The issue of identity authentication for online medical services has been one of the key focuses of the healthcare industry in recent years. Most healthcare organizations use centralized identity management systems (IDMs), which not only limit the interoperability of patient identities between institutions of healthcare, but also create isolation between data islands. The more important matter is that centralized IDMs may lead to privacy disclosure. Therefore, we propose Health-zkIDM, a decentralized identity authentication system based on zero-knowledge proof and blockchain technology, which allows patients to identify and verify their identities transparently and safely in different health fields and promotes the interaction between IDM providers and patients. The users in Health-zkIDM are uniquely identified by one ID registered. The zero-knowledge proof technology is deployed on the client, which provides the user with a proof of identity information and automatically verifies the user's identity after registration. We implemented chaincodes on the Fabric, including the upload of proof of identity information, identification, and verification functions. The experiences show that the performance of the Health-zkIDM system can achieve throughputs higher than 400 TPS in Caliper.
Vikas Goel, Mukul Aggarwal, Amit Gupta, Narendra Kumar
An Aadhaar is a unique number issued to every citizen in India. Aadhar’s current identity authentication relies on the central identities data repository (CDIR) of the unique identification authority of India (UIDAI), which is at risk of a single-point fault attack. Perhaps worse, internal attacks can tamper with the sensitive data of authenticated devices without being detected. In this paper, the proposed system utilizes emerging technology: blockchain for solving the issue of centralized authentication. The proposed system provides a distributed, secure, and tamper-proof ledger platform for Aadhar in that Aadhar is implemented using blockchain ethereum technology. The proposed system considers the unique Aadhar identification (ID) for each citizen of India and registered it on the smart contract of ethereum so that this unique ID may be authenticated by each other in a peer-to-peer network without a central authority. For securing the data, the proposed framework uses hashing technique for significant data (i.e. firmware). Blockchain stores hashed data and instantly any change in the state of the data may be possible to detect.
In recent years, counterfeit luxury products have become a major concern for consumers worldwide. The reason for the proliferation of counterfeit products is that the manufacturing and distribution process is not transparent to consumers and this information can be easily falsified or altered by others. To solve this problem, this paper proposes the development of a management system using blockchain and smart contract technology to solve the problems of data forgery and data tampering, while tracking the information related to luxury products and ensuring the accuracy and authenticity of the relevant data, to achieve the purpose of luxury product anti-counterfeiting. When using Hyperledger Fabric to deploy the blockchain and execute smart contracts, all information related to the production and logistics process of luxury goods will be uploaded to the blockchain. No human intervention is required to create a complete, traceable, tamper-proof, and trusted repository. Compared to previous work, this paper combines blockchain technology with specific processes in the supply chain, employing a variety of security methods to secure the communication process. Moreover, our proposed solution is more flexible in transmission, with more secure protocols also making data harder to tamper with and falsify, thereby solving the problem of forgery and tracking of luxury products.
Integrating the internet of things (IoT) and healthcare monitoring systems is one of the most dynamic innovations in the research area. Since the tremendous number of IoT devices in smart healthcare systems is increasing exponentially, privacy and security issues related to the patient's data are significant concerns. The authors propose an access control for a healthcare monitoring system using blockchain-based smart contracts. They created four smart contract forms for user registration, authentication, access control including misbehavior detection and access revocation. The sensor automatically measures the patient's health data and filters the data before determining whether to write the data into the blockchain or not. The sensor detects abnormal data and alerts doctors and hospitals for immediate treatment. The efficiency of the proposed framework is verified by performance evaluation based on the Ethereum test environment. The proposed system outperforms existing approaches by reducing deployment and execution latency and average response latency in the real-time smart healthcare system.
Sharing data securely and efficiently has been identified as an issue in IoT-based smart systems such as smart cities, smart agriculture, smart health, etc. A large number of IoT devices are used in these smart systems and they produce a large amount of data. IoT devices generally have limited storage and processing capabilities, and configuring any security techniques on these devices is a challenge. In this paper, we propose a novel device identity management approach for blockchain-based IoT systems that provides data security in two ways. Firstly, a lightweight time-based identification protocol that uses hub identification for validating data. Secondly, data storage is augmented with an effective blockchain application for providing easy access and immutability for data sharing among multiple parties. Our initial prototype implementation shows that: our identity management approach can be implemented in large scale settings, our system can be effectively implemented in blockchain platforms, and our performance evaluation result shows that the prototype fulfills system requirements adequately.
