Nikos Fotiou, Iakovos Pittaras, Vasilios A. Siris, George C. Polyzos · 5 authors
Service providers usually require detailed statistics in order to improve their services. On the other hand, privacy concerns are intensifying and sensitive data is protected by legislation, such as GDPR (General Data Protection Regulation). In this paper, we present the design, implementation, and evaluation of a marketplace that allows “data consumers” to buy information from “data providers”, which can then be used for generating meaningful statistics. Additionally, our system enables “system operators” that can select which data providers are allowed to provide data, based on filtering criteria specified by the data consumer. We leverage local differential privacy to protect the data provider's privacy against data consumers, as well as against system operators, and we build a blockchain-based solution for ensuring fair exchange, and immutable data logs. Our design targets use cases that involve hundreds or even thousands of data providers. We prove the feasibility of our approach through a proof-of concept implementation of a measurement sharing application for smart-grid systems.
Abstract For the current medical block chain, the access rights of electronic medical records and agent encryption are mainly controlled by permission contract. The way of protecting electronic medical records realizes the sharing of medical data, but neglects the management and protection of user identity. In this paper, this article studies the privacy protection technology of the blockchain, combined with the stealth address and zero-knowledge proof technology, and proposes a plan to weigh anonymity and security to protect the privacy of users in the medical blockchain.
Siyi Liao, Jun Wu, Jianhua Li, Ali Kashif Bashir · 5 authors
The Internet of Drones (IoD) is a layered network control architecture, which is having a revolutionary impact on the monitoring and preservationvof the environment. Large-scale drone-assisted environmental monitoring can provide a better perspective and high-quality data by monitoring the operation of critical components of smart cities. However, with the continuous expansion of IoD scale and the increase of multi-drone collaboration tasks, the large-scale drone-assisted service in smart cities monitoring will inevitably encounter the problem of relay and transfer of drone control. Lack of a trust collaboration paradigm between drone controllers will bring huge security challenges to real-time monitoring the environment, collaboration of tasks, data, location privacy of drones, and so on. To address this important issue in IoD, this article proposes a paradigm that uses smart contracts and blockchain to ensure trusted collaboration between controllers of software defined IoD (SD-IoD). First, we propose a novel SD-IoD architecture to enhance the support for heterogeneity and flexibility of IoD for monitoring of the environment. Second, we propose a controller consortium blockchain for secure and efficient cooperation and interoperability of drone controllers, which includes a new cryptographic currency cooperation coin and a new consensus mechanism proof of security guarantee (PoSG). Third, we have designed a novel incentive mechanism to encourage controllers to maintain their security and provide safer services to other controllers. The security analysis and performance simulation results indicate the effectiveness of the proposed mechanism.
The start of e-commerce introduced centralized trust and reputation management system to deal with the trust issues in the transactions since the initial transactions usually took place between businesses and consumers (B2C). However, with the development of P2P e-commerce paradigm and problems of centralized systems, such as privacy concerns and abnormal recommendations, coming to surface, the need for distributed trust and reputation management systems has become urgent, and therefore many related approaches have been put forward in the literature. However, even though the approaches are learning from the past experience and therefore improving, drawbacks like weak to attacks still exist. In this paper, Distributed Ledger Technology (DLT) and its implementation Blockchain (BC) are considered as a rather positive solution that may handle the hard problems. To ensure the effectiveness of Blockchain, its potential future trends are discussed in this article as well.
Reliable identity management and authentication are significant for network security. In recent years, as traditional centralized identity management systems suffer from security and scalability problems, decentralized identity management has received considerable attention in academia and industry. However, with the increasing sharing interaction among each domain, management and authentication of decentralized identity has raised higher requirements for cross-domain trust and faced implementation challenges galore. To solve these problems, we propose BIdM, a decentralized cross- domain identity management system based on blockchain. We design a decentralized identifier (DID) for naming identities based on the consortium blockchain technique. Since the identity subject fully controls the life cycle and ownership of the proposed DID, it can be signed and issued without a central authentication node's intervention. Simultaneously, every node in the system can participate in identity authentication and trust establishment, thereby solving the centralized mechanism's single point of failure problem. To further improve authentication efficiency and protect users' privacy, BIdM introduces a one-way accumulator as an identity data structure, which guarantees the validity of entity identity. We theoretically analyze the feasibility and performance of BIdM and conduct evaluations on a prototype implementation. The experimental results demonstrate that BIdM achieves excellent optimization on cross-domain authentication compared with existing identity management systems.
