Recently, the interest around the Blockchain concept has grown faster and, as a consequence, several studies about the possibility of exploiting such technology in different application domains have been conducted. Most of these studies highlighted the benefits that the use of the blockchain could bring in those contexts where integrity and authenticity of the data are important, e.g., for reasons linked to regulations about consumers’ healthcare. In such cases, it would be important to collect data, coming in real-time through sensors, and then store them in the blockchain, so that they can become immutable and tamper-proof. In this paper, the design and development of a software framework that allows Internet-of-Things (IoT) devices to interact directly with an Ethereum-based blockchain are reported. The proposed solution represents an alternative way for integrating a wide category of IoT devices without relying on a centralized intermediary and third-party services. The main application scenario for which the project has been conceived regards food-chain traceability in the Industry 4.0 domain. Indeed, the designed system has been integrated into the depiction of a use case for monitoring the temperature of fish products within a warehouse and during the delivery process.
Increasing popularity of cryptocurrencies lead to the rapid development of blockchain-based distributed ledger keeping systems. Industrial applications for the new technologies were soon found, enhanced by needs of security, trust and transparency along the value-chain in traceability of products, parts and processes, particularly when transactions are being maintained through several different entities. Traceability solutions are also increasingly being built upon IoT or IIoT platforms. Although this allows for highly modular and flexible architectures, severe security deficiencies make these designs inapplicable to most real-life production lines. Lack of research and practical advances in the creation of modular and easily deployable frameworks motivated development of the project underlying this dissertation.
As the core of blockchain technology, the consensus algorithm plays an important role in determining the security, data consistency, and efficiency of blockchain systems. The existing mainstream consensus algorithm is experiencing difficulties satisfying the needs of efficiency, security, and decentralization in real-world scenarios. This paper proposes a hybrid consensus algorithm based on modified Proof-of-Probability and Delegated Proof-of-Stake. In this method, the work of block generation and validation is, respectively, completed by the nodes using the modified Proof-of-Probability consensus algorithm and Delegated Proof-of-Stake consensus algorithm. When a transaction occurs, the system sends several target hash values to the whole network. Each modified Proof-of-Probability node has a different sorting algorithm, so they have different mining priorities. Every time a hash is decrypted by a modified Proof-of-Probability node, the modulo operation is done to the value of nonce, which is then compared with the expected value given by the supernode selected by the Delegated Proof-of-Stake nodes. If they are not the same, the Proof-of-Probability node enters the waiting time and the other Proof-of-Probability nodes continue to mine. By adopting two consensus algorithms, the malicious nodes must control more than 51% of the nodes that adopt the two consensus algorithms, at the same time, to effectively attack the system, that is, they must have more than 51% of the computing power and more than 51% of the tokens. This not only increases the cost of malicious attacks, but also reduces waste of computing power. In addition, the efficiency of the DPoS algorithm makes up for the deficiency of the PoP algorithm in system efficiency, and the mining behavior based on probability in the PoP algorithm also significantly weakens the ability of supernodes in the DPoS algorithm to conduct monopoly behavior or other malicious behaviors. In a word, the combination of the two algorithms makes the system perform better in terms of security, system efficiency, and decentralization.
Martín Garriga, Stefano Dalla Palma, Maxmiliano Arias, Alan De Renzis · 6 authors
Abstract Blockchain is a decentralized transaction and data management solution, the technological leap behind the success of Bitcoin and other cryptocurrencies. As the variety of existing blockchains and distributed ledgers continues to increase, adopters should focus on selecting the solution that best fits their needs and the requirements of their decentralized applications, rather than developing yet another blockchain from scratch. In this article we present a conceptual framework to aid software architects, developers, and decision makers to adopt the right blockchain technology. The framework exposes the interrelation between technological decisions and architectural features, capturing the knowledge from existing academic literature, industrial products, technical forums/blogs, and experts' feedback. We empirically show the applicability of our framework by dissecting the platforms behind Bitcoin and other top 10 cryptocurrencies, aided by a focus group with researchers and industry practitioners. Then, we leverage the framework together with key notions of the architectural tradeoff analysis method to analyze four real‐world blockchain case studies from industry and academia. Results shown that applying our framework leads to a deeper understanding of the architectural tradeoffs, allowing to assess technologies more objectively and select the one that best fit developers' needs, ultimately cutting costs, reducing time‐to‐market and accelerating return on investment.
