Oscar Delgado-Mohatar, Julián Fiérrez, Rubén Tolosana, Rubén Vera-Rodríguez
Blockchain technologies provide excellent architectures and practical tools for securing and managing the sensitive and private data stored in biometric templates, but at a cost. We discuss opportunities and challenges in the integration of blockchain and biometrics, with emphasis in biometric template storage and protection, a key problem in biometrics still largely unsolved. Key tradeoffs involved in that integration, namely, latency, processing time, economic cost, and biometric performance are experimentally studied through the implementation of a smart contract on the Ethereum blockchain platform, which is publicly available in github for research purposes.
In recent years, due to the rapid development of information techniques and network technologies, more and more medical documents have been replaced by electronic files for sharing and transmitting in real time. However, medical data transmitted over public communication channels may suffer from security attacks and privacy threats. Blockchain technology has been gotten many attentions in different areas due to its unique properties such as anonymity, verifiability, immutability and decentralization. In order to secure patient privacy and provide more personal healthcare services, in this paper, we propose a data aggregation scheme based on Blockchain technology for medical environments. Moreover, in order to implement remote medical monitoring, we design a group authentication mechanism for multiple authorized users (such as patient, doctors, caregivers, family and friends) to freely access patient's personal health records. The authorized group members in a group will agree on a group session key and use it to protect patient's sensitive information. In case of a new member joins the medical group or an old member leaves the medical group, the group session key needs to be updated at any time. Finally, the electronic medical system will become more secure, reliable and useful by our proposed scheme.
Recently, application scenario of crowdsourcing IoT has covered to e-healthcare service, smart home, smart city, internet of vehicles due to the proliferation of smart devices such as smart mobile devices, smart wearable device, smart medical devices and smart furniture, etc. Patient's data collected by the smart devices send to the various remote medical servers. A group of medical professionals remote access patient data stored at the medical server database. Smart home users want to remote real-time access information of smart devices at home. All these operations need via wireless remote communication, which is suffering from various kinds of threat and attacks. Hence, there are a large number of multi-factor remote authentication and key agreement schemes designed for the application of crowdsourcing IoT. However, in most existing related multi-factor schemes, all factors for identity authentication only act as a parameter for encrypting the local secret key. In this paper, we propose a new secure remote multi-factor authentication scheme that includes three factors: 1) user identity; 2) password; and 3) user biometrics, which are authenticated by the remote server, act as a part of the secret key and participate in the key agreement process. We choose the chaotic map since it has a smaller key size and lower computational overhead, and then achieve remote multi-factor authentication and key agreement by artfully employ it to zero-knowledge technology and the fuzzy extractor technology. Our scheme is more secure and robust since the user revealing nothing sensitive information, and the adversary cannot impersonate any user even if he gets the server's master key. We have done security proof for our proposed scheme using the Random-Or-Real(ROR) model, Burrows-Abadi-Needham (BAN) logic, and ProVerif 2.00 to show that the presented scheme is secure. Also, we give an additional security analysis for other various attacks. Finally, according to the test and simulation result, the proposed scheme is very suitable for the power-constrained smart devices, and in the next generation 5G communication environment, its applicability and usability will be greatly enhanced.
User authentication can rely on various factors (e.g., a password, a cryptographic key, biometric data) but should not reveal any secret or private information. This seemingly paradoxical feat can be achieved through zero-knowledge proofs. Unfortunately, naive password-based approaches still prevail on the web. Multi-factor authentication schemes address some of the weaknesses of the traditional login process, but generally have deployability issues or degrade usability even further as they assume users do not possess adequate hardware. This assumption no longer holds: smartphones with biometric sensors, cameras, short-range communication capabilities, and unlimited data plans have become ubiquitous. In this paper, we show that, assuming the user has such a device, both security and usability can be drastically improved using an augmented password-authenticated key agreement (PAKE) protocol and message authentication codes.
