An efficient and lossless fingerprint encryption algorithm using Henon map &amp;amp; Arnold transformation

Mehta, Garima; Dutta, Malay Kishore; Karasek, Jan; Kim, Pyung Soo

doi:10.1109/iccc.2013.6731703

Cited by 21 publications

(9 citation statements)

References 6 publications

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“…Biometric templates are very important and hence, there is need to keep them from all forms of attacks which can cause corruption or abuse [12]. Biometric template protection ensures the security of biometric templates at both network and database levels [13] and it therefore important to discuss some of the significant efforts that have been expended on the capability of BioHashing and Arnold transform schemes for protecting and securing biometric templates.…”

Section: Related Workmentioning

confidence: 99%

A Fingerprint Template Protection Scheme Using Arnold Transform and Bio-hashing

Onifade¹,

Olayemi²,

Isinkaye³

2020

IJIGSP

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Fingerprint biometric is popularly used for protecting digital devices and applications. They are better and more reliable for authentication in comparison to the usual security tokens or password, which make them to be at the forefront of identity management systems. Though, they have several security benefits, there are several weaknesses of the fingerprint biometric recognition system. The greatest challenge of the fingerprint biometric system is theft or leakage of the template information. Also, each individual has limited and unique fingerprint which is permanent throughout their lifespan, hence, the compromise of the fingerprint biometric will cause a lifetime threat to the security and privacy of such an individual. Security and privacy risk of fingerprint biometric have previously been studied in the context of cryptosystem and cancelable biometric generation. However, these approaches do not obviously address the issue of revocability, diversity and irreversibility of fingerprint features to guard against the wrong use or theft of fingerprint biometric information. In this paper, we proposed a model that harnesses the strength of Arnold transform and Bio-hashing on fingerprint biometric features to overcome the limitations commonly encountered in sole fingerprint biometric approaches. In the experimental analysis, the result of irreversibility showed 0% False Acceptance Rate (FAR), performance showed maximum of 0.2% FAR and maximum of 0.8% False Rejection Rate (FRR) at different threshold values. Also, the result of renewability/revocability at SMDKAB SMKADKB and SMKBDKA showed that the protection did not match each other. Therefore, the performance of the proposed model was notable and the techniques could be efficiently and reliably used to enforce protection on biometric templates in establishments/organizations so that their information and processes could be secured.

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Section: Related Workmentioning

confidence: 99%

A Fingerprint Template Protection Scheme Using Arnold Transform and Bio-hashing

Onifade¹,

Olayemi²,

Isinkaye³

2020

IJIGSP

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“…It is to show that encrypted template's images are fully meaningless and make it difficult for the attackers to retrieve any important data relating to the original image. Therefore, 28 dB is the maximum threshold of PSNR value needed for similarity between original and encrypted biometric template [27]. Low PSNR (Peak Signal to Noise Ratio) indicates a high variation between the encrypted template and original.…”

Section: Peak Signal To Noise Ratio (Psnr)mentioning

confidence: 99%

“…For example, correlation coefficients should ensure the value is between 0.75 -1.00 for the original image and less than 0.1 for the encrypted image. If the correlation is zero, the original and encrypted images are totally not the same [27]. A negative correlation shows that for any two variables x and y, an increase in x is associated with a decrease in y.…”

Section: Correlation Coefficientmentioning

confidence: 99%

Security performance evaluation of biometric lightweight encryption for fingerprint template protection

Ghazali¹,

Zakaria²

2019

IJACR

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Due to its accuracy and convenience, the fingerprint is one of the most reliable biometric-based authentication methods for personal identification and providing access control to many applications. However, previous studies have shown that, the fingerprint template is exposed to threat in which the attackers can steal and modified the template to acquire illegal authorization. Therefore, a technique to protect the biometric template has been proposed. The proposed technique involved the biometric template binding by advanced encryption standard (AES-128) key algorithm, which is to provide confidentiality alongside with the offset codebook mode (OCB), an authenticated encryption (AE) mode to provide integrity. Hence, this paper intends to evaluate the security performance of the proposed technique. Three parameters will be analysed which are peak signal to noise ratio (PSNR), correlation coefficient and histogram. The efficiency of the proposed technique is measured by the standard of its capability to hide all the information by correlating the relationship between the original and encrypted biometric image using PSNR, correlation coefficient and histogram analysis. The experimental results show good security performance in the given parameters.

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“…Arnold cat map is a two dimensional chaotic map employing shearing and wrapping operation to generate a scrambled matrix [8] after several iterations.…”

Section: Arnold Cat Mapmentioning

confidence: 99%

An efficient & secure encryption scheme for biometric data using holmes map & singular value decomposition

Mehta

Dutta

Kim

2014

2014 International Conference on Medical Imaging, M-Health and Emerging Communication Systems (MedCom)

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In the recent past we have been facing security challenges towards the transmission of biometric data over unsecured data channels. A lot of techniques have been developed and implemented for the secure transmission of the data. Taking the security concept in mind we introduce an efficient method based on chaotic theory for secured data transmission. The core idea of the proposed method is to shuffle the adjacent pixel correlation using the combination of Arnold Cat Map, Holmes Map and Singular Value Decomposition (SVD). The pixel values are scrambled using the Arnold Cat Map and further Holmes Map and SVD are used to alter the pixel values to complicate the relationship. Finally, decryption method is proposed to reconstruct the original data from encrypted data. Performance of proposed algorithm has been experimentally analyzed using statistical attack analysis, key sensitivity analysis and Peak Signal to Noise Ratio (PSNR). Experimental results shows that the proposed algorithm is lossless in nature, robust against statistical attacks and has high key sensitivity. Further low PSNR values indicate that the proposed algorithm provides a high level of perceptual security for the biometric data.

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An efficient and lossless fingerprint encryption algorithm using Henon map & Arnold transformation

Cited by 21 publications

References 6 publications

A Fingerprint Template Protection Scheme Using Arnold Transform and Bio-hashing

A Fingerprint Template Protection Scheme Using Arnold Transform and Bio-hashing

Security performance evaluation of biometric lightweight encryption for fingerprint template protection

An efficient & secure encryption scheme for biometric data using holmes map & singular value decomposition

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An efficient and lossless fingerprint encryption algorithm using Henon map &amp; Arnold transformation

Cited by 21 publications

References 6 publications

A Fingerprint Template Protection Scheme Using Arnold Transform and Bio-hashing

A Fingerprint Template Protection Scheme Using Arnold Transform and Bio-hashing

Security performance evaluation of biometric lightweight encryption for fingerprint template protection

An efficient &amp; secure encryption scheme for biometric data using holmes map &amp; singular value decomposition

Contact Info

Product

Resources

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An efficient and lossless fingerprint encryption algorithm using Henon map & Arnold transformation

An efficient & secure encryption scheme for biometric data using holmes map & singular value decomposition