Iris Cancellable Template Generation Based on Indexing-First-One Hashing

Lai, Yen-Lung; Jin, Zhe; Goi, Bok‐Min; Chai, Tong-Yuen; Yap, Wun‐She

doi:10.1007/978-3-319-46298-1_29

Cited by 20 publications

(23 citation statements)

References 15 publications

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“…Afterward, a permutation strategy is embedded to the iris template protection scheme based on Bloom filters to prevent cross-matching and achieve the unlinkability in [38]. In [39], Lai et al proposed a cancelable iris biometric based on the Indexing-First-One (IFO) hashing, which is inspired by the Min-hashing. They employed the P-order Hadamard product and modulo threshold function in IFO hashing to realize noninvertible transform.…”

Section: Related Workmentioning

confidence: 99%

Iris Template Protection Based on Local Ranking

Zhao

Fang

Xiang

et al. 2018

Security and Communication Networks

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Biometrics have been widely studied in recent years, and they are increasingly employed in real-world applications. Meanwhile, a number of potential threats to the privacy of biometric data arise. Iris template protection demands that the privacy of iris data should be protected when performing iris recognition. According to the international standard ISO/IEC 24745, iris template protection should satisfy the irreversibility, revocability, and unlinkability. However, existing works about iris template protection demonstrate that it is difficult to satisfy the three privacy requirements simultaneously while supporting effective iris recognition. In this paper, we propose an iris template protection method based on local ranking. Specifically, the iris data are first XORed (Exclusive OR operation) with an application-specific string; next, we divide the results into blocks and then partition the blocks into groups. The blocks in each group are ranked according to their decimal values, and original blocks are transformed to their rank values for storage. We also extend the basic method to support the shifting strategy and masking strategy, which are two important strategies for iris recognition. We demonstrate that the proposed method satisfies the irreversibility, revocability, and unlinkability. Experimental results on typical iris datasets (i.e., CASIA-IrisV3-Interval, CASIA-IrisV4-Lamp, UBIRIS-V1-S1, and MMU-V1) show that the proposed method could maintain the recognition performance while protecting the privacy of iris data.

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Section: Related Workmentioning

confidence: 99%

Iris Template Protection Based on Local Ranking

Zhao

Fang

Xiang

et al. 2018

Security and Communication Networks

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“…In 2013 Rathgeb et al suggested a method using bloom filters [12], and another method using two bloom filters was suggested in [13]. In 2017 Lai et al suggested Indexing-First-One hashing, which generates a cancelable template using min-hashing, permutation, Hadamard product, and modulo thresholding of [14], and another alignment-free scheme using bloom filter and Indexing-First-One hashing [15]. Finally, in 2017 Dwivedi et al suggested a novel method using look-up table mapping [6].…”

Section: S-iriscode Encoding Was Proposed In 2006 Bymentioning

confidence: 99%

“…Revocability. The revocability can be proved through the genuine, imposter, and pseudo-imposter scores distribution [14]. The genuine and imposter scores are defined as the same in section Experimental Comparisons.…”

Section: Security Analysismentioning

confidence: 99%

Efficient Cancelable Iris Template Generation for Wearable Sensors

Jeong

2019

Security and Communication Networks

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When biometric authentication is performed on On-Body Wearable Wireless Networks, a cancelable template is useful to protect biometric information. A cancelable template generation method converts the original biometric information into irreversibly transformed information to protect the original biometric information. If a cancelable template is damaged or leaked, it can be replaced with another cancelable template. In 2017, Dwivedi et al. proposed a novel cancelable iris template generation scheme based on the randomized look-up table mapping. So far their scheme is the most accurate scheme with respect to EER compared to the previous cancelable iris template generation schemes. However, their scheme is not alignment-free and so is not efficient enough for wearable sensors. In the paper, we first suggest how to improve the accuracy of the Dwivedi et al.’s scheme using the partial sort technique. Our experiment result shows that our suggested scheme is more accurate than the Dwivedi et al.’s scheme under almost all parameter settings. More concretely, our scheme achieves EER 0.09%, whereas the Dwivedi et al.’s scheme achieves EER 0.43% in the best parameter settings for the CASIA-V3-Interval iris database. We also suggest how to improve the efficiency of the Dwivedi et al.’s scheme. Our second scheme is alignment-free by processing IrisCode column-wise, whereas the Dwivedi et al.’s scheme handles IrisCode row-wise. Our experiment shows that our second scheme is 15 times faster than the Dwivedi et al.’s scheme, so our scheme is efficient enough for wearable sensors. Though our second scheme has very high EER under some parameter settings, our second scheme achieves EER 0.53% in the best parameter settings for the CASIA-V3-Interval iris database.

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“…Thus, recently developed non-invertible transforms that are providing good recognition performance and privacy protection, e.g. Bloom Filters [41] or Indexing-First-One (IFO) hashing [25] (both are adoptable for finger vein biometrics in principle)…”

Section: Introductionmentioning

confidence: 99%

Finger Vein Template Protection Based on Alignment-Robust Feature Description and Index-of-Maximum Hashing

Kirchgasser

Kauba

Lai

et al. 2020

IEEE Trans. Biom. Behav. Identity Sci.

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Privacy preserving storage and secure processing of biometric data is a key issue that has to be addressed in finger vein recognition systems as well. Various template protection approaches originally proposed for well established biometric modalities have been adopted to the domain of finger vein authentication. However, these adopted methods have the disadvantage that they are not designed for finger vein patterns in particular and are thus, sub-optimal in several ways. In this study we propose an alignment-robust template protection scheme that is based on an efficient binary representation of finger vein patterns on the one hand and is further using the advantages of Index-of-Maximum (IoM) hashing to fulfill mandatory privacy and security based characteristics on the other hand. The proposed method is compared to block re-mapping and warping regarding recognition performance and is analyzed with respect to security and privacy aspects. The analysis is further extended to robustness against misalignment of the finger vein data and a combination of block re-mapping/warping and the proposed method is investigated as well.

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Iris Cancellable Template Generation Based on Indexing-First-One Hashing

Cited by 20 publications

References 15 publications

Iris Template Protection Based on Local Ranking

Iris Template Protection Based on Local Ranking

Efficient Cancelable Iris Template Generation for Wearable Sensors

Finger Vein Template Protection Based on Alignment-Robust Feature Description and Index-of-Maximum Hashing

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