Blockchain has been emerging as a promising technology that could totally change the landscape of data security in the coming years, particularly for data access over Internet-of-Things and cloud servers. However, blockchain itself, though secured by its protocol, does not identify who owns the data and who uses the data. Other than simply encrypting data into keys, in this paper, we proposed a protocol called Biometric Blockchain (BBC) that explicitly incorporate the biometric cues of individuals to unambiguously identify the creators and users in a blockchain-based system, particularly to address the increasing needs to secure the food logistics, following the recently widely reported incident on wrongly labelled foods that caused the death of a customer on a flight. The advantage of using BBC in the food logistics is clear: it can not only identify if the data or labels are authentic, but also clearly record who is responsible for the secured data or labels. As a result, such a BBC-based solution can great ease the difficulty to control the risks accompanying the food logistics, such as faked foods or wrong gradient labels.
Mehmet Aydar, Salih Cemil Cetin, Serkan Ayvaz, Betul Aygun
The disruptive technology of blockchain can deliver secure solutions without the need for a central authority. In blockchain protocols, 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; $a)$ users don't have an efficient and secure way to store their keys, $b)$ 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.
Oscar Delgado-Mohatar, Julián Fiérrez, Rubén Tolosana, Rubén Vera-Rodríguez
We explore practical tradeoffs in blockchain-based biometric template storage. We first discuss opportunities and challenges in the integration of blockchain and biometrics, with emphasis in biometric template storage and protection, a key problem in biometrics still largely unsolved. Blockchain technologies provide excellent architectures and practical tools for securing and managing the sensitive and private data stored in biometric templates, but at a cost. We explore experimentally the key tradeoffs involved in that integration, namely: latency, processing time, economic cost, and biometric performance. We experimentally study those factors by implementing a smart contract on Ethereum for biometric template storage, whose cost-performance is evaluated by varying the complexity of state-of-the-art schemes for face and handwritten signature biometrics. We report our experiments using popular benchmarks in biometrics research, including deep learning approaches and databases captured in the wild. As a result, we experimentally show that straightforward schemes for data storage in blockchain (i.e., direct and hash-based) may be prohibitive for biometric template storage using state-of-the-art biometric methods. A good cost-performance tradeoff is shown by using a blockchain approach based on Merkle trees.
Oscar Delgado-Mohatar, Julián Fiérrez, Rubén Tolosana, Rubén Vera-Rodríguez
Blockchain technology has become a thriving topic in the last years, making possible to transform old-fashioned operations to more fast, secured, and cheap approaches. In this study we explore the potential of blockchain for biometrics, analyzing how both technologies can mutually benefit each other. The contribution of this study is twofold: 1) we provide a short overview of both blockchain and biometrics, focusing on the opportunities and challenges that arise when combining them, and 2) we discuss in more detail blockchain for biometric template protection.
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.
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.
ICT 기술이 발달하며 IoT 환경이 주목받고 있다. 하지만 IoT 디바이스는 다양한 사용 용도만큼 디바이스가 동작하는 CPU의 성능도 다양하지만, 인증에 필요한 암호화가 내장되지 않은 CPU를 사용하거나, 공개키 암호가 동작하지 않는 디바이스도 다수 존재한다. 이에 따라, 본 논문에서는 램포트 해시체인, 램포트 서명, 블록체인을 분석하고, 기존 인증 프로토콜 분석을 통해 인증, 무결성 및 부인 방지 기능을 제공하는 블록체인 기반 IoT 디바이스 인증 스킴을 제안하였다. 본 논문에서 제안하는 스킴은 IoT 디바이스에 단순 해시연산만을 요구하여 저성능 IoT 디바이스에서도 동작이 가능해 IoT 환경에서 안전한 인증을 보장할 수 있다. With ICT technology develops, IoT environment is attracting attention. However, IoT devices have various CPU performance as much as various purpose of use. Some IoT devices use the cpu that doesn't support public key cryptogrphy or crypto acceleration. In this paper, we study Blockchain-based IoT Device Authentication Scheme that provides authentication, integirity and non-repudation through analysis of Lamport Hash-chain, Lamport Signature, Blockchain and existing Authentication protocols. The proposed scheme requires only simple hash operation in IoT devices and it can operate in low performance IoT device, thus ensuring secure authentication in IoT environment.
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
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.
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