For the difficulties in sharing sensitive data among financial institutions, hidden dangers in data security, and high financial risk control costs, the paper proposed a secure data sharing solution based on blockchain technology with proxy re-encryption technology. The solution consists of data sharing model and data sharing protocol. Firstly, using the distributed storage, decentralized management and non-tampering characteristics of the blockchain, we designed a data security sharing model. The model sets access control strategies on the blockchain platform, and uses the blockchain platform and distributed databases to store encrypted data together to prevent sensitive data from being tampered with and leaked. The data sharing protocol uses identity-based proxy re-encryption technology and distributed key generation technology. The protocol selects proxy nodes by the proof-of-stake algorithm, and realizes data sharing among users by re-encrypting sensitive data. The analysis of the solution discusses the correctness and security of the proposed scheme in terms of key generation.
Muhammad Al-Abdullah, Izzat Alsmadi, Ruwaida AlAbdullah, Bernie Farkas
Purpose The paper posits that a solution for businesses to use privacy-friendly data repositories for its customers’ data is to change from the traditional centralized repository to a trusted, decentralized data repository. Blockchain is a technology that provides such a data repository. However, the European Union’s General Data Protection Regulation (GDPR) assumed a centralized data repository, and it is commonly argued that blockchain technology is not usable. This paper aims to posit a framework for adopting a blockchain that follows the GDPR. Design/methodology/approach The paper uses the Levy and Ellis’ narrative review of literature methodology, which is based on constructivist theory posited by Lincoln and Guba. Using five information systems and computer science databases, the researchers searched for studies using the keywords GDPR and blockchain, using a forward and backward search technique. The search identified a corpus of 416 candidate studies, from which the researchers applied pre-established criteria to select 39 studies. The researchers mined this corpus for concepts, which they clustered into themes. Using the accepted computer science practice of privacy by design, the researchers combined the clustered themes into the paper’s posited framework. Findings The paper posits a framework that provides architectural tactics for designing a blockchain that follows GDPR to enhance privacy. The framework explicitly addresses the challenges of GDPR compliance using the unimagined decentralized storage of personal data. The framework addresses the blockchain–GDPR tension by establishing trust between a business and its customers vis-à-vis storing customers’ data. The trust is established through blockchain’s capability of providing the customer with private keys and control over their data, e.g. processing and access. Research limitations/implications The paper provides a framework that demonstrates that blockchain technology can be designed for use in GDPR compliant solutions. In using the framework, a blockchain-based solution provides the ability to audit and monitor privacy measures, demonstrates a legal justification for processing activities, incorporates a data privacy policy, provides a map for data processing and ensures security and privacy awareness among all actors. The research is limited to a focus on blockchain–GDPR compliance; however, future research is needed to investigate the use of the framework in specific domains. Practical implications The paper posits a framework that identifies the strategies and tactics necessary for GDPR compliance. Practitioners need to compliment the framework with rigorous privacy risk management, i.e. conducting a privacy risk analysis, identifying strategies and tactics to address such risks and preparing a privacy impact assessment that enhances accountability and transparency of a blockchain. Originality/value With the increasingly strategic use of data by businesses and the contravening growth of data privacy regulation, alternative technologies could provide businesses with a means to nurture trust with its customers regarding collected data. However, it is commonly assumed that the decentralized approach of blockchain technology cannot be applied to this business need. This paper posits a framework that enables a blockchain to be designed that follows the GDPR; thereby, providing an alternative for businesses to collect customers’ data while ensuring the customers’ trust.
With the recent development of Internet of Things (IoT) in the next generation cyber-physical system (CPS) such as autonomous driving, there is a significant requirement of big data analysis with high accuracy and low latency. For efficient big data analysis, deep learning (DL) supports strong analytic capability; it has been applied at the cloud and edge layers by extensive research to provide accurate data analysis at low latency. However, existing researches failed to address certain challenges, such as centralized control, adversarial attacks, security, and privacy. To this end, we propose DeepBlockIoTNet, a secure DL approach with blockchain for the IoT network wherein the DL operation is carried out among the edge nodes at the edge layer in a decentralized, secure manner. The blockchain provides a secure DL operation and removes the control from a centralized authority. The experimental evaluation demonstrates that the proposed approach supports higher accuracy.
