Alignment-free indexing-first-one hashing with bloom filter integration

Lai, Yen-Lung; Goi, Bok‐Min; Chai, Tong-Yuen

doi:10.1109/isi.2017.8004878

Cited by 7 publications

(8 citation statements)

References 13 publications

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“…Tables show that our second scheme is about 15 times faster than our first scheme and the Dwivedi et al 's scheme. And our second scheme is about 22 times faster than alignment-free IFO [15].…”

Section: Execution Time For Matchingmentioning

confidence: 92%

“…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%

“…We have compared the matching time of our schemes with the Dwivedi et al 's scheme and alignment-free IFO in [15] (see Table 4). Tables show that our second scheme is about 15 times faster than our first scheme and the Dwivedi et al 's scheme.…”

Section: Execution Time For Matchingmentioning

confidence: 99%

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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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Section: Execution Time For Matchingmentioning

confidence: 92%

Section: S-iriscode Encoding Was Proposed In 2006 Bymentioning

confidence: 99%

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Efficient Cancelable Iris Template Generation for Wearable Sensors

Jeong

2019

Security and Communication Networks

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“…Our proposed scheme incorporated Bloom filter [49] and Indexing First One hashing (IFO) [55] for the purpose of alignment-free biometric template generation, as explained in our recent work [56]. Thus, a brief introduction about IFO and Bloom filter are given to facilitate the understanding of our proposed scheme in the methodology section.…”

Section: Cancelable Biometricsmentioning

confidence: 99%

A New Design for Alignment-Free Chaffed Cancelable Iris Key Binding Scheme

et al. 2019

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Iris has been found to be unique and consistent over time despite its random nature. Unprotected biometric (iris) template raises concerns in security and privacy, as numerous large-scale iris recognition projects have been deployed worldwide—for instance, susceptibility to attacks, cumbersome renewability, and cross-matching. Template protection schemes from biometric cryptosystems and cancelable biometrics are expected to restore the confidence in biometrics regarding data privacy, given the great advancement in recent years. However, a majority of the biometric template protection schemes have uncertainties in guaranteeing criteria such as unlinkability, irreversibility, and revocability, while maintaining significant performance. Fuzzy commitment, a theoretically secure biometric key binding scheme, is vulnerable due to the inherent dependency of the biometric features and its reliance on error correction code (ECC). In this paper, an alignment-free and cancelable iris key binding scheme without ECC is proposed. The proposed system protects the binary biometric data, i.e., IrisCodes, from security and privacy attacks through a strong and size varying non-invertible cancelable transform. The proposed scheme provides flexibility in system storage and authentication speed via controllable hashed code length. We also proposed a fast key regeneration without either re-enrollment or constant storage of seeds. The experimental results and security analysis show the validity of the proposed scheme.

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“…In other words, most of the good iris BTP schemes which provide stronger security features will expect weaker performance as the main drawback. Knowing the effect of this tradeoff, there are also efforts by respective iris BTP schemes [8,9] to introduce remedies such as optimizing the selection of parameters and some of the steps to mitigate the performance degradation. It is a non-trivial task to offer a security guaranty to a biometric template while preserving the recognition rate, which is viewed as one of the major requirements in designing an iris BTP scheme.…”

Section: Introductionmentioning

confidence: 99%

Towards Better Performance for Protected Iris Biometric System with Confidence Matrix

2021

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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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Alignment-free indexing-first-one hashing with bloom filter integration

Cited by 7 publications

References 13 publications

Efficient Cancelable Iris Template Generation for Wearable Sensors

Efficient Cancelable Iris Template Generation for Wearable Sensors

A New Design for Alignment-Free Chaffed Cancelable Iris Key Binding Scheme

Towards Better Performance for Protected Iris Biometric System with Confidence Matrix

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