The disruptive technology of blockchain can deliver secure solutions without the need for a central authority. In blockchain, assets that belong to a participant are controlled through the private key of an asymmetric key pair that is owned by the participant. Although, this lets blockchain network participants to have sovereignty on their assets, it comes with the responsibility of managing their own keys. Currently, there exists two major bottlenecks in managing keys; @math users don't have an efficient and secure way to store their keys, @math no efficient recovery mechanism exists in case the keys are lost. In this study, we propose secure methods to efficiently store and recover keys. For the first, we introduce an efficient encryption mechanism to securely encrypt and decrypt the private key using the owner's biometric signature. For the later, we introduce an efficient recovery mechanism using biometrics and secret sharing scheme. By applying the proposed key encryption and recovery mechanism, asset owners are able to securely store their keys on their devices and recover the keys in case they are lost.
@cite_24: This paper considers signals from the cardiovascular system for possible use in biometric authentication. The signals of particular interest here derive from photoplethysmography (PPG), which refers to the use of illumination-based sensors that are sensitive to volumetric changes as blood travels through the body. Photoplethysmography sensors have been developed for the fingertip and the ear lobe, and they provide a convenient, noninvasive means of measuring heart rate and heart-rate variability. We demonstrate in this paper that PPG-based signals also have the potential to be used for biometric authentication, even though PPG signals appear to convey much less information than their electromagnetic counterparts, electrocardiograms (ECG). Through a novel decomposition into a sum-of-Gaussians representation, we present experimental results that indicate rank-1 accuracies of 90 and 95 with 2 seconds and 8 seconds of PPG test signal data, respectively. To our knowledge, this paper is the first to demonstrate robust PPG-based authentication for subjects with different emotional states.
@cite_14: Biometric data offer a potential source of high-entropy, secret information that can be used in cryptographic protocols provided two issues are addressed: (1) biometric data are not uniformly distributed; and (2) they are not exactly reproducible. Recent work, most notably that of Dodis, Reyzin, and Smith, has shown how these obstacles may be overcome by allowing some auxiliary public information to be reliably sent from a server to the human user. Subsequent work of Boyen has shown how to extend these techniques, in the random oracle model, to enable unidirectional authentication from the user to the server without the assumption of a reliable communication channel. We show two efficient techniques enabling the use of biometric data to achieve mutual authentication or authenticated key exchange over a completely insecure (i.e., adversarially controlled) channel. In addition to achieving stronger security guarantees than the work of Boyen, we improve upon his solution in a number of other respects: we tolerate a broader class of errors and, in one case, improve upon the parameters of his solution and give a proof of security in the standard model.
@cite_10: Personal identification numbers, passwords, smart cards and digital certificates are some of the means employed for user authentication in various electronic commerce applications. However, these means do not really identify a person, but only knowledge of some data or belonging of some determined object. This paper introduces the notion of biometric signature – a new approach to integrate biometrics with public key infrastructure, using biometric based digital signature generation which is secure, efficacious, fast, convenient, non‐invasive and correctly identifies the maker of a transaction. It also suggests two schemes for biometric signature using two existing and widely used digital signature algorithms, RSA and DSA, and discusses the problems associated with them individually. Speed of both schemes (based on iris recognition) is measured and compared with the help of JAVA implementation for both approaches.
@cite_3: In this study, a generic treatment of how to generate biometric keys from binary biometric templates is presented. A context-based analysis of iris biometric feature vectors based on which stable biometric keys are extracted is proposed. Most reliable bits in binary iris codes are detected and utilised to construct keys from fuzzy biometric data. The proposed key-generation scheme is adapted to diverse iris biometric feature extraction algorithms, evaluated on a comprehensive database and compared against existing iris biometric cryptosystems. In addition, the scheme is extended to provide fully revocable biometric keys, long enough to be applied in generic cryptosystems. Experimental results confirm the soundness of the approach.
There are very few studies that integrate biometric traits into RSA keys. In his study, Je-Gyeong proposed a method for generating keys of digital signature (public and private key) from biometric. Some others investigated Iris texture as a biometric feature for generating cryptographic key. Rathgeb and Andreas proposed an approach using bits of the iris code for deriving biometric cryptographic key @cite_3 . Janbandhu et.al derives signature keys from the code generated by using the 512 byte iris biometric data invented by the work done by J. Daugman @cite_10 . Similarly, study by also considers the iris texture as biometric trait @cite_14 . In the study by Sarkar et. al, biometric authentication was used for obtaining asymmetric cryptography keys @cite_24 .