Yuntao Wang, Zhou Su, Ning Zhang, J.F. Chen · 7 authors
The exponential growth of data generated from increasing smart meters and smart appliances brings about huge potentials for more efficient energy production, pricing, and personalized energy services in smart grids. However, it also causes severe concerns due to improper use of individuals' private data, as well as the lack of transparency and auditability for data usage. To bridge this gap, in this article, we propose a secure and auditable private data sharing (SPDS) scheme under data processing-as-a-service mode in smart grid. Specifically, we first present a novel blockchain-based framework for trust-free private data computation and data usage tracking, where smart contracts are employed to specify fine-grained data usage policies (i.e., who can access what kinds of data, for what purposes, at what price) while the distributed ledgers keep an immutable and transparent record of data usage. A trusted execution environment based off-chain smart contract execution mechanism is exploited as well to process confidential user datasets and relieve the computation overhead in blockchain systems. A two-phase atomic delivery protocol is designed to ensure the atomicity of data transactions in computing result release and payment. Furthermore, based on contract theory, the optimal contracts are designed under information asymmetry to stimulate user's participation and high-quality data sharing while optimizing the payoff of the energy service provider. Extensive simulation results demonstrate that the proposed SPDS can effectively improve the payoffs of participants, compared with conventional schemes.
Nowadays, the digitalization of urban environments is redefining the public and private sectors. Moreover, Internet of Things (IoT) platforms, cloud computing infrastructure and smart devices are exchanging tremendous amount of data. This harmonious integration of the cyber capabilities of the corresponding devices with the physical world generates new opportunities in many areas; however it raises a lot of security and privacy challenges due to the diversity of sources and stakeholders, the centralized data management and the resulting lack of trust and governance. Hence, we introduce "SmartPrivChain" a Smart Blockchain Based System for preserving privacy and security in a smart city environment. The proposed scheme is different from the existing approaches on many points. The data privacy is preserved by combining data access control and data usage auditing measures based on smart contracts. In addition, the proposed solution is compliant with the main privacy laws and regulations especially the obligations of the European Union General Data Protection Regulation (GDPR). Lastly, we propose an enhanced Proof of Reputation (PoR) consensus scheme using a multidimensional Trust model.
Mirko Zichichi, Stefano Ferretti, Gabriele D’Angelo, Victor Rodrı́guez-Doncel
This paper presents an architecture of a Personal Information Management System, in which individuals can define the access to their personal data by means of smart contracts. These smart contracts, running on the Ethereum blockchain, implement access control lists and grant immutability, traceability and verifiability of the references to personal data, which is stored itself in a (possibly distributed) file system. A distributed authorization mechanism is devised, where trust from multiple network nodes is necessary to grant the access to the data. To this aim, two possible alternatives are described: a Secret Sharing scheme and Threshold Proxy Re-Encryption scheme. The performance of these alternatives is experimentally compared in terms of execution time. Threshold Proxy Re- Encryption appears to be faster in different scenarios, in particular when increasing message size, number of nodes and the threshold value, i.e. number of nodes needed to grant the data disclosure.