Electronic health records (EHRs) have become a popular method to store and manage patients’ data in hospitals. Sharing these records makes the current healthcare data management system more accurate and cost-efficient. Currently, EHRs are stored using the client/server architecture by which each hospital retains the stewardship of the patients’ data. The records of a patient are scattered among different hospitals using heterogeneous database servers. These limitations constitute a burden towards a personalized healthcare, when it comes to offering a cohesive view and a shared, secure and private access to patients’ health history for multiple allied professionals and the patients. The data availability, privacy and security characteristics of the blockchain have a propitious future in the healthcare presenting solutions to the complexity, confidentiality, integrity, interoperability and privacy issues of the current client/server architecture-based EHR management system. This paper analyzes and compares the performance of the blockchain and the client/server paradigms. The results reveal that notable performance can be achieved using blockchain in a patient-centric approach. In addition, the immutable and valid patients’ data in the blockchain can aid allied health professionals in better prognosis and diagnosis support through machine learning and artificial intelligence.
The objective of this research is to present the use of blockchain technology, the internet of things and fog computing to develop the potential of school management for smart education. By using the blockchain to record and store various pieces of information the organization will create credibility of administrative data in all departments and will reduce corruption. Data can be examined transparently, especially the financial and budget management and procurement of durable articles. Regarding the academic work and registration, it can be used to store learners' information, educational history, information of enrollment, academic results, and participation in the various activities of the educational institutions. It can create credibility in the management of information about content, learning and ability assessment results that students receive, and these can be recorded and stored in a blockchain that can be safely distributed. In addition, IoT and fog computing are integrated with AI systems embedded in various modern devices to be applied in environmental management and smart education management. IoT and fog computing help to support and respond quickly to questions about the use of all types of equipment for real-time management of executives, personnel and students, as well as creating new work and learning styles that can solve the situation of dangerous communicable diseases, such as the COVID-19 situation, or can solve emergency situations that will emerge in the future by working and studying from home. It can organize and share resources for work and learning together to access the organization from outside anywhere and at any time
Recently, blockchain has elicited escalating attention from academia to industry. However, blockchain is still in its initial stage, and remains a great number of non-trivial problems to be delved before being used as a generic platform. The most intractable one is the scalability problem. The deep reinforcement learning empowered adaptivity can help the blockchain network break through the bottleneck. In this paper, we study a deep reinforcement learning empowered adaptivity approach for future blockchain networks, so as to improve the scalability and meet the requirements of different users. Specifically, rather than using one consensus protocol as the best fit one, the blockchain networks launch different consensus protocols, based on users’ quality of service (QoS) requirements. To this end, we quantify four consensus protocols. Additionally, the blockchain networks are heavily hampered by the limited computation and bandwidth resources. We also dynamically allocate computation and bandwidth resources to the blockchain networks. Then we formulate these thress items, i.e., the selection of consensus protocols, computation resource, and network bandwidth resource, as a joint optimization problem. A deep reinforcement learning approach is used to solve this problem. Simulation results are presented to show the effectiveness of our proposed scheme.
COVID-19 is a severe global epidemic in human history. Even though there are particular medications and vaccines to curb the epidemic, tracing and isolating the infection source is the best option to slow the virus spread and reduce infection and death rates. There are three disadvantages to the existing contact tracing system: 1. User data is stored in a centralized database that could be stolen and tampered with, 2. User’s confidential personal identity may be revealed to a third party or organization, 3. Existing contact tracing systems [1][2] only focus on information sharing from one dimension, such as location-based tracing, which significantly limits the effectiveness of such systems.We propose a global COVID-19 information sharing and risk notification system that utilizes the Blockchain, Smart Contract, and Bluetooth. To protect user privacy, we design a novel Blockchain-based platform that can share consistent and non-tampered contact tracing information from multiple dimensions, such as location-based for indirect contact and Bluetooth-based for direct contact. Hierarchical smart contract architecture is also designed to achieve global agreements from users about how to process and utilize user data, thereby enhancing the data usage transparency. Furthermore, we propose a mechanism to protect user identity privacy from multiple aspects. More importantly, our system can notify the users about the exposure risk via smart contracts. We implement a prototype system to conduct extensive measurements to demonstrate the feasibility and effectiveness of our system.
