Blockchain technology has attracted a lot of attention in the previous years as a secure way to protect transactions in different processes. It has been particularly used to define cryptocurrencies. While inherently secure against classical single node attacks, the blockchain cryptocurrencies have recently been subject to attacks by malwares able to capture a single user wallet and its included keys. In this work we propose the use of biometric cryptosystems to control the access to the wallets on single machines. After a brief description of the blockchain, the cryptocurrencies and the possible attacks, the paper describes the use of convolutional neural network face recognition as a tool to extract biometric features that help in a key binding approach to protect the personal data in the wallet. Experiments have been conducted on three independent face datasets and the results obtained are satisfactory. The equal error rate between false acceptance and false rejection is negligible when testing on images from the same dataset used for the training of the convolutional neural network. This generalizes well when experimenting on two other independent datasets. These results prove that face cryptosystems can be used to protect the access on sensitive data existing in the wallets of many cryptocurrencies.
Identity-based mutual authentication and key agreement (ID-MAKA) between a mobile user and cloud service provider is necessary for accessing any cloud services. In recent years, there are a large number of ID-MAKA schemes had been proposed on mobile cloud computing services to make authentication and accessing process more usability, security, and scalability. In this paper, we propose a new ID-MAKA scheme for mobile cloud computing, which firstly achieves remote biometric-based authentication(remote servers authenticate user's biometrics), single sign-on (a single credential and single registration for accessing multiple servers) and center-less authentication(the registration center does not participate in the access procedure) in one scheme. In order to realize this target, we design a ZK-token based on ECC and cryptographic hash function, and then artfully employ it to introduce the fuzzy extractor technology and zero-knowledge technology into our scheme. Therefore, the user can access multiple cloud computing servers by registering only once in the registration center, and cloud computing servers can complete the biometric-based remote authentication and key agreement for the user without the registration center participating. In this way, our scheme greatly improves usability, scalability, and security compared to other existing solutions. We give a formal security proof for our scheme by using Real-Or-Random(RoR) model and Burrows-Abadi-Needham (BAN) logic to show that the present scheme is secure and security analysis for other known attacks. Finally, according to the experiment result, our scheme has lower computation and communication cost compared with most existing related schemes.
Aiming at the poor encryption effect existing in the data encryption algorithm of e-commerce platform, and the data lost and distorted easily after encrypting, a data encryption algorithm based on blockchain technology is proposed in this paper. By analyzing the symmetric key algorithm and the public key algorithm, the DES encryption algorithm is described in detail. The two related technologies of digital envelopes and message authentication are analyzed to ensure the accuracy of the data and the one time encryption of the data. Based on this, in order to ensure the effectiveness of encryption, the process of asymmetric encryption algorithm based on chaotic sequence of neural network and asymmetric encryption algorithm based on neural network chaotic attractor are analyzed, and the security is tested. While ensuring the accuracy of data, it improves the effect of data encryption and realizes the encryption of e-commerce platform data, which is to realize data encryption algorithm based on blockchain technology. Experimental results show that the~proposed algorithm can encrypt the data of e-commerce platform, and the encryption process is relatively simple, the encryption effect is better, and the accuracy of the encrypted data is relatively high, which provides a theoretical basis for further research of the subject.
Open access
Chaos-based Image/Signal Encryption
Advanced Steganography and Watermarking Techniques
In traditional Chinese medicine, the growth situation of the surface of nails reflects the physiological condition of the human body. Diagnosis by nail can effectively predict and prevent disease. Human nails have a high degree of uniqueness, and it can be used for biometric recognition. In this work, microscope sensor was used to capture the clear image and segment the lunula and nail plate effectively through image preprocessing. Fingernails’ image is managed as the identity authentication. Histogram of oriented gradients and local binary patterns are used to capture the characteristic value. It uses support vector machine and random forest tree for classification. The performance of each feature extraction algorithm was analyzed for the two classifiers and the deep neural network algorithm was used comparatively. Furthermore, the security and privacy of the Internet of Things is still a challenge. This work uses the highly anonymous blockchain technology to effectively protect data privacy and manage each user’s data through the blockchain, in which any change or manipulation can be recorded and tracked, and the data security is improved. Therefore, this article presents a nail analysis management system with the use of microscopy sensor and blockchain.
We introduce a privacy preserving biometrics-based authentication solution by which users can authenticate to different service providers from mobile phones without involving identity providers in the transactions. Authentication is performed via zero-knowledge proof of knowledge, based on a cryptographic identity token that encodes the biometric identifier of the user and a secret provided by the user, making it three-factor authentication. Our approach for generating a unique, repeatable, and revocable biometric identifier from the user’s biometric image is based on a machine learning-based classification technique, which involves the features extracted from the user’s biometric image. We have implemented a prototype of the proposed authentication solution and evaluated our solution with respect to its performance, security, and privacy. The evaluation has been performed on a public data set of face images.
