With the continuous innovative development and popularization of mobile smart devices , the application of Mobile Crowd Sensing (MCS) continues to be studied extensively. However, existing centralized MCS applications that use servers for task publishing and data collection exhibit common problems, such as single points of failure and security vulnerabilities . Accordingly, we proposed a hybrid blockchain-based identity authentication scheme for MCS called HBIA, which uses blockchain technology to resolve the single-point failure problem. HBIA builds a cluster structure based on factors such as geographical location and balance, and uses it to construct a hybrid blockchain , with the cluster head node and internal cluster node authenticating on the public and private chains, respectively. We also implemented zero-knowledge proof (ZKP) to ensure the privacy of participantsā identities, thus balancing the contradiction between blockchain transparency and security. In addition, HBIA uses the zero-knowledge succinct non-interactive argument of knowledge (zk-SNARK) technology to enable off-chain computing and on-chain verification, further reducing the blockchainās workload. Finally,ā HBIA was evaluated based on the pavement crack detection task and tested on the Ethereum public test network known as Ropsten. The test results indicate that the identity authentication scheme proposed in this paper is superior to existing schemes in terms of authentication time.
Aaliya Sarfaraz, Ripon K. Chakrabortty, Daryl Essam
In recent years, supply chains have evolved into huge ecosystems, demanding trust, provenance, and data privacy. Since blockchain technology (BCT) allows for the development of a distributed environment, it is ideal for supply chain management (SCM) applications. However, concerns regarding data privacy have impeded the development of blockchains. Despite the fact that some blockchains can restrict participants from reading and/or writing data, blockchainās transparency makes protecting sensitive data challenging. To solve the data privacy challenge, this paper proposes a framework, AccessChain, that is an SCM access control framework that is based on an attribute-based access control (ABAC) model that restricts access to competing parties while allowing for network scalability. This proposed AccessChain model has two types of ledgers in its system: local and global. Local ledgers are used to store business contracts between stakeholders and the attribute-based access control model management, whereas the global ledger is used to record transaction data. AccessChain can enable decentralized, fine-grained and dynamic access control management in SCM when combined with the ABAC model and BCT. This paperās experimental results illustrate that high throughput can be achieved in a large-scale request environment while maintaining data privacy and sustaining a scalable network.
Edge computing offloads the data processing capacity to the user side, provides flexible and efficient computing services for the development of smart city, and brings many security challenges. Aiming at the problems of fuzzy boundary security protection and dynamic identity authentication in the edge computing environment in smart city, the zero trust architecture based on blockchain is studied, and a digital identity model and dynamic authentication scheme of edge computing nodes based on distributed ledger are proposed. Firstly, a digital identity model of two-way authentication between edge computing node and sensing terminal is established to realize fine-grained authorization and access control in edge computing. Secondly, based on the identity data and behavior log bookkeeping on the chain, the quantification of trust value, trust transmission and update are realized, and the traceability of security events is improved. Finally, based on the improved RAFT consensus algorithm, the multi-party consensus and consistency accounting in the authentication process are realized. Simulation results show that this scheme can meet the requirements of zero trust verification in edge computing environment, and has good efficiency and robustness.
Recently, unmanned aerial vehicles (UAVs) have gained attention due to increased use-cases in healthcare, monitoring, surveillance, and logistics operations. UAVs mainly communicate with mobile base stations, ground stations (GS), or networked peer UAVs, known as UAV swarms. UAVs communicate with GS, or UAV swarms, over wireless channels to support mission-critical operations. Communication latency, bandwidth, and precision are of prime importance in such operations. With the rise of data-driven applications, fifth-generation (5G) networks would face bottlenecks to communicate at near-real-time, at low latency and improved coverage. Thus, researchers have shifted towards network designs that incorporate beyond 5G (B5G) networks for UAV designs. However, UAVs are resource-constrained, with limited power and battery, and thus centralized cloud-centric models are not suitable. Moreover, as exchanged data is through open channels, privacy and security issues exist. Federated learning (FL) allows data to be trained on local nodes, preserving privacy and improving network communication. However, sharing of local updates is required through a trusted consensus mechanism. Thus, blockchain (BC)-based FL schemes for UAVs allow trusted exchange of FL updates among UAV swarms and GS. To date, limited research has been carried out on the integration of BC and FL in UAV management. The proposed survey addresses the gap and presents a solution taxonomy of BC-based FL in UAVs for B5G networks due to the open problem. This paper presents a reference architecture and compares its potential benefits over traditional BC-based UAV networks. Open issues and challenges are discussed, with possible future directions. Finally, a logistics case study of BC-based FL-oriented UAVs in 6G networks is presented. The survey aims to aid researchers in developing potential UAV solutions with the key integrating principles over a diverse set of application verticals.