With an increasing penetration of ubiquitous connectivity, the amount of data describing the actions of end-users has been increasing dramatically, both within the domain of the Internet of Things (IoT) and other smart devices. This has led to more awareness of users in terms of protecting personal data. Within the IoT, there is a growing number of peer-to-peer (P2P) transactions, increasing the exposure to security vulnerabilities, and the risk of cyberattacks. Blockchain technology has been explored as middleware in P2P transactions, but existing solutions have mainly focused on providing a safe environment for data trade without considering potential changes in interaction topologies. we present EdgeBoT, a proof-of-concept smart contracts based platform for the IoT built on top of the ethereum blockchain. With the Blockchain of Things (BoT) at the edge of the network, EdgeBoT enables a wider variety of interaction topologies between nodes in the network and external services while guaranteeing ownership of data and end users' privacy. in EdgeBoT, edge devices trade their data directly with third parties and without the need of intermediaries. This opens the door to new interaction modalities, in which data producers at the edge grant access to batches of their data to different third parties. Leveraging the immutability properties of blockchains, together with the distributed nature of smart contracts, data owners can audit and are aware of all transactions that have occurred with their data. we report initial results demonstrating the potential of EdgeBoT within the IoT. we show that integrating our solutions on top of existing IoT systems has a relatively small footprint in terms of computational resource usage, but a significant impact on the protection of data ownership and management of data trade.
Abstract Cloud computing based on OpenStack is widely used as a distributed computing platform. OpenStack has progressed at a rapid pace, incorporating a variety of service modules; it is supported by many companies, has a community of active developers, and a diverse user base. OpenStack uses message queue to coordinate and exchange operation and status information between services. OpenStack supports various message queue services including RabbitMQ, Qpid, and ZeroMQ, whereas its distribution architecture uses RabbitMQ. As an OpenStack’s message queue service, RabbitMQ runs on a controller node as a centralized service. In case of the centralized service, increased usage may cause slowed response times and security vulnerability. This paper proposes a Hybrid decentralized Practical byzantine fault tolerance Blockchain Framework with two-step verification for OpenStack message queue service. When compared to existing OpenStack message queue service, OpenStack with the proposed framework demonstrates identical reliability a faster response time by approximately 46.75% with a two-step verification process and decentralization approach. Additionally, a reduction in the security vulnerability in the OpenStack message queue information with saving the message queue information into each node by blockchain-based decentralized data duplication approach.
This paper presents LinSBFT, a Byzantine Fault Tolerance (BFT) protocol with the capacity of processing over 2000 smart contract transactions per second in production. LinSBFT applies to a permissionless, public blockchain system, in which there is no public-key infrastructure, based on the classic PBFT with 4 improvements: (\romannumeral1) LinSBFT achieves $O(n)$ worst-case communication volume, in contract to PBFT's $O(n^4)$; (\romannumeral2) LinSBFT rotates the leader of protocol randomly to reduce the risk of denial-of-service attacks on leader; and (\romannumeral3) each run of LinSBFT finalizes one block, which is robust against participants that are honest in one run of the protocol, and dishonest in another, and the set of participants is dynamic, which is update periodically. (\romannumeral4) LinSBFT helps the delayed nodes to catch up via a synchronization mechanism to promise the liveness. Further, in the ordinary case, LinSBFT involves only a single round of voting instead of two in PBFT, which reduces both communication overhead and confirmation time, and employs the \emph{proof-of-stake} scheme to reward all participants. Extensive experiments using data obtained from the Ethereum demonstrate that LinSBFT consistently and significantly outperforms existing in-production BFT protocols for blockchains.