The rapid increase of the data scale in Internet of Vehicles (IoV) system paradigm, hews out new possibilities in boosting the service quality for the emerging applications through data sharing. Nevertheless, privacy concerns are major bottlenecks for data providers to share private data in traditional IoV networks. To this end, federated learning (FL) as an emerging learning paradigm, where data providers only send local model updates trained on their local raw data rather than upload any raw data, has been recently proposed to build a privacy-preserving data sharing models. Unfortunately, by analyzing on the differences of uploaded local model updates from data providers, private information can still be divulged, and performance of the system cannot be guaranteed when partial federated nodes executes malicious behavior. Additionally, traditional cloud-based FL poses challenges to the communication overhead with the rapid increase of terminal equipment in IoV system. All these issues inspire us to propose an autonomous blockchain empowered privacy-preserving FL framework in this paper, where the mobile edge computing (MEC) technology was naturally integrated in IoV system.
Constant function market makers (CFMMs) such as Uniswap, Balancer, Curve, and mStable, among many others, make up some of the largest decentralized exchanges on Ethereum and other blockchains. Because all transactions are public in current implementations, a natural next question is if there exist similar decentralized exchanges which are privacy-preserving; i.e., if a transaction's quantities are hidden from the public view, then an adversary cannot correctly reconstruct the traded quantities from other public information. In this note, we show that privacy is impossible with the usual implementations of CFMMs under most reasonable models of an adversary and provide some mitigating strategies.
With customization of demands and functionalities, diverse blockchain systems are integrated with IoT in different application scenarios, forming a multichain environment. Multichain interoperability has become a crucial emerging issue, i.e., different blockchain systems are difficult to interact with each other credibly and efficiently. It further leads to isolated data islands across multichain. Therefore, it is of significant importance to facilitate data sharing among multichain systems. Toward achieving this, there are two main challenges. First, data across multiple blockchains must be shared reliably to meet the tamper-proof merits of blockchain technology. Second, we must control the data access process in a fine-grained way to protect sensitive data and user privacy. This article proposes SynergyChain, a multichain framework to enable reliable data sharing with controllable data access. By aggregating the data from multiple blockchains and reorganizing it in SynergyChain, we can achieve data reliability with the verification. Meanwhile, SynergyChain provides hierarchical access control based on smart contracts, making access control automated and credible. Experiments show that SynergyChain can support data sharing reliably and efficiently and reduce data query latency compared with multichain data requesting sequentially.
Unlike a traditional centralized and producer-controlled power grid, the smart grid is a more complicated distributed power system consisted of many resources and applications. In smart grid, huge amounts of data generated by edge devices are collected by different parties. To achieve high operation efficiency, it is important to enable the data sharing and cooperative computation among different parties. How to protect the security and privacy of the utility data and the identities of their owners has become a major concern. There have been some studies on this issue. However, most of these works failed to consider the privacy protection in the dual sides of the data owner and receiver. In this article, we propose BPM4SG, a blockchain-based dual-side privacy-preserving multiparty computation (MPC) scheme for edge-enabled smart grid. In BPM4SG, the data segmentation method is adopted to ensure the security of MPC (e.g., summation) in edge nodes. The consortium blockchain and smart contract are used to further increase the system security and avoid the dependency on trusted third parties. Additionally, a data obfuscation method based on the ring signatures and a new one-time address scheme are proposed to protect the privacy of both the data owner and data receiver. The analysis shows that BPM4SG can meet the security and privacy requirements of smart grid. The experimental evaluation results demonstrate that our scheme has a better performance compared with other popular schemes.
