A privacy-preserving cancelable iris template generation scheme using decimal encoding and look-up table mapping

Dwivedi, Rudresh; Dey, Somnath; Singh, Ramveer; Prasad, Aditya

doi:10.1016/j.cose.2016.10.004

Cited by 53 publications

(33 citation statements)

References 12 publications

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“…Dwivedip et al [15] exploit the concept of randomized look-up table mapping for the generation of cancelable iris template. After pre-processing of iris images, the feature vectors are generated in binary matrix form using a 1-D Log Gabor filter.…”

Section: Related Workmentioning

confidence: 99%

Cancelable Face Template Protection using Transform Features for Cyberworld Security

Kausar¹

2020

IJACSA

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Cyber world becomes a fundamental and vital component of the physical world with the increase of dependence on internet-connected devices in industry and government organizations. Provision of privacy and security of users during online communication offers unique cybersecurity challenges for industry and government. Intrusion is one of the crucial issues of cybersecurity, which can be overcome by providing the vigorous authentication solutions. Biometrics authentication is used in different cybersecurity systems for user authentication purpose. The cancelable biometric is a solution to rid of privacy problems in traditional biometric systems. This paper purposes a new cancelable face authentication method, which uses Hybrid Gabor PCA (HGPCA) descriptor for cyberworld security. The proposed method uses the wavelet transform for the extraction of the features of the face images by using Gabor filter and Principal Component Analysis (PCA). Later, both types of features have been ensemble by using the simple concatenation scheme. Then scrambling has been applied to the fused features by using the random key generated by the user. So finally, scrambled fused features has been stored in the database which are used for the cancelable biometric authentication as well as recovery. HGPCA achieves "cancelability" and increases the authentication accuracy. The proposed method has been tested on three standard face datasets. Experimental results of the proposed method have been compared with existing methods by using standard quantitative measures that show superiority over existing methods.

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Section: Related Workmentioning

confidence: 99%

Cancelable Face Template Protection using Transform Features for Cyberworld Security

Kausar¹

2020

IJACSA

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“…Dwivedi et al [40] proposed a secrecy-protective cancelable irises template encoding and a new cancelable iris template on arbitrarily look-up table drawing. The method uses a number vector created from a changing-invariant character vector using 1-D Log Gabor filter usable to the iris picture.…”

Section: A Vulnerabilities Attacks Of Biometric Template In the Datamentioning

confidence: 99%

Developing an Algorithm for Securing the Biometric Data Template in the Database

Habibu¹,

Luhanga²,

Sam³

2019

IJACSA

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In the current technology advancement, biometric template provides a dependable solution to the problem of user verification in an identity control system. The template is saved in the database during the enrollment and compared with query information in the verification stage. Serious security and privacy concerns can arise, if raw, unprotected data template is saved in the database. An attacker can hack the template information in the database to gain illicit access. A novel approach of encryption-decryption algorithm utilizing a design pattern of Model View Template (MVT) is developed to secure the biometric data template. The model manages information logically, the view shows the visualization of the data, and the template addresses the data migration into pattern object. The established algorithm is based on the cryptographic module of the Fernet key instance. The Fernet keys are combined to generate a multiFernet key to produce two encrypted files (byte and text file). These files are incorporated with Twilio message and securely preserved in the database. In the event where an attacker tries to access the biometric data template in the database, the system alerts the user and stops the attacker from unauthorized access, and cross-verify the impersonator based on the validation of the ownership. Thus, helps inform the users and the authority of, how secure the individual biometric data template is, and provided a high level of the security pertaining the individual data privacy.

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“…The comparison between cancelable enrolled and cancelable query template is performed to evaluate match scores for iris and fingerprint biometric. To derive cancelable templates for iris and fingerprint, we apply the similar methodology proposed in our earlier work [10,8]. For reader's clarity, we briefly describe the template generation methods for both modalities.…”

Section: Score Computationmentioning

confidence: 99%

“…In a nutshell, we extend this work in the following aspect as compared to our previous work. In this work, we utilize our previous works [10,8] to derive cancelable template for iris and fingerprint. Next, we apply the mean-closure weighting (MCW) to combine scores from individual matchers corresponding to one particular biometric modality.…”

Section: Introductionmentioning

confidence: 99%

A novel hybrid score level and decision level fusion scheme for cancelable multi-biometric verification

Dwivedi

Dey

2018

Appl Intell

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In spite of the benefits of biometric-based authentication systems, there are few concerns raised because of the sensitivity of biometric data to outliers, low performance caused due to intra-class variations and privacy invasion caused by information leakage. To address these issues, we propose a hybrid fusion framework where only the protected modalities are combined to fulfill the requirement of secrecy and performance improvement. This paper presents a method to integrate cancelable modalities utilizing mean-closure weighting (MCW) score level and Dempster-Shafer (DS) theory based decision level fusion for iris and fingerprint to mitigate the limitations in the individual score or decision fusion mechanisms. The proposed hybrid fusion scheme incorporates the similarity scores from different matchers corresponding to each protected modality. The individual scores obtained from different matchers for each modality are combined using MCW score fusion method. The MCW technique achieves the optimal weight for each matcher involved in the score computation. Further, DS theory is applied to the induced scores to output the final decision. The rigorous experimental evaluations on three virtual databases indicate that the proposed hybrid fusion framework outperforms over the component level or individual fusion methods (score level and decision level fusion). As a result, we achieve (48%,66%), (72%,86%) and (49%,38%) of performance improvement over unimodal cancelable iris and unimodal cancelable fingerprint verification systems for Virtual A, Virtual B and Virtual C databases, respectively. Also, the proposed method is robust enough to the variability of scores and outliers satisfying the requirement of secure authentication.

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A privacy-preserving cancelable iris template generation scheme using decimal encoding and look-up table mapping

Cited by 53 publications

References 12 publications

Cancelable Face Template Protection using Transform Features for Cyberworld Security

Cancelable Face Template Protection using Transform Features for Cyberworld Security

Developing an Algorithm for Securing the Biometric Data Template in the Database

A novel hybrid score level and decision level fusion scheme for cancelable multi-biometric verification

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