Ilhaam A. Omar, Raja Jayaraman, Khaled Salah, Ibrar Yaqoob · 5 authors
Blockchain technology has disclosed unprecedented opportunities in the healthcare sector by unlocking the true value of interoperability. Specifically, the striking features of blockchain technology, such as data provenance, transparency, decentralized transaction validation, and immutability can help to compensate for stringent data management issues (e.g., patient recruitment, persistent monitoring, data management, and data analytics and accurate reporting) in clinical trials (CTs). Although several research studies show that blockchain solutions help to improve patient retention, data integrity, privacy, and ensure CTs compliance with regulatory policies, a comprehensive survey on this topic is lacking. In this survey, we provide insights into the adoption of blockchain technology in CTs. We categorize and classify the literature by devising a meticulous taxonomy of the decentralized tasks of CT and practices based on indispensable parameters. Furthermore, we provide insights on works in progress towards deploying blockchain solutions in CTs. Finally, we identify and discuss several challenges that hinder the successful implementation of blockchain technologies in CTs.
Open access
2 source records
Blockchain Technology Applications and Security
IoT and Edge/Fog Computing
Artificial Intelligence in Healthcare and Education
The concept of smart cities has become prominent in modern metropolises due to the emergence of embedded and connected smart devices, systems, and technologies. They have enabled the connection of every "thing" to the Internet. Therefore, in the upcoming era of the Internet of Things, the Internet of Vehicles (IoV) will play a crucial role in newly developed smart cities. The IoV has the potential to solve various traffic and road safety problems effectively in order to prevent fatal crashes. However, a particular challenge in the IoV, especially in Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communications, is to ensure fast, secure transmission and accurate recording of the data. In order to overcome these challenges, this work is adapting Blockchain technology for real time application (RTA) to solve Vehicle-to-Everything (V2X) communications problems. Therefore, the main novelty of this paper is to develop a Blockchain-based IoT system in order to establish secure communication and create an entirely decentralized cloud computing platform. Moreover, the authors qualitatively tested the performance and resilience of the proposed system against common security attacks. Computational tests showed that the proposed solution solved the main challenges of Vehicle-to-X (V2X) communications such as security, centralization, and lack of privacy. In addition, it guaranteed an easy data exchange between different actors of intelligent transportation systems.
Technological innovations have enabled the realization of a utopian world where all objects of everyday life, as well as humans, are interconnected to form an “Internet of Things (IoT).” These connected technologies and IoT solutions have led to the emergence of smart cities where all components are converted into a connected smart ecosystem. IoT has envisioned several areas of smart cities including the modern healthcare environment like real-time monitoring, patient information management, ambient-assisted living, ambient-intelligence, anomaly detection, and accelerated sensing. IoT has also brought a breakthrough in the medical domain by integrating stake holders, medical components, and hospitals to bring about holistic healthcare management. The healthcare domain is already witnessing promising IoT-based solutions ranging from embedded mobile applications to wearable devices and implantable gadgets. However, with all these exemplary benefits, there is a need to ensure the safety and privacy of the patient’s personal and medical data communicated to and from the connected devices and systems. For a smart city, it is pertinent to have an accessible, effective, and secure healthcare system for its inhabitants. This paper discusses the various elements of technology-enabled healthcare and presents a privacy-preserved and secure “Smart Medical System (SMS)” framework for the smart city ecosystem. For providing real-time analysis and responses, this paper proposes to use the concept of secured Mobile Edge Computing (MEC) for performing critical time-bound computations on the edge itself. In order to protect the medical and personal data of the patients and to make the data tamper-proof, the concept of blockchain has been used. Finally, this paper highlights the ways to capture and store the medical big data generated from IoT devices and sensors.
The idea of blockchains technology (BT) in the Internet of Things (IoT) is to allow the physical things to trust in the transactions held within the IoT network. The BT is a distributed, decentralized, publicly shared its digital ledger and secured technology to eternally record the transactions across the shared database. The BT in IoT can be called Trust Machine to eliminate the intermediates and enables the physical things to trust with each other. This research evaluates the performance of BT in IoT. The simulated results are tested and can be used in the sustainable development of the integration of BT and IoT.
