Ranking-Based Locality Sensitive Hashing-Enabled Cancelable Biometrics: Index-of-Max Hashing

Abstract

Abstract-In this paper, we propose a ranking based locality sensitive hashing inspired two-factor cancelable biometrics, dubbed "Index-of-Max" (IoM) hashing for biometric template protection. With externally generated random parameters, IoM hashing transforms a real-valued biometric feature vector into discrete index (max ranked) hashed code. We demonstrate two realizations from IoM hashing notion, namely Gaussian Random Projection based and Uniformly Random Permutation based hashing schemes. The discrete indices representation nature of IoM hashed codes enjoy several merits. Firstly, IoM hashing empowers strong concealment to the biometric information. This contributes to the solid ground of non-invertibility guarantee. Secondly, IoM hashing is insensitive to the features magnitude, hence is more robust against biometric features variation. Thirdly, the magnitude-independence trait of IoM hashing makes the hash codes being scale-invariant, which is critical for matching and feature alignment. The experimental results demonstrate favorable accuracy performance on benchmark FVC2002 and FVC2004 fingerprint databases. The analyses justify its resilience to the existing and newly introduced security and privacy attacks as well as satisfy the revocability and unlinkability criteria of cancelable biometrics.Index Terms-Fingerprint, cancelable template, Index-of-Max hashing, security and privacy I. INTRODUCTIONATELY, rapid proliferation of biometric applications leads to massive amount of biometric templates. Public worries about the security and privacy of the biometric templates if stolen or compromised. Such concerns are attributed to the strong binding of individuals and privacy, and further complicated by the fact that biometric traits are irrevocable. Given the above threats, a number of proposals have been reported to protect the biometric templates. Generally, the proposals available in the literature can be broadly divided into two categories: feature transformation (or cancelable biometrics) and biometric cryptosystems (biometric encryption). Biometric cryptosystem serves the purpose of either securing the secret using biometric feature (key binding) or generating the secret directly from the biometric feature (key generation). On the other hand, cancelable biometrics [1] is truly meant for biometric template protection. It refers to the irreversible transform that can alter the biometric templates such that security and privacy of the templates can be assured. If a cancelable template is compromised, a new template can be re-generated from the same biometrics.The cancelable biometric schemes in the literature vary according to different biometric modalities. However, the operation of a general cancelable biometrics system is similar to the conventional biometric system where the system composes of sensor, feature extractor and matcher except the former includes a parameterized transformation function right after feature extractor, and the matching is done in the transformed domain, rather in the feature doma...

Symmetric keyring encryption scheme for biometric cryptosystem

“…A total number of 4950 trials for imposter attempts and 2800 trials for genuine attempts were recorded. However, because different nonce is used, we named the genuine attempt (under same subject) as pseudo imposter attempt follows [19]. Figure 3 shows the pseudo imposter score and imposter score, which corresponds to the normalized genuine pairs count.…”

Evaluating biometrics fingerprint template protection for an emergency situation

“…According to the international standard ISO/IEC 24745: biometric information protection, the biometric template protection schemes must meet these properties: irreversibility, unlinkability, revocability and performance [5]. The irreversibility means the reconstruction from the protected biometric template to the original image or the biometric sample, should be difficult.…”

Enhancing the Security of Transformation Based Biometric Template Protection Schemes

“…A complete review of cancelable biometric systems can be found in [17]. Very recently, Teoh et al [10] proposed a new two-factor scheme to protect the biometric template by transformation. Compared with previous works, this method is based on localized random projection and on the rank correlation.…”

“…These particular biometric systems must of course address classical issues such as a high level of performance (i.e., minimizing the Equal Error Rate (EER) or Area Under the Curve (AUC) value of the system) but also new constraints concerning privacy. In the literature, many papers have been published dealing with the definition of new schemes for the protection of biometric templates (such as those presented in [2], [10], [21], [29]).…”