The development of information technology has brought great convenience to our lives, but at the same time, the unfairness and privacy issues brought about by traditional centralized systems cannot be ignored. Blockchain is a peer-to-peer and decentralized ledger technology that has the characteristics of transparency, consistency, traceability and fairness, but it reveals private information in some scenarios. Secure multi-party computation (MPC) guarantees enhanced privacy and correctness, so many researchers have been trying to combine secure MPC with blockchain to deal with privacy and trust issues. In this paper, we used homomorphic encryption, secret sharing and zero-knowledge proofs to construct a publicly verifiable secure MPC protocol consisting of two parts-an on-chain computation phase and an off-chain preprocessing phase-and we integrated the protocol as part of the chaincode in Hyperledger Fabric to protect the privacy of transaction data. Experiments showed that our solution performed well on a permissioned blockchain. Most of the time taken to complete the protocol was spent on communication, so the performance has a great deal of room to grow.
Electing democratic representatives via voting has been a common mechanism since the 17th century. However, these mechanisms raise concerns about fairness, privacy, vote concealment, fair calculations of tally, and proxies voting on their behalf for the voters. Ballot voting, and in recent times, electronic voting via electronic voting machines (EVMs) improves fairness by relying on centralized trust. Homomorphic encryption-based voting protocols also assure fairness but cannot scale to large scale elections such as presidential elections. In this paper, we leverage the blockchain technology of distributing trust to propose a smart contract-based protocol, namely, \proto. There are many existing protocols for voting using smart contracts. We observe that these either are not scalable or leak the vote tally during the voting stage, i.e., do not provide vote concealment. In contrast, we show that FASTEN preserves voter's privacy ensures vote concealment, immutability, and avoids double voting. We prove that the probability of privacy breaches is negligibly small. Further, our cost analysis of executing FASTEN over Ethereum is comparable to most of the existing cost of elections.
With the increasing number of cybercrimes, the digital forensics team has no choice but to implement more robust and resilient evidence-handling mechanisms. The capturing of digital evidence, which is a tangible and probative piece of information that can be presented in court and used in trial, is very challenging due to its volatility and improper handling procedures. When computer systems get compromised, digital forensics comes into play to analyze, discover, extract, and preserve all relevant evidence. Therefore, it is imperative to maintain efficient evidence management to guarantee the credibility and admissibility of digital evidence in a court of law. A critical component of this process is to utilize an adequate chain of custody (CoC) approach to preserve the evidence in its original state from compromise and/or contamination. In this paper, a practical and secure CustodyBlock (CB) model using private blockchain protocol and smart contracts to support the control, transfer, analysis, and preservation monitoring is proposed. The smart contracts in CB are utilized to enhance the model automation process for better and more secure evidence preservation and handling. A further research direction in terms of implementing blockchain-based evidence management ecosystems, and the implications on other different areas, are discussed.
In this paper, we develop a foundation for a constellation of Low Earth Orbit (LEO) satellite IoT by constructing a Blockchain-based framework for continual knowledge sharing and learning collaboratively. This approach is directly applicable for a swarm of Unmanned Aerial Vehicles (UAVs). We ablate Federated Learning (FL) successful features as a basis to ensure high precision of learning inferences at timescales relevant to the underlying time-varying space network and channel dynamics. In such a dynamic setting, there is always a likelihood that miners may be compromised or fail to propagate information in time because of some intrinsic factors such as channel impairments, satellite handovers and attacks. Such transmission failures often lead to undesirable forking events in the Blockchain. Consequently, maintaining a low energy consumption and smallish delay in such an erratic network is highly nontrivial and challenging. To quantify the impacts of the forking and minimize the occurrence of such unwanted events and their adverse effects, we develop a procedure to estimate the expected energy consumption for a given set of miners, block transmissions, and LEOs’ or UAVs’ mobility. Besides, we shed light on deep learning-based resource allocation for mobile mining and demonstrate the synergic gain of FL with Blockchain.