In the digital twin environment, the fusion data onto physical entities in the physical space are mapped to multiple virtual spaces for digital modeling and intelligent simulation in different dimensions. In real intelligent manufacturing scenarios, heterogeneous multi-source fusion data are collected at the same time period. So they are consistent in time state. For the autonomous digital twin system, time states verification and integrity checking are basic security factors. Provable data possession technology can check the integrity of data onto virtual spaces. The blockchain can provide the synchronization interface to make distributed entities to obtain the trusted time state value. Considering the privacy, the blockchain can also provide anonymous services for entities. Therefore, we propose the blockchain-based synchronized provable data possession scheme (named BSPDP) for digital twin. In our scheme, the selection of verifier is flexible. Since virtual spaces may be maliciously framed to pay compensation, we use tag verification to prevent honest virtual spaces from being framed. Under the assumption of RSA, the proposed BSPDP is provably secure. Finally, the performance analysis demonstrates that BSPDP is practical. The experimental results show that BSPDP is effective and attractive for digital twin.
The Internet of Vehicles (IoV) technology enables vehicles to communicate with each other, with pedestrians and with roadside infrastructures, to realize more efficient, safer and more environmentally friendly transportation. IoV also promises rich location-based services for vehicles, such as parking and toll highway. However, preserving privacy for location-based service payments emerges as a critical and challenging problem in IoV. Existing schemes rely on centralized banks for payment processing, resulting in location privacy leakage to centralized entities. In this paper, we propose a decentralized privacy-preserving payment scheme named Vehicloak for IoV based on the blockchain technology. The biggest challenge is to provide location privacy for vehicles while guaranteeing correct service payments using the transparent blockchain. To tackle this challenge, we introduce a new cryptographic technique called zk-GSigproof that integrates zero-knowledge proof with group signature. Vehicloak implements this technique in a smart contract to process payment, which verifies zero-knowledge proof and group signature without leaking location information. It is not limited to IoV and can be applied in many payment scenarios. To evaluate the performance of our scheme, we implement Vehicloak on a private blockchain of 100 nodes on Aliyun, and conduct a test with up to 4,000 transactions. The experimental results prove the feasibility of Vehicloak.
As a peerātoāpeer āP2Pā distributed ledger, the blockchain has the advantages of decentralization, no trust, open autonomy, and nontampering. Therefore, many users are willing to conduct transactions in blockchain cryptocurrency systems such as Bitcoin and Ethereum. However, the throughput of traditional blockchain is extremely low, and the transaction is so delayed. The payment channel network is the most promising solution to expand the blockchain for widespread use. Achieving secure instant payment on the payment channel can significantly increase transaction throughput and reduce transaction delays. When the payment channel is closed, the balance in the channel will be returned to an account on the blockchain. In this paper, we discuss the design and the implementation of a multiparty payment channel network based on smart contracts. Where a twoāparty payment channel is designed based on blockchain and smart contracts, a new multiparty payment channel is established on the basis of the payment channel. A detailed definition and description are given, and the creation, update, and closing functions of the multiparty payment channel are designed. Moreover, we design a multiparty payment channel smart contract, deploy it to the local private blockchain, and conduct simulation and testing. The delay time of different transaction methods is counted, and the network topology type, transaction amount, and other factors are studied. The impact of transaction success rate and the gas consumption of different transaction methods are analyzed through multiple sets of experimental statistics.
Data-driven applications play an important role in modern-time maritime transportation systems, for instance in facilitating decision-making relating to communication and safety. One example application is position data sharing between vessels within the maritime Internet of Things (IoT)-enabled context. When designing such applications, we need to also consider how to ensure data accuracy as well as privacy in a large scale deployment. In this paper, we demonstrate the potential of using blockchain to facilitate privacy-preserving data sharing. Specifically, we develop a zero-knowledge proof-based scheme to protect vessel identities while allowing data sharing, and a commitment-based approach to ensure relationship-related privacy in data trading between participants. Our security and performance evaluations demonstrate the utility of the proposed approach.