User Authentication and Security Systems
Biometric Identification and Security
Advanced Steganography and Watermarking Techniques
J. S. Hammudoglu, J. Sparreboom, J. I. Rauhamaa, J. K. Faber · 8 authors
We devised a mobile biometric-based authentication system only relying on local processing. Our Android open source solution explores the capability of current smartphones to acquire, process and match fingerprints using only its built-in hardware. Our architecture is specifically designed to run completely locally and autonomously, not requiring any cloud service, server, or permissioned access to fingerprint reader hardware. It involves three main stages, starting with the fingerprint acquisition using the smartphone camera, followed by a processing pipeline to obtain minutiae features and a final step for matching against other locally stored fingerprints, based on Oriented FAST and Rotated BRIEF (ORB) descriptors. We obtained a mean matching accuracy of 55%, with the highest value of 67% for thumb fingers. Our ability to capture and process a finger fingerprint in mere seconds using a smartphone makes this work usable in a wide range of scenarios, for instance, offline remote regions. This work is specifically designed to be a key building block for a self-sovereign identity solution and integrate with our permissionless blockchain for identity and key attestation.
The potential synergies between consumer handheld devices, particularly smartphones and biometric technologies is outlines. The practicalities and challenges for three such technologies - fingerprint, iris and palmprint - are presented. The use of biometrics for personal authentication is discussed, including the use of zero knowledge proof techniques to ensure that the biometric data does not leave the phone. The scope for data theft and breach through spoofing of the original biometric are discussed. Finally the potential impact of this technology synergy on personal privacy is considered.
Ulrich Rührmair, J. L. Martínez-Hurtado, Xiaolin Xu, Christian Kraeh · 8 authors
We discuss the question of how physical statements can be proven over digital communication channels between two parties (a "prover" and a "verifier") residing in two separate local systems. Examples include: (i) "a certain object in the prover's system has temperature X°C", (ii) "two certain objects in the prover's system are positioned at distance X", or (iii) "a certain object in the prover's system has been irreversibly altered or destroyed". As illustrated by these examples, our treatment goes beyond classical security sensors in considering more general physical statements. Another distinctive aspect is the underlying security model: We neither assume secret keys in the prover's system, nor do we suppose classical sensor hardware in his system which is tamper-resistant and trusted by the verifier. Without an established name, we call this new type of security protocol a "virtual proof of reality" or simply a "virtual proof" (VP). In order to illustrate our novel concept, we give example VPs based on temperature sensitive integrated circuits, disordered optical scattering media, and quantum systems. The corresponding protocols prove the temperature, relative position, or destruction/modification of certain physical objects in the prover's system to the verifier. These objects (so-called "witness objects") are prepared by the verifier and handed over to the prover prior to the VP. Furthermore, we verify the practical validity of our method for all our optical and circuit-based VPs in detailed proof-of-concept experiments. Our work touches upon, and partly extends, several established concepts in cryptography and security, including physical unclonable functions, quantum cryptography, interactive proof systems, and, most recently, physical zero-knowledge proofs. We also discuss potential advancements of our method, for example "public virtual proofs" that function without exchanging witness objects between the verifier and the prover.
Open access
Physical Unclonable Functions (PUFs) and Hardware Security
For the cheating problem in group signature,With the discrete logarithm problem and zero-knowledge proof protocol,and combined with the participants'identity,agroup signature scheme without trusted center is presented.In the scheme,there is no trusted key distribution center,and the dealer is also a participant,each participant's secret shadow is composed of participants through the shadow of their own secret calculation to get,the group public key recovery is invisible recovery.The analysis shows that the scheme is safe and efficient.
We present a technique that uses privacy enhancing technologies and biometrics to prevent the unauthorized lending of credentials. Current credential schemes suffer the weakness that issued credentials can be transferred between users. Our technique ensures the biometric identity of the individual executing the Issue and Show protocols of an existing credential system in a manner analogous to the enrollment and verification steps in traditional biometric systems. During Issue we create Pedersen commitments on biometrically derived keys obtained from fuzzy extractors. This issue-time commitment is sealed into the issued credential. During Show a verification-time commitment is generated. Correspondence of keys is verified using a zero-knowledge proof of knowledge. The proposed approach preserves the security of the underlying credential system, protects the privacy of the biometric, and generalizes to multiple biometric modalities. We illustrate the usage of our technique by showing how it can be incorporated into digital credentials and anonymous credentials.