Abstract Nowadays, the exponential increase in the usage of drones in various realms of societal and military applications necessitates advancements and stability in drone communication. Drones have proven their potential in providing real‐time cost‐efficient solutions for several applications like healthcare, smart grid surveillance, smart city monitoring, and border surveillance. Though it has many security and privacy issues, researchers across the globe have given numerous solutions to protect drone communication from cyber‐attacks. Most of these solutions were based on cryptographic techniques and are highly compute extensive. There exist few blockchain‐based solutions, which suffer from high transaction storage costs with communication reliability, latency, and bandwidth issues. Motivated by these facts, in this paper, we present a comprehensive survey to secure drone communication and propose a blockchain‐based secure and intelligent drone communication architecture underlying 5G communication network and artificial intelligence (AI) techniques. The proposed architecture uses an InterPlanetary File System (IPFS) as a platform for data storage, which ensures improved network performance, communication security and privacy, and reduces transaction storage cost. Further, it facilitates efficient drone communication in providing dynamic, flexible, and on‐the‐fly decisions competencies through 5G and AI technologies. Then, we incorporate a healthcare‐based case study using the proposed architecture. At last, future research challenges and directions are emphasized for improvement in this research area.
Data privacy and sharing has always been a critical issue when trying to\nbuild complex deep learning-based systems to model data. Facilitation of a\ndecentralized approach that could take benefit from data across multiple nodes\nwhile not needing to merge their data contents physically has been an area of\nactive research. In this paper, we present a solution to benefit from a\ndistributed data setup in the case of training deep learning architectures by\nmaking use of a smart contract system. Specifically, we propose a mechanism\nthat aggregates together the intermediate representations obtained from local\nANN models over a blockchain. Training of local models takes place on their\nrespective data. The intermediate representations derived from them, when\ncombined and trained together on the host node, helps to get a more accurate\nsystem. While federated learning primarily deals with the same features of data\nwhere the number of samples being distributed on multiple nodes, here we are\ndealing with the same number of samples but with their features being\ndistributed on multiple nodes. We consider the task of bank loan prediction\nwherein the personal details of an individual and their bank-specific details\nmay not be available at the same place. Our aggregation mechanism helps to\ntrain a model on such existing distributed data without having to share and\nconcatenate together the actual data values. The obtained performance, which is\nbetter than that of individual nodes, and is at par with that of a centralized\ndata setup makes a strong case for extending our technique across other\narchitectures and tasks. The solution finds its application in organizations\nthat want to train deep learning models on vertically partitioned data.\n
With the tremendous pervasion of location-based services (LBSs) in vehicular networks, the location privacy of vehicles has become an utmost concern. K-anonymity is one of the most popular privacy protection solutions, in which the real location of the request vehicle (RV) can be covered by a cloaking area including the location of k -1 cooperative vehicles (CVs). However, K-anonymity assumes all CVs are always honest and thus offering opportunities for dishonest CVs to provide false location information. To combat such threats, we propose a trusted cloaking area construction (TCAC) scheme based on the trust mechanism to protect the location privacy of vehicles. In this article, the trust value is not only used to identify dishonest CVs, but also utilized to decide the LBS request of RV. A low trust value will make the LBS request be rejected due to dishonest and selfish cooperative behaviors when the RV has played the role of CV. To deal with the massive trust requirements caused by frequent vehicle movement, edge computing is employed to assist trust value evaluation. Moreover, traditional central and distributed trust data management may be unsuitable for vehicular networks. We also propose a blockchain-based trust data management method by combining vehicular regions partition, so as to rapidly evaluate trust value during the cloaking area construction. The security analysis and simulation results indicate that our proposed scheme is resilient to suppress dishonest CVs, inspire selfish CVs, and protect the location privacy of vehicles effectively, whereas the required computation time and communication cost are both limited.
Vehicular ad hoc network(VANET) is a special mobile ad hoc network (MANET) which plays an important role in the intelligent traffic system(ITS). Based on the high mobility of VANETs, the security problems have not been reasonably solved when we enjoy the convenience brought by the Location Based Service(LBS). We present a blockchain-based trust management model for location privacy preserving. The scheme allows vehicles to use certificate to request LBS without revealing their privacy information. We construct anonymous cloaking region to ensure the privacy security of vehicles. We propose a trust management algorithm to constrain and standardize the behavior of vehicles, and use blockchain to implement the data security of vehicles. In the experiments, we conduct the tests with various data sets. Security analysis and experiments show that the system is resilient to sorts of trust model attacks, which can better preserve the privacy security of vehicles. Simulation results reveal that the proposed system is effective and feasible in collect.