The continuous production of large-scale data makes data outsourcing computation a trend. In order to ensure that data outsourcing transaction is trusted and fair, it needs the supervision and judgment of a third party. However, the third-party intermediary increases the transaction cost, and there is also subjective unreliability. Smart contracts allow trusted transactions without a third party, which are automatic, traceable and irreversible. Therefore, in this paper, we propose a framework for data outsourcing computation transaction based on the smart contract, in which the transaction is verifiable, fair and privacy protected. In this framework, by improved the replication-based verifiable computation technology, the data in the dataset is evenly distributed to each server, and at least one data in the sub datasets of the adjacent servers is the same, only the results from the duplicate data are verified, so as to implement the verifiable transaction with the low transaction cost. Meanwhile, a punishment mechanism is adopted to solve the fairness of the transaction in the smart contract. In addition, the oblivious transfer protocol is used to implement the privacy protection of transaction data. We deploy the data outsourcing computation transaction framework in the simulation environment of the Ethereum blockchain, and the experimental results show that our proposed scheme is effective and has low overhead. Specifically, the data returned by the server is verifiable, and the data privacy of the client is protected. When the client and servers are dishonest, they will be punished so that the transaction is fair. Moreover, the cost of using the smart contract in transactions is almost negligible.
Privacy is playing a crucial role in the smart health industry, where health service providers and their customers use the internet of things (IoT) to provide and consume health services. Preserving privacy for legitimate users and preventing illegitimate users from accessing services are difficult to implement simultaneously. In this study, we addressed this issue by proposing a new healthcare system for IoT based on the blockchain and zero-knowledge succinct noninteractive argument of knowledge (zk-SNARK). We employ the anonymity property of the public blockchain to protect users’ privacy. The zk-SNARK scheme works as an anonymous authenticator to prevent unauthorized users from using services. We also analyze the security of the proposed system by showing that it can resist various types of attacks, such as impersonation, collusion, and man-in-the-middle attacks. Finally, we evaluate the performance of the zk-SNARK scheme with respect to computational costs and the interactions with the Ethereum blockchain smart contract with respect to transaction fees.
Awais Abdul Khaliq, Adeel Anjum, Abdul Basit Ajmal, Julian Webber Ā· 6 authors
The privacy preservation has received considerable attention from organizations as the growing population is apprehensive regarding personal data being preserved.There are several privacy and security issues in existing systems, such as identity and location disclosure, availability, and authenticity. Smart parking systems utilize third-party parking recommender systems to offer customized parking space recommendations to its users based on userās past parking experience. However, indiscriminately sharing a userās data with a third party recommendation system may violate their personal information because their activity and node mobility can be deduced from their previous paring experience. Another problem with existing solutions is that most distributed systems need a third party to anonymize user data to preserve the userās privacy. Therefore, this article provides three solutions that address the problems mentioned above; at first, based on elliptic curve cryptography (ECC), we proposed the mutual authentication mechanism using HMAC to provide anonymity and integrity during communication; secondly, given the risks to security and privacy posed by untrustworthy third parties, we used local differential privacy, which uses the Laplace distribution technique to add noise randomly and eliminates any necessity for a third party for data perturbation. And thirdly, in addition to LDP , we utilize the IOTA distributed ledger technology to provide a new level of security that ensures immutability, scalability, and quantum secrecy and decentralized the system. Our experiments demonstrate that, in addition to preserving the driverās privacy and security, our proposed model has low storage overheads, computation, and communication costs.
Open access
Smart Parking Systems Research
Advanced Steganography and Watermarking Techniques
In recent years, the interest in using wireless communication technologies and mobile devices in the healthcare environment has increased. However, despite increased attention to the security of electronic health records, patient privacy is still at risk for data breaches. Thus, it is quite a challenge to involve an access control system especially if the patientsā medical data are accessible by users who have diverse privileges in different situations. Blockchain is a new technology that can be adopted for decentralized access control management issues. Nevertheless, different scalability, security, and privacy challenges affect this technology. To address these issues, we suggest a novel Decentralized Self-Management of data Access Control (DSMAC) system using a blockchain-based Self-Sovereign Identity (SSI) model for privacy-preserving medical data, empowering patients with mechanisms to preserve control over their personal information and allowing them to self-grant access rights to their medical data. DSMAC leverages smart contracts to conduct Role-based Access Control policies and adopts the implementation of decentralized identifiers and verifiable credentials to describe advanced access control techniques for emergency cases. Finally, by evaluating performance and comparing analyses with other schemes, DSMAC can satisfy the privacy requirements of medical systems in terms of privacy, scalability, and sustainability, and offers a new approach for emergency cases.