Biometric Identification and Security
User Authentication and Security Systems
Advanced Steganography and Watermarking Techniques
Cryptographic credentials allow user authorizations to be granted and verified. and have such applications as e-Passports, e-Commerce, and electronic cash. This thesis proposes a privacy protecting approach of binding biometrically derived keys to cryptographic credentials to prevent unauthorized lending. Our approach builds on the 2011 work of Adams, offering additional benefits of privacy protection of biometric information, generality on biometric modalities, and performance. Our protocol integrates into Brands’ Digital Credential scheme, and the Anonymous Credentials scheme of Camenisch and Lysyanskaya. We describe a detailed integration with the Digital Credential Scheme and sketch the integration into the Anonymous Credentials scheme. Security proofs for non-transferability, correctness of ownership, and unlinkability are provided for the protocol’s instantiation into Digital Credentials. Our approach uses specialized biometric devices in both the issue and show protocols. These devices are configured with our proposed primitive, the fuzzy ex-tractor indistinguishability adaptor which uses a traditional fuzzy extractor to create and regenerate cryptographic keys from biometric data and IND-CCA2 secure en-cryption protect the generated public data against multiplicity attacks. Pedersen commitments are used to hold the key at issue and show time, and A zero-knowledge proof of knowledge is used to ensure correspondence of key created at issue-time and regenerated at show-time. The above is done in a manner which preserves biometric privacy, as and delivers non-transferability of digital credentials. The biometric itself is not stored or divulged to any of the parties involved in the protocol. Privacy protection in multiple enrollments scenarios is achieved by the fuzzy extractor indistinguishability adapter. The zero knowledge proof of knowledge is used in the showing protocol to prove knowledge of values without divulging them.
In this paper, a novel biometric authentication scheme is proposed, which combines zero-knowledge proof, - protocols and bit commitment scheme. The remote server compares biometric template using committed values, this can keep privacy of user's biometrics. To the best knowledge of us, this is the first scheme which uses - protocols as a basic tool to implement biometric authentication. Compared with the previous schemes, this scheme has advantages as higher security, lower computation complexity and privacy keeping of biometric template.
Biometric Identification and Security
User Authentication and Security Systems
Advanced Steganography and Watermarking Techniques
George Danezis, Markulf Kohlweiss, Benjamin Livshits, Alfredo Rial
Abstract. Nowadays, service providers gather fine-grained data about users to deliver personalized services, for example, through the use of third-party cookies or social network profiles. This poses a threat both to privacy, since the amount of information obtained is excessive for the purpose of customization, and authenticity, because those methods employed to gather data can be blocked and fooled. In this paper we propose privacy-preserving profiling techniques, in which users perform the profiling task locally, reveal to service providers the result and prove its correctness. We address how our approach applies to tasks of both classification and pattern recognition. For the former, we describe client-side profiling based on random forests, where users, based on certified input data representing their activity, resolve a random forest and reveal the classification result to service providers. For the latter, we show how to match a stream of user activity to a regular expression, or how to assign it a probability using a hidden Markov model. Our techniques, based on the use of zero-knowledge proofs, can be composed with other protocols as part of the certification of a larger computation. 1
As the use and deployment of biometrics becomes more widespread throughout the world, so do the privacy and security risks associated with the growing collection, use, disclosure and retention of biometric data. At stake is public trust, or the lack thereof, in biometric systems and the organizations involved. Unlike passwords, biometric data are unique, irrevocable, and variable. Biometric Encryption (BE) is highlighted as a prominent example of Privacy by Design, where privacy is embedded as a core functionality in the biometric system. BE binds a digital key to (or extracts the key from) the biometric. Earlier technical challenges to this new technology, as well as recent advances, are presented. Lastly, an overview is provided of an application using facial recognition in a watch list scenario, known to be the first and largest successful deployment of BE using facial recognition, in a casino context.
Abhilasha Bhargav-Spantzel, Anna Squicciarini, Elisa Bertino, Xiangwei Kong · 5 authors
We present algorithms to reliably generate biometric identifiers from a user's biometric image which in turn is used for identity verification possibly in conjunction with cryptographic keys. The biometric identifier generation algorithms employ image hashing functions using singular value decomposition and support vector classification techniques. Our algorithms capture generic biometric features that ensure unique and repeatable biometric identifiers. We provide an empirical evaluation of our techniques using 2569 images of 488 different individuals for three types of biometric images; namely fingerprint, iris and face. Based on the biometric type and the classification models, as a result of the empirical evaluation we can generate biometric identifiers ranging from 64 bits up to 214 bits. We provide an example use of the biometric identifiers in privacy preserving multi-factor identity verification based on zero knowledge proofs. Therefore several identity verification factors, including various traditional identity attributes, can be used in conjunction with one or more biometrics of the individual to provide strong identity verification. We also ensure security and privacy of the biometric data. More specifically, we analyze several attack scenarios. We assure privacy of the biometric using the one-way hashing property, in that no information about the original biometric image is revealed from the biometric identifier.
Biometric Identification and Security
Advanced Steganography and Watermarking Techniques