Pavlo Gaiduk, Kumar Rajeev Ranjan, Thomas Basmer, Florian Tschorsch
Cooperative intelligent transport systems promise considerable improvements on road safety and the utilization of transport infrastructures. Current approaches, however, build upon policies to protect privacy, which raise serious concerns. In this paper, we propose a privacy-preserving public key infrastructure (PKI) for vehicle-to-everything communication. We use zero-knowledge proofs to authenticate, while still being able to hide identities. In order to exclude malicious actors, we integrate an anonymous reputation-based blacklisting scheme. Our benchmarks on an on-board connectivity unit with resource-constrained hardware confirms the feasibility of the approach. Specifically, we expect approximately 67 kB payload and 35 minutes computation time per day to authenticate.
In every direction, there is a lot of noise about the Internet of Things (IoT) and its impact on everything. The technology of IoT is a huge network of interrelated devices and human beings that record and transmit the data to each other about the way they are used and about their surroundings. Conventional networks of IoT rely on a concentrated structure with finite scalability among other negative aspects. Hence, blockchain can deal with the IoT by providing many benefits and security to the data of the network. Globally, with the growth of technologies, companies and organizations are relying upon their data systems. Issues about missing or robbing of data are becoming a constant in news headlines because organizations depend more and more upon their computer systems to collect confidential information of customers. Therefore, in this chapter, the detailed background of IoT is introduced. Then, the problems of IoT are illustrated where blockchain can act as a rescue for security issues of IoT. Furthermore, the blockchain is described in detail with an introduction to its architecture, major features, approaches of data secrecy, and mining process. Moreover, an idea of IoT based on blockchain with applications, security, and confidentiality is described, and finally, disputes of blockchain are illustrated. The main motive of this chapter is to focus on the open research issues and directions of possible upcoming research on blockchain for IoT, as well as on the services of security and confidentiality for data using blockchain.
This chapter explores an incentivized blockchain-based firmware update scheme tailored for Autonomous Vehicles (AVs). As the number of autonomous vehicles increases, the security and reliability of AVs require complex server infrastructure, thus making it very expensive for the manufacturers. Blockchain was first introduced in 2008 as the underline technology behind the cryptocurrency known as Bitcoin to help make the peer-to-peer exchange of value without a centralized third party. A blockchain is a distributed, immutable, and append-only data structure formed by a sequence of blocks that are chronologically and cryptographically linked together. Attribute-based encryption (ABE) is an encryption scheme that allows access control over encrypted data. The manufacturer deploys a smart-contract by broadcasting a transaction to the blockchain network. A smart contract is used to ensure the authenticity and integrity of firmware updates, and more importantly to manage the reputation scores of AVs that transfer the new updates to other AVs.
<title>Abstract</title> Data is the most important factor in building a smart city. City data is composed of many data islands, such as transportation, industry, and residents. In order to build a smart city, breaking data islands, achieving trusted and collaborative sharing of data, while protecting data privacy are essential. As a distributed ledger, the blockchain can solve the problem of data trust. Federated learning achieves data privacy protection by sharing model parameters instead of original data. However, it still has some problems such as malicious nodes and differential attacks. This paper proposes a data sharing mechanism that combines blockchain and federated learning over smart city. Firstly, the blockchain is combined to ensure the credibility of the performance information of the work nodes, then the work node selection algorithm is designed, and a consensus incentive mechanism IPoQ is proposed for efficient federated learning tasks. Finally, differential privacy technology is introduced to resist differential attack. Experimental results show that the methods proposed in this paper achieves an effective federated learning data sharing mechanism.