Driven by an unprecedented boom in artificial intelligence (AI) and Internet of Things (IoT), edge intelligence (EI) pushes the frontier of AI from cloud to network edge, serving as a remarkable solution that unlocks the full potential of AI services. It is yet facing critical challenges in its decentralized management and security, limiting its capabilities to support services with numerous requirements. In this context, blockchain (BC) has been seen as a promising solution to tackle the above issues, and further support EI. Based on the number of citations or the relevance of emerging methods, this paper presents the results of a literature survey on the integration of EI and BC. Accordingly, we summarize the recent research efforts reported in the existing works on EI and BC. We then paint a comprehensive picture of the limitations of EI and why BC could benefit from EI. From there, we explore how BC benefits EI in terms of computing power management, data administration, and model optimization. In order to narrow the gap between immature BC and EI-amicable BC, we also probe into how to tailor BC to EI from four perspectives, including flexible consensus protocol, effective incentive, intellectuality smart contract, and scalability. Finally, some research challenges and future directions are presented. Different from existing surveys, our work focuses on the integration of EI and BC, develops some general models to help the reader build relevant optimization models in the integrated system, as well as provides detailed tutorials on implementation. We anticipate that this survey will motivate further discussions on the synergy of EI and BC, and offer some guidance in EI, BC, future networks, and other areas.
Tom Godden, Ruben De Smet, Christophe Debruyne, Thibaut Vandervelden Ā· 6 authors
Driven by the increased consciousness in data ownership and privacy, zero-knowledge proofs (ZKPs) have become a popular tool to convince a third party of the truthfulness of a statement without disclosing any further information. As ZKPs are rather complex to design, frameworks that transform high-level languages into ZKPs have been proposed. We propose Circuitree, a Datalog reasoner in zero-knowledge. Datalog is a high-level declarative logic language that is generally used for querying. Furthermore, as a logic language, it can also be used to solve logic problems. An application using Circuitree can efficiently generate ZKPs, based on Datalog rules and encrypted data, to prove that a certain conclusion follows from a Datalog ruleset and encrypted input data. Compared to existing frameworks, which generally use their own limited imperative languages, Circuitree uses an existing high-level declarative language. We point out several applications for Circuitree, including EU Digital COVID Certificates and privacy-preserving access control for peer-to-peer (p2p) networks. Circuitreeās performance is evaluated for access control in a p2p network. First results show that our approach allows for fast proofs and proof verification for this application.
Bitcoin is one of the best-known cryptocurrencies, which captivated researchers with its innovative blockchain structure. Examinations of this public blockchain resulted in many proposals for improvement in terms of anonymity and privacy. Generally used methods for improvement include mixing protocols, ring signatures, zero-knowledge proofs, homomorphic commitments, and off-chain storage systems. To the best of our knowledge, in the literature, there is no study examining Bitcoin in terms of differential privacy, which is a privacy notion coming up with some mechanisms that enable running useful statistical queries without identifying any personal information. In this paper, we provide a theoretical examination of differential privacy in Bitcoin. Our motivation arises from the idea that the Bitcoin public blockchain structure can benefit from differential privacy mechanisms for improved privacy, both making anonymization and privacy breaches by direct queries impossible, and preserving the checkability of the integrity of the blockchain. We first examine the current Bitcoin implementation for four query functions using the differential privacy formulation. Then, we present the feasibility of the utilization of two differential privacy mechanisms in Bitcoin; the noise addition to the transaction amounts and the user graph perturbation. We show that these mechanisms decrease the fraction of the cases violating differential privacy, therefore they can be used for improving anonymity and privacy in Bitcoin. Moreover, we showcase the noise addition to transaction amounts by using IBM Differential Privacy Library. We compare four differential privacy mechanisms for varying privacy parameter values and determine the feasible mechanisms and the parameters.
Md. Rayhan Ahmed, A.K.M. Muzahidul Islam, Swakkhar Shatabda, Salekul Islam
Identity Management System (IDMS) refers to how users or individuals are identified and authorized to use organizational systems and services. Since traditional identity management and authentication systems rely heavily on a trusted central authority, they cannot mitigate the effects of single points of failure. As a decentralized and distributed public ledger in a peer-to- peer (P2P) network, Blockchain (BC) technology has garnered a considerable amount of attention in the field of IDMS in recent years. Through Self-Sovereign Identity (SSI), users can have full authority over their digital identity. Successful implementation of a BC-based IDMS can significantly increase the degree of privacy and security of a userās SSI. However, the integration of BC-based IMDS to provide a user with SSI is still an unorganized area of research in its early stages of development. This article presents an extensive literature review of state-of-the-art academic publications as well as commercial market offerings regarding the applicability of BC-based SSI solutions. It also provides a detailed preliminary regarding the building blocks of blockchain technology and a progressive roadmap of IDMS solutions. In order to develop an effective BC-based IDMS solution that focuses on securing a userās SSI, this article outline five essential components of a BC-based IDMS: authentication, integrity, privacy, trust, and simplicity. Furthermore, we perform a security analysis that outlines several types of adversarial threats that can cause potential damage to the BC-based IDMS. We identify and discuss associated issues and challenges by analyzing several notable BC-based IDMS solutions in academic literature. We also highlight potential research gaps and provide future research scope.