Muhammad Nazmul Islam, Mubashir Husain Rehmani, Jinjun Chen
Permissioned blockchain such as Hyperledger fabric enables a secure supply chain model in Industrial Internet of Things (IIoT) through multichannel and private data collection mechanisms. Sharing of Industrial data including private data exchange at every stage between supply chain partners helps to improve product quality, enable future forecast, and enhance management activities. However, the existing data sharing and querying mechanism in Hyperledger fabric is not suitable for supply chain environment in IIoT because the queries are evaluated on actual data stored on ledger which consists of sensitive information such as business secrets, and special discounts offered to retailers and individuals. To solve this problem, we propose a differential privacy-based permissioned blockchain using Hyperledger fabric to enable private data sharing in supply chain in IIoT (DH-IIoT). We integrate differential privacy into the chaindcode (smart contract) of Hyperledger fabric to achieve privacy preservation. As a result, the query response consists of perturbed data which protects the sensitive information in the ledger. The proposed work (DH-IIoT) is evaluated by simulating a permissioned blockchain using Hyperledger fabric. We compare our differential privacy integrated chaincode of Hyperledger fabric with the default chaincode setting of Hyperledger fabric for supply chain scenario. The results confirm that the proposed work maintains 96.15% of accuracy in the shared data while guarantees the protection of sensitive ledger's data.
The integration of Internet of Vehicles (IoV) with social networks has introduced Social IoV (SIoV) that will offer new applications in vehicular networks, e.g., personalized recommendations and route planning. This will be facilitated by heterogeneous access technologies and edge computing to offload tasks from vehicles via secure resource assignment. Thus, each vehicle in SIoV acts as a social subject that manages its own network. SIoV will lead to an explosive growth in network size, and induce issues like scalability and resource discovery. Blockchain is a potential candidate to address these, however, it is not suitable for SIoV with traditional proof-of-work (PoW) consensus. In this paper, we propose a framework that uses a dynamic PoW (dPoW) consensus with a checkpoint mechanism and a resource assignment policy. The dPoW consensus has different mining difficulty levels that change according to the communication traffic, whereas the checkpoint defines an alternative mechanism to generate the next block hash. The assignment policy manages an access control list to mandate the edge modules to securely distribute resources among vehicles. To study the feasibility of our framework, we present a formal security analysis using the Access Control Logic model. For the performance analysis, we use three metrics, i.e., scalability, latency, and security. With these analyses, we demonstrate that our framework offers enhanced security and can scale with a minimal increase in computation overhead. A case study with a comparative analysis is also discussed that evaluates the network dynamics and attests the superior performance of the framework under a real-life vehicular network scenario.
Abdullah Lakhan, Muneer Ahmad, Muhammad Bilal, Alireza Jolfaei · 5 authors
The development of vehicular Internet of Things (IoT) applications, such as E-Transport, Augmented Reality, and Virtual Reality are growing progressively. The mobility aware services and network-based security are fundamental requirements of these applications. However, multi-side offloading enabling blockchain and cost-efficient scheduling in heterogeneous vehicular fog cloud nodes network become a challenging task. The study formulates this problem as a convex optimization problem, where all constraints are the convex set. The goal of the study is to minimize communication cost and computation cost of applications under mobility, security, deadline, and resource constraints. Initially, we propose a novel vehicular fog cloud network (VFCN) which consists of different components and heterogeneous computing nodes. The ensure mobility privacy, the study devises Mobility Aware Blockchain-Enabled offloading scheme (MABOS). It extends blockchain enable multi-side offloading (e.g., offline offloading and online offloading) with proof of work (PoW), proof of creditability (PoC) and fault-tolerant techniques. The purpose is to offload all tasks under the secure network without any violation. Furthermore, to ensure Quality of Service (QoS) of applications, this work suggests linear search based task scheduling (LSBTS) method, which maps all tasks onto appropriate computing nodes. The experimental results show that devise schemes outperform all existing baseline approaches to the considered problem.