With the continuous development of the Internet era, people's demand for network security is increasingly high, information is an essential component of the network, which implies numerous privacy, secrets, but also contains a large number of value, thus generating a multiparty trust issues of data security. Blockchain technology itself is still in the early stages of rapid development, the existing blockchain system in the design and implementation of the use of distributed systems, cryptography, game theory, network protocols and many other disciplines, for learning the principles and practical applications have brought considerable challenges. The blockchain, with its decentralized quality, quickly captures the attention of the public and solves many security problems derived from data security, thus attracting wide attention from people. In recent years, along with the increasing maturity of homomorphic encryption technology and push new, it is more and more people's favour and attention.
Abstract Even though there is continuous improvement in road and vehicle safety, road traffic incidents have been increasing over last few decades. There is a need to reduce traffic incidents like accidents through predictive analysis and timely warnings while at the same time data related to accidents and traffic violations need to be maintained in a tamper proof storage system that can be retrieved for forensic analysis and law enforcement at a later stage. The Secure Incident and Evidence Management Framework (SIEMF) proposed in this work address these two challenges of predictive modeling for timely warning and secure evidence management for forensics analysis in case of accidents and traffic violations. The system proposes a deep learning based predictive incident modeling with blockchain and CP-ABE based access control for the incident data stored in blockchain.
Today healthcare industries are maintaining COVID-19 patients' information electronically which includes patients' diagnostic reports, patients' private information, and doctor prescriptions. However, the COVID-19, patient sensitive information is currently stored in centralized or third-party storage model. One of the key challenge of centralized storage model is the preserving privacy of patient information and transparency in the system. The privacy risk include illegitimate access to sensitive information of patient such as identification details access and misutilization of patient information and their clinical records. To overcome this challenge, we proposed a distributed on-chain and off-chain storage model using consortium blockchain and interplanetary file systems (IPFS). The proposed framework though maintaining patient privacy makes it easier for legitimate entities like healthcare providers (e.g., physicians and clinical staffs) to access clinical data of COVID-19 patients'.
the instinct characteristics of blockchain technology to write transactions on distributed ledgers offers new opportunities for government to improve transparency, prevent fraud, and establish trust in the public sector. However, there still exits the challenge to protect data confidentiality, authenticity and ownership when sharing and exchanging e-document in decentralized blockchain network. In order to address this concern, we propose a fusion scheme of CP-ABE and Blockchain called GovChain. In GovChain, a blockchain framework is used to implement trusted identity authentication environment and improve scalability of CP-ABE policy. Moreover, encrypted e-government documents are stored on off-chain InterPlanetary File System(IPFS) and the data users can be authorized to obtain the index of documents on the chain. Finally, the security analysis is given in GovChain to prove the security of proposed fusion scheme. Meanwhile, experimental results also show that our system is feasible and effective.
Although Blockchain technology is formerly invented for digital currencies such as Bitcoin, its applications have extended into such areas as fair voting, healthcare, banking, and digital identity. A blockchain `s data is cryptographically connected and distributed across multiple computers, making them nearly impossible to temper with. Hence, this paper considers the possible use of introducing blockchain technology for digital identity management system for the issue of digital identity (passport) in Myanmar. Through blockchain technology, all the passport offices in Myanmar will be connected to each other in decentralized environment and enough passport information of a person can be securely shared within peers. Therefore, the proposed system can hinder the illegal duplication of passports (different types) since a valid passport can be issued only once to a person (except passport loss, renewal and expired) and it is impossible for a person to apply more than one passport type in the decentralized system. In addition, in the proposed system, the authenticity of passport can also be verified after granting permission for international travel. Therefore, the proposed system can be effectively applied for the passport offices in Myanmar for verifying the passport application and its data authentication.
