| Title | A Secure and Practical Sample-then-lock Scheme for Iris Recognition |
| Publication Type | Conference Paper |
| Year of Publication | 2022 |
| Authors | Zhu, Feng, Shen, Peisong, Chen, Kaini, Ma, Yucheng, Chen, Chi |
| Conference Name | 2022 26th International Conference on Pattern Recognition (ICPR) |
| Keywords | codes, cryptography, Entropy, Force, Human Behavior, pattern locks, Pattern recognition, pubcrawl, resilience, Resiliency, Resists, Scalability, Stability analysis |
| Abstract | Sample-then-lock construction is a reusable fuzzy extractor for low-entropy sources. When applied on iris recognition scenarios, many subsets of an iris-code are used to lock the cryptographic key. The security of this construction relies on the entropy of subsets of iris codes. Simhadri et al. reported a security level of 32 bits on iris sources. In this paper, we propose two kinds of attacks to crack existing sample-then-lock schemes. Exploiting the low-entropy subsets, our attacks can break the locked key and the enrollment iris-code respectively in less than 220 brute force attempts. To protect from these proposed attacks, we design an improved sample-then-lock scheme. More precisely, our scheme employs stability and discriminability to select high-entropy subsets to lock the genuine secret, and conceals genuine locker by a large amount of chaff lockers. Our experiment verifies that existing schemes are vulnerable to the proposed attacks with a security level of less than 20 bits, while our scheme can resist these attacks with a security level of more than 100 bits when number of genuine subsets is 106. |
| Notes | ISSN: 2831-7475 |
| DOI | 10.1109/ICPR56361.2022.9956077 |
| Citation Key | zhu_secure_2022 |
A Secure and Practical Sample-then-lock Scheme for Iris Recognition