A Cancelable Iris- and Steganography-Based User Authentication System for the Internet of Things

Abstract

Remote user authentication for Internet of Things (IoT) devices is critical to IoT security, as it helps prevent unauthorized access to IoT networks. Biometrics is an appealing authentication technique due to its advantages over traditional password-based authentication. However, the protection of biometric data itself is also important, as original biometric data cannot be replaced or reissued if compromised. In this paper, we propose a cancelable iris- and steganography-based user authentication system to provide user authentication and secure the original iris data. Most of the existing cancelable iris biometric systems need a user-specific key to guide feature transformation, e.g., permutation or random projection, which is also known as key-dependent transformation. One issue associated with key-dependent transformations is that if the user-specific key is compromised, some useful information can be leaked and exploited by adversaries to restore the original iris feature data. To mitigate this risk, the proposed scheme enhances system security by integrating an effective information-hiding technique—steganography. By concealing the user-specific key, the threat of key exposure-related attacks, e.g., attacks via record multiplicity, can be defused, thus heightening the overall system security and complementing the protection offered by cancelable biometric techniques.

Optical PTFT Asymmetric Cryptosystem-Based Secure and Efficient Cancelable Biometric Recognition System

“…In [32], a steganography scheme based CBRS for iris templates is presented to preserve user verification and safeguard the original unique iris information for IoT remote access applications. The main benefit of the suggested CBRS is that it integrates the data steganography process to generate the cancelable biometric templates to mitigate the issue of traditional CBRSs that depend on random projection and permutation techniques that are dependent on key-dependent transforms.…”

“…For additional verification for the competence of the suggested algorithm for consistent cancelable recognition model, further comparisons are carried out for contrasting the outcomes of the suggested cancelable system with the recent literature CBRSs in [12,13,15,16,17,21,24,32,33,35,49]. We contrasted the average numerical security assessment of the FAR, EER, AROC, and FRR findings of the suggested CBRS with the previous recent CBRSs in [12,13,15,16,17,21,24,32,33,35,49] as summarized in Table 13. The offered outcomes in Table 13 demonstrated that the FAR, EER, AROC, and FRR of the suggested optical cryptography algorithm based CBRS are superior and highly contrasted as compared to the previous CBRSs.…”

No Soldiers Left Behind: An IoT-Based Low-Power Military Mobile Health System Design

“…Military applications have strict security requirements and therefore require high recognition accuracy. Iris-based recognition systems usually outperform systems using fingerprints or face, thus in this paper, we present an iris recognition system as an example for showing how to perform personal recognition with the iristhis approach is based on [70].…”

“…Ii is in the ranging from 0 to 255. As in the method used in [70], each of these integer values is quantized with the following equation,…”

“…A total of 1153 (=1332-179) samples were included in the experiment to evaluate the system performance through the following three metrics: false acceptance rate (FAR): the proportion of times the system grants access to an unauthorized person, false rejection rate (FRR): the proportion of times the system fails to grant access to an authorized person, and the equal error rate (EER): the value when FAR and FRR are equal. In the experiment, the feature vector extracted from the first iris image of each eye is compared with the rest of the iris images of the same eye to calculate the FRR, while the feature vector extracted from the first iris image of each eye is compared with the feature vector extracted from the first iris image of different eyes to calculate the FAR [70].…”