Pronaya Bhattacharya, Payal Mehta, Sudeep Tanwar, Mohammad S. Obaidat · 5 authors
The paper proposes a light-weight blockchain (BC)-envisioned scheme HeaL, that ensures secure and trusted exchange of electronic health records (EHR) over open wireless channels, with minimum encryption and signing overheads. HeaL operates in two phases. In the first phase, proximity sensor nodes (PSN) are mounted over the patient to form a wireless body area network (WBAN). The nodes elect a cluster-head (CH) in its vicinity based on resource capability to forward data to gateway sensor nodes (GSN) in WBAN, with EHR meta-information recorded in BC. Then, in the second phase, GSN executes a lightweight signcryption scheme that combines encryption and signing of data among authorized stakeholders. The data is exchanged over open channels and is accessible to authorized personals by fetching secure keys from Inter-planetary file systems (IPFS). The mined information is finally stored as block ledgers in global chain structures to reduce computational overheads. The proposed scheme HeaL is compared against existing schemes in terms of parameters like transaction and signing cost, transactional throughput, and computational and communication costs. In simulation, HeaL achieves an average signing cost and verifying cost of 3.32 seconds (s) and 6.52 s, respectively. For 200 blocks, the mining latency is 3.325 s, compared to traditional schemes with a latency of 7.8 s. The obtained transactional throughput is 142.78 Mbps, compared to traditional 102.45 Mbps. In security evaluation, the computation cost (CC) is 45.80 milli-seconds (ms), and communication cost (CCM) is 97 bytes, which indicates the viability of the proposed scheme against other state-of-the-art approaches.
Nowadays, more and more sensors, devices and applications are connected in Industrial Internet of Things (IIoT), producing massive real-time flows which need to be scheduled for Quality-of-Service provision. To realize application-aware and adaptive flow scheduling, the problem of traffic classification must be addressed at first. When edge computing paradigm is introduced into IIoT, the traffic classification service can be deployed on edge node in the near-end. Recently, deep-learning-based IIoT traffic classification methods show better performance, but the computational cost of deep learning model is too high to be deployed on edge node. Moreover, increasingly unknown flows generated by new devices and emerging industrial APPs lead to frequent training of traffic classifiers. It is difficult to migrate the complex process of classifier training from cloud server to edge nodes with limited resources. To address these issues, we take the benefits of hash mechanism and consensus mechanism in blockchain to design a lightweight IIoT traffic classification service, which is more applicable for edge computing paradigm. First, inspired by the hash mechanism in blockchain and the learning to hash for big data, we propose a new learning-to-hash method named extension hashing. By this method, we can build the set of binary coding tress (BCT set), then generating hash table for more efficient k-nearest neighbor-based classification without complex classifier training. Then, we design a new voting-based consensus algorithm to synchronize the BCT sets and the hash tables across edge nodes, thereby providing the traffic classification service. Finally, we conduct data-driven simulations to evaluate the proposed service. By comparing traffic classification results on public data set, we can see that the proposed service achieves the highest classification accuracy with the minimal time cost and memory usage.
COVID-19 is a major global public health challenge and difficult to control in a short time completely. To prevent the COVID-19 epidemic from continuing to worsen, global scientific research institutions have actively carried out studies on COVID-19, thereby effectively improving the prevention, monitoring, tracking, control, and treatment of the epidemic. However, the COVID-19 electronic medical records (CEMRs) among hospitals worldwide are managed independently. With privacy consideration, CEMRs cannot be made public or shared, which is not conducive to in-depth and extensive research on COVID-19 by medical research institutions. In addition, even if new research results are developed, the disclosure and sharing process is slow. To address this issue, we propose a blockchain-based medical research support platform, which can provide efficient and privacy-preserving data sharing against COVID-19. First, hospitals and medical research institutions are treated as nodes on the alliance chain, so consensus and data sharing among the nodes is achieved. Then, COVID-19 patients, doctors, and researchers need to be authenticated in various institutes. Moreover, doctors and researchers need to be registered with the Fabric certificate authority. The CEMRs for COVID-19 patients uses the blockchain's pseudonym mechanism to protect privacy. After that, doctors upload CEMRs on the alliance chain, and researchers can obtain CEMRs from the alliance chain for research. Finally, the research results will be published on the blockchain for doctors to use. The experimental results show that the read and write performance and security performance on the alliance chain meet the requirements, which can promote the wide application of scientific research results against COVID-19.