility of leaked encrypted templates, and renewability of e.g., voice models following the i-vector paradigm, biometric voice-based systems are prepared for the latest EU data privacy legislation. Employing Paillier cryptosystems, Euclidean and cosine comparators are known to ensure data privacy demands, without loss of discrimination nor calibration performance. Bridging gaps from template protection to speaker recognition, two architectures are proposed for the two-covariance comparator, serving as a generative model in this study. The first architecture preserves privacy of biometric data capture subjects. In the second architecture, model parameters of the comparator are encrypted as well, such that biometric service providers can supply the same comparison modules employing different key pairs to multiple biometric service operators. An experimental proof-of-concept and complexity analysis is carried out on the data from the 2013 -2014 NIST i-vector machine learning challenge.

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Implementing FingerCode-based identity matching in the encrypted domain

Cited by 16 publications

References 11 publications

Implementation of the discrete wavelet transform and multiresolution analysis in the encrypted domain

Implementation of the discrete wavelet transform and multiresolution analysis in the encrypted domain

PassBio: Privacy-Preserving User-Centric Biometric Authentication

Homomorphic Encryption for Speaker Recognition: Protection of Biometric Templates and Vendor Model Parameters

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