Non-fungible tokens (NFTs) are becoming very popular in a large number of applications ranging from copyright protection to monetization of both physical and digital assets. It is however a fact that NFTs suffer from a large number of security issues that create a lack of trust in solutions based on them. In this paper, we provide an overview of some of the most critical security challenges in media assets in form of visual content and then propose a specific solution for one among them, namely, secure person identification used in the context of KnowYour-Customer (KYC) with emphasis on liveness detection. The solution includes an authentication procedure that matches a selfie photo to a photograph of an identity document (ID). The system runs through a series of steps. First, detection is applied to extract faces from the selfie and the ID. Then a face comparison is performed to assess if they belong to the same person. While these two procedures are standard in KYC, a liveness check is also included so as to increase the security. The latter ensures that the user undergoing identity verification is in front of the camera and not a fraudster attempting to impersonate another individual. The system instructs the user to perform gestures such as waving hands or tilting head in front of the camera. The algorithmic detection of these actions during the live feed will reveal whether or not the user is carrying out the instructed activities. Performance of the proposed solution is then assessed under varying conditions.
Mehedi Masud, Gurjot Singh Gaba, Pardeep Kumar, Andrei Gurtov
Ambient Intelligence (AmI) in Internet of Things (IoT) has empowered healthcare professionals to monitor, diagnose, and treat patients remotely. Besides, the AmI-IoT has improved patient engagement and gratification as doctors’ interactions have become more comfortable and efficient. However, the benefits of the AmI-IoT-based healthcare applications are not availed entirely due to the adversarial threats. IoT networks are prone to cyber attacks due to vulnerable wireless mediums and the absentia of lightweight and robust security protocols. This paper introduces computationally-inexpensive privacy-assuring authentication protocol for AmI-IoT healthcare applications. The use of blockchain & fog computing in the protocol guarantees unforgeability, non-repudiation, transparency, low latency, and efficient bandwidth utilization. The protocol uses physically unclonable functions (PUF), biometrics, and Ethereum powered smart contracts to prevent replay, impersonation, and cloning attacks. Results prove the resource efficiency of the protocol as the smart contract incurs very minimal gas and transaction fees. The Scyther results validate the robustness of the proposed protocol against cyber-attacks. The protocol applies lightweight cryptography primitives (Hash, PUF) instead of conventional public-key cryptography and scalar multiplications. Consequently, the proposed protocol is better than centralized infrastructure-based authentication approaches.
Michael Froehlich, Jose Adrian Vega Vermehren, Florian Alt, Albrecht Schmidt
Cryptocurrencies have the potential to improve financial inclusion. However, the technology is complex to understand and difficult to use. Human-Computer-Interaction (HCI) can play a vital role in improving accessibility by identifying and overcoming challenges that hold users back. However, most HCI studies have focused only on Bitcoin and Ethereum so far. Newer blockchains promise transaction speeds comparable to traditional payment systems, enabling the use of cryptocurrencies as a medium of exchange for everyday transactions. To explore the viability of cryptocurrency-based point-of-sale solutions through a human-centered lens, we used Bitcoin Lightning to implement a payment system and evaluated it in a mixed-methods study. Our results show that Bitcoin Lightning is a usable alternative to traditional solutions and that friction aggregates at the interface to existing payment systems, i.e. when purchasing Bitcoin. We discuss qualitative insights and derive implications for deploying cryptocurrencies as payment solutions.
Abstract The internet of things (IoT) is now advancing at a tremendous pace. Devices in the IoT can connect and communicate in a fully autonomous mode. Because of its autonomy and numerous infractions of security policies, the IoT network is subject to various security risks. However, because of this autonomy, dependable security and storage mechanisms for authentication to share data across IoT devices are essential. Furthermore, since it has initially been popularized in Bitcoin, blockchain development has accelerated. Blockchain can be used to solve security challenges in the IoT. Making secure communication between IoT devices is one approach to accomplish this. To address this issue, we present an effective technique for intranetwork and internetwork device‐to‐device secure communication that enables IoT device identification and authentication while also providing secure communication in an open environment. The method also provides data integrity in addition to authentication and secure communication. We have presented informal security analysis, which confirms that there is no important security threats in our protocol. The performance of the protocol is also better in comparison with previously published papers.