We propose three constructions of classically verifiable non-interactive zero-knowledge proofs and arguments (CV-NIZK) for QMA in various preprocessing models. - We construct a CV-NIZK for QMA in the quantum secret parameter model where a trusted setup sends a quantum proving key to the prover and a classical verification key to the verifier. It is information theoretically sound and zero-knowledge. - Assuming the quantum hardness of the learning with errors problem, we construct a CV-NIZK for QMA in a model where a trusted party generates a CRS and the verifier sends an instance-independent quantum message to the prover as preprocessing. This model is the same as one considered in the recent work by Coladangelo, Vidick, and Zhang (CRYPTO '20). Our construction has the so-called dual-mode property, which means that there are two computationally indistinguishable modes of generating CRS, and we have information theoretical soundness in one mode and information theoretical zero-knowledge property in the other. This answers an open problem left by Coladangelo et al, which is to achieve either of soundness or zero-knowledge information theoretically. To the best of our knowledge, ours is the first dual-mode NIZK for QMA in any kind of model. - We construct a CV-NIZK for QMA with quantum preprocessing in the quantum random oracle model. This quantum preprocessing is the one where the verifier sends a random Pauli-basis states to the prover. Our construction uses the Fiat-Shamir transformation. The quantum preprocessing can be replaced with the setup that distributes Bell pairs among the prover and the verifier, and therefore we solve the open problem by Broadbent and Grilo (FOCS '20) about the possibility of NIZK for QMA in the shared Bell pair model via the Fiat-Shamir transformation.
Homomorphic Encryption and Zero Knowledge Proofs are two trending concepts that are widely popular as data privacy preservation techniques in a wide variety of applications, especially in those associated with the newly evolved block chain technology which are immutable, distributed and secure. Zero knowledge proof is a cryptographic technique can provide proof that a certain statement is correct, without revealing any details about the statement, while homomorphic encryption allows to perform computations on encrypted data without decrypting it. This article explores the significance of the data privacy aspect provided by both ZKP and Homomorphic Encryption and how it can be effectively used to improvise the privacy of blockchain applications in various domains.\n\n
Sultan Algarni, Fathy Eassa, Khalid Ali Almarhabi, Abduallah Almalaise · 7 authors
The distributed nature of Internet of Things (IoT) and its rapid increase on a large scale raises many security and privacy issues. Access control is one of the major challenges currently addressed through centralized approaches that may rely on a third party and they are constrained by availability and scalability, which may result in a performance bottleneck. Therefore, this paper proposes a novel solution to manage the delivery of lightweight and decentralized secure access control of an IoT system based on a multi-agent system and a blockchain. The main objective of the proposed solution is to build Blockchain Managers (BCMs) for securing IoT access control, as well as allowing for secure communication between local IoT devices. Moreover, the solution also enables secure communication between IoT devices, fog nodes and cloud computing.
Dinh C. Nguyen, Pubudu N. Pathirana, Ming Ding, Aruna Seneviratne
The healthcare industry has witnessed significant transformations in e-health services by using mobile-edge computing (MEC) and blockchain to facilitate healthcare operations. Many MEC-blockchain-based schemes have been proposed, but some critical technical challenges still remain, such as low Quality of Services (QoS), data privacy, and system security vulnerabilities. In this article, we propose a new decentralized health architecture, called BEdgeHealth that integrates MEC and blockchain for data offloading and data sharing in distributed hospital networks. First, a data offloading scheme is proposed where mobile devices can offload health data to a nearby MEC server for efficient computation with privacy awareness. Moreover, we design a data-sharing scheme, which enables data exchanges among healthcare users by leveraging blockchain and interplanetary file system. Particularly, a smart contract-based authentication mechanism is integrated with MEC to perform decentralized user access verification at the network edge without requiring any central authority. The real-world experiment results and evaluations demonstrate the effectiveness of the proposed BEdgeHealth architecture in terms of improved QoS with data privacy and security guarantees, compared to the existing schemes.
T Kim, Seo-Joon Lee, Dong Jin Chang, Ja‐Wook Koo · 7 authors
Although blockchain is acknowledged as one of the most important technologies to lead the fourth industrial revolution, major technical challenges regarding security breach and privacy issues remain. This issue is particularly sensitive in applied medical fields where personal health information is handled within the network. In addition, contemporary blockchain-converged solutions do not consider restricted medical data regulations that are still obstacles in many countries worldwide. This implies a crucial need for a system or solution that is suitable for the healthcare sector. Therefore, this article proposes the development of a dynamic consent medical blockchain system called DynamiChain, based on a ruleset management algorithm for handling health examination data. Moreover, medical blockchain-related studies were systematically reviewed to prove the novelty of DynamiChain. The proposed system was implemented in a scenario where the exercise management healthcare company provided health management services based on data obtained from the data provider’s hospital. The proposed research is envisioned to provide a widely compatible blockchain medical system that could be applied in future healthcare fields.