Biometric identification is a convenient and reliable method in identity authentication. The widespread adoption of biometric identification requires strong privacy protection against possible theft or loss of biometric data. Existing techniques for privacy-preserving biometric identification mainly rely on traditional cryptographic technology such as oblivious transfer and homomorphic encryption, which will incur huge expenses to the system and cannot be applied to large-scale practical applications. For these issues, we propose a biometric identification scheme by constructing zero-knowledge succinct noninteractive argument of knowledge (zk-SNARK). Our scheme not only reduces the communication overhead, which only needs to send 8 constants to the verifier but also can protect the fingerprint template from disclosure. The time complexity of proof generation and proof verification are about O(C) and <a:math xmlns:a="http://www.w3.org/1998/Math/MathML" id="M1"> <a:mi>O</a:mi> <a:mfenced open="(" close=")" separators="|"> <a:mrow> <a:mi>x</a:mi> </a:mrow> </a:mfenced> <a:mo>+</a:mo> <a:mi mathvariant="normal">log</a:mi> <a:mtext> </a:mtext> <a:mtext> </a:mtext> <a:mi>C</a:mi> </a:math> , respectively, and the size of the proof is only 8 constants, where C and x represent the size of the circuit and the public input, respectively. We have implemented the proposed authentication solution on a public data set of fingerprint images and evaluated the performance and security.
Xiaotong Zhou, Debiao He, Muhammad Khurram Khan, Wei Wu · 5 authors
Vehicular Ad-hoc Networks (VANETs) have potential applications in improving the efficiency and safety for intelligent transportation systems. The openness of VANETs, however, also introduces privacy and security implications. Despite a number of conditional privacy-preserving authentication (CPPA) schemes with anonymity and conditional traceability have been designed for VANETs, a majority of these schemes cannot be directly applied to a real-world setting (e.g., due to the need for a certificate manager for issuing keys in PKI-based solutions, or the inherent key escrow problem in ID-based solutions). There have also been attempts to design blockchain-based CPPA schemes, but these schemes may not support key revocation or are inefficient (e.g., due to on-chain operations). This paper proposes an efficient blockchain-based CPPA (EBCPPA) scheme, which is designed to mitigate the above limitations. Our proposal consists of two key building blocks, namely: signature of knowledge and smart contract. To evaluate the feasibility, we present the security and performance analyses of EBCPPA. Specifically, the performance evaluations show that EBCPPA is more efficient than other existing state-of-the-art solutions, in terms of signing (improving at least 49.71%), the verification (improving at least 32.84%) and bandwidth requirement (reducing at least 27.59%).
NBA (National Basketball Association) trading cards are a hot collector’s item, with sales increasing rapidly every year. However, with the popularity of online trading, some sellers have started to intentionally and unintentionally sell imitation trading cards, and even PwC (Pricewaterhouse Coopers) is not immune. However, the PSA (Professional Sports Authenticator), which is the authentication agency, is not liable for this. Faced with the above situation, we moved trading cards online and proposed a blockchain-based anti-counterfeit and traceable NBA digital trading card management system, using blockchain technology to protect digital trading cards, and special digital copyright, to move from relying on other regulators to achieve the fight against counterfeit cards and maintain the security of the digital trading card market. Finally, we analyzed the security of the system and compared it with other methods. Our system uses Hyperledger Fabric to share data while protecting corporate privacy. Proxy re-encryption enables secure and trusted access authorization for digital transaction cards. Asymmetric encryption protects the data and uses signatures to achieve traceability and non-repudiation. Overall, our system solves the problem of counterfeiting and traceability that can occur in the digital trading card process from production to purchase.
Seniors safety is a compelling need, which necessitates 24/7 real-time monitoring and timely dangerous action recognition. Being able to mirror characteristics of physical objects (PO) to corresponding logical objects (LO) and seamlessly monitor their footprints thus detect anomaly parameters, Digital Twins (DT) has been considered a practical way to provide virtual health services for seniors safety. Meanwhile, widely adopted Internet of Medical Things (IoMT) consisting of wearable sensors and non-contact optical cameras for self and remote health data monitoring also raises concerns on information security and privacy violation. Therefore, security of POs, LOs and reliable data sharing among healthcare professionals are challenging as constructing trust and privacy-preserving virtual health services. Thanks to characteristics of decentralization, traceability and unalterability, Blockchain is promising to enhance security and privacy properties in many areas like data analysis, finance and healthcare. This paper envisions a lightweight authentication framework (LAF) to enable secure and privacy-preserving virtual healthcare services. Leveraging Non-Fungible Token (NFT) technology to tokenize LOs and data streams on blockchain, anyone can certify the authenticity of a digital LO along with its synchronized data between PO without relying on a third-party agency. In addition, the NFT-based tokenization not only allows owners fully control their IoMT devices and data, but it also enables verifiable ownership and traceable transferability during data sharing process. Moreover, NFT only contains references to encrypted raw data that are saved on off-chain storage like local files or distributed databases, such a hybrid storage strategy ensures privacy-preservation for sensitive information. A proof-of-concept prototype is implemented and tests are conducted on a case study of seniors safety. The experimental evaluation shows the feasibility and effectiveness of the proposed LAF solution.
The recent development of Internet of Things (IoT) and Unmanned Aerial Vehicles has revolutionized traditional agriculture with intelligence and automation. In a typical Intelligent Agriculture (IA) ecosystem, massive and real-time data are generated, analyzed, and sent to the Cloud Server (CS) for the purpose of addressing complex agricultural issues, such as yield prediction, water feed calculation, and so on. This helps farmer and associated stakeholders to take correct decision that improves the yield and quality of agricultural product. However, the distributed nature of IA entities and the usage of insecure wireless communication open various challenges related to data sharing, monitoring, storage, and further makes the entire IA ecosystem vulnerable to various potential attacks. In this article, we exploit deep learning and smart contract to propose a new IoT-enabled IA framework for enabling secure data sharing among its various entities. Specifically, first we develop new authentication and key management scheme to ensure secure data transmission in IoT-enabled IA. The encrypted transactions are then used by the CS to analyze and further detect intrusions by a novel deep learning architecture. In CS, the smart contract (SC)-based consensus mechanism is executed on legitimate transactions that verifies and adds the formed blocks into blockchain by a peer-to-peer CSs network. In comparison to existing competing security solutions, a rigorous comparative research demonstrates that the proposed approach provides greater security and more utility characteristics.
Non Fungible Tokens (NFTs) are becoming a standard to represent unique and valuable items, such as a piece of art, a videogame item, or other digital or physical goods, and keep track of their provenance. Thanks to blockchain technology and the power of smart contracts, NFT holders have true ownership over them, because they are the only ones who can transfer them. However, through an attack called sleepminting, an attacker is able to impersonate another person, including an artist, and create NFTs on the artist’s behalf, while still maintaining its possession, leveraging bugs in the code of the smart contract that manages the NFTs. Therefore, the attacker can cheat concerning the provenance of an NFT and then sell the fake NFTs to unaware buyers. In this paper, we propose a study that sheds light on this phenomenon. In particular, we collect over 1.3 million events that are connected to sleepminting and analyse the events under multiple aspects. The study uncovers that, by using the sleepminting attack, some users are able to create fake NFTs of popular brands, and are able to mint them to famous personalities in the NFT field, such as well known artists and collectors.
Abstract Cloud services are distributed from manifold sources with autonomous security procedures. The conventional authentication methods result in asynchronous security towards multi‐resource access and sharing. This provides volatile authentication for sequential service sessions. For alleviating this issue, a Rendezvous Block‐based Authentication Framework (RBAF) is proposed. This framework is backboned with a blockchain paradigm that differentiates authentication based on rendezvous and asynchronous attributes. The modifications in initial and final attributes are observed, intended for training, and supplanted with service‐dependent authentications. In the different sessions, attribute‐based authentication and agreed end‐to‐end security are administered using agreed keys that are valid within the sessions. This key generation is modified using the new session and user attributes based on learning recommendations. The ledger paradigm records the session and its associated attributes for different training instances, based on which service flexibility is ensured. The proposed framework's performance is verified using the metrics service distribution ratio, false rate, session uptime, and service delay.
In vehicular networks, authentication technology provides a basic security means to achieve trusted communication between legitimate vehicles. Revocation checking for vehicle certificates is an indispensable procedure in the process of authentication to protect vehicular networks from attacks by non-legitimate vehicles. However, revocation checking introduces procedures that requires additional time to process which challenges latency-sensitive applications in vehicular networks. This challenge grows more evidently when considering the factor of privacy preservation. In this paper, we propose to offload partial revocation task to network edges to lighten the revocation process in vehicles. Particularly, we design a method to achieve decentralized Global Certificate Revocation List (GCRL) management in network edges using permissioned blockchain technologies. In the method, both tamper-proof property and quick synchronization of the GCRL are guaranteed. Besides, our method can detect illegal revocation behaviours by validation in vehicles. Finally, we build a prototype of our proposed solution based on Hyperledger Fabric, and compare with Proof-of-Work scheme in terms of blockchain synchronization latency performance.
Edge-Integrated Internet-of-Vehicles (IoV) sinks service to edge nodes, which responses quickly to vehicles' requests and alleviates the burden of cloud servers. In such scenario, the entities of IoV need to be mutually authenticated since potential attacks can impersonate edge nodes to send false instructions to vehicles, or impersonate legitimate service subscribers to get free-ride IoV services. Furthermore, due to the high mobility characteristics of vehicles, frequent authentication is required between vehicles and edge nodes. We hope that the authentication process can be conducted efficiently to ensure the continuous service. Existing works cannot balance the security and efficiency well. This is still an issue worthy of discussion. In this article, we propose SEA, a secure and efficient blockchain-assisted authentication scheme for IoV. SEA achieves mutual authentication among vehicles, edge nodes and cloud servers. Specifically, the cloud server is only involved when vehicles are initially authenticated. And edge nodes realize the authentication of vehicles by querying the authentication result recorded by cloud on the blockchain, which significantly reduces the cryptographic computation overhead and eliminates network communication delay. Besides, session keys between any two entities involved are negotiated, which can secure sensitive data of vehicles. Extensive experiments have been conducted to show the security and efficiency of SEA.
Speech is one form of biometric that combines both physiological and behavioral features. It is beneficial for remote-access transactions over telecommunication networks. Presently, this task is the most challenging one for researchers. People's mental status in the form of emotions is quite complex, and its complexity depends upon internal behavior. Emotion and facial behavior are essential characteristics through which human internal thought can be predicted. Speech is one of the mechanisms through which human's various internal reflections can be expected and extracted by focusing on the vocal track, the flow of voice, voice frequency, etc. Human voice specimens of different ages can be emotions that can be predicted through a deep learning approach using feature removal behavior prediction that will help build a step intelligent healthcare system strong and provide data to various doctors of medical institutes and hospitals to understand the physiological behavior of humans. Healthcare is a clinical area with data concentrated where many details are accessed, generated, and circulated periodically. Healthcare systems with many existing approaches like tracing and tracking continuously disclose the system's constraints in controlling patient data privacy and security. In the healthcare system, majority of the work involves swapping or using decisively confidential and personal data. A key issue is the modeling of approaches that guarantee the value of health-related data while protecting privacy and observing high behavioral standards. This will encourage large-scale perception, especially as healthcare information collection is expected to continue far off this current ongoing pandemic. So, the research section is looking for a privacy-preserving, secure, and sustainable system by using a technology called Blockchain. Data related to healthcare and distribution among institutions is a very challenging task. Storage of facts in the centralized form is a targeted choice for cyber hackers and initiates an accordant sight of patients' facts which will cause a problem in sharing information over a network. So, this research paper's approach based on Blockchain for sharing sufferer data in a secured manner is presented. Finally, the proposed model for extracting optimum value in error rate and accuracy was analyzed using different feature removal approaches to determine which feature removal performs better with different voice specimen variations. The proposed method increases the rate of correct evidence collection and minimizes the loss and authentication issues and using feature extraction based on text validation increases the sustainability of the healthcare system.