There has been an increasing interest in blockchain technology from the health care sector in the last couple of years. The value proposition for using blockchain technology in the health care sector is to share sensitive patient data among health care entities securely and to empower patients. Blockchain technology allows patients to have an active role in developing and updating their own patient data. However, is blockchain technology really the silver bullet it seems to be? With this paper, we aim to understand the benefits and challenges of blockchain technology in the health care sector. We discuss innovation and security implications concerning blockchain technology in health care. Furthermore, we show that there is a need for more use cases to ensure the secure sharing of data within the health care sector. In our opinion, blockchain technology will not solve the issues encountered by the health care sector; in fact, it may raise more issues than it will solve.
The sudden development of the COVID-19 pandemic exposed the limitations in modern healthcare systems to handle public health emergencies. It is evident that adopting innovative technologies such as blockchain can help in effective planning operations and resource deployments. Blockchain technology can play an important role in the healthcare sector such as improved clinical trial data management by reducing delays in regulatory approvals, streamline the communication between diverse stakeholders of the supply chain etc. Moreover, the spread of misinformation has intensely increased during the outbreak and existing platforms lack the ability to validate the authenticity of data, causing people to panic and act irrationally. Thus, developing a blockchain-based tracking system is important to ensure that the information received by the public and government agencies are reliable and trustworthy. In this paper, we focus on blockchain abilities to track the COVID-19 data collected from various sources including news, healthcare professionals, researchers etc, verify and append them in a secure and trusted distributed ledger. Thus, we propose a generic framework using Ethereum smart contracts and oracles to track real-time data related to the number of new cases, deaths and recovered cases obtained from trusted sources. We present detailed algorithms that capture the interactions between stakeholders in the network. The smart contract code was developed and tested in Remix environment. We present the cost and security analysis incurred by the stakeholders and highlight the challenges and future directions of our work. Our work demonstrates that the proposed solution is economically feasible and ensures data integrity, security, transparency, data traceability among stakeholders.
<p>The sudden development of the COVID-19 pandemic exposed the limitations in modern healthcare systems to handle public health emergencies. It is evident that adopting innovative technologies such as blockchain can help in effective planning operations and resource deployments. Blockchain technology can play an important role in the healthcare sector such as improved clinical trial data management by reducing delays in regulatory approvals, streamline the communication between diverse stakeholders of the supply chain etc. Moreover, the spread of misinformation has intensely increased during the outbreak and existing platforms lack the ability to validate the authenticity of data, causing people to panic and act irrationally. Thus, developing a blockchain-based tracking system is important to ensure that the information received by the public and government agencies are reliable and trustworthy. In this paper, we focus on blockchain abilities to track the COVID-19 data collected from various sources including news, healthcare professionals, researchers etc, verify and append them in a secure and trusted distributed ledger. Thus, we propose a generic framework using Ethereum smart contracts and oracles to track real-time data related to the number of new cases, deaths and recovered cases obtained from trusted sources. We present detailed algorithms that capture the interactions between stakeholders in the network. The smart contract code was developed and tested in Remix environment. We present the cost and security analysis incurred by the stakeholders and highlight the challenges and future directions of our work. Our work demonstrates that the proposed solution is economically feasible and ensures data integrity, security, transparency, data traceability among stakeholders. </p>
This paper opts to mitigate the energy-inefficiency of the Blockchain Proof-of-Work (PoW) consensus algorithm by rationally repurposing the power spent during the mining process. The original PoW mining scheme is designed to consider one block at a time and assign a reward to the first place winner of a computation race. To reduce the mining-related energy consumption, we propose to compensate the computation effort of the runner(s)-up of a mining round, by granting them exclusivity of solving the upcoming block in the next round. This will considerably reduce the number of competing nodes in the next round and consequently, the consumed energy. Our proposed scheme divides time into epochs, where each comprises two mining rounds; in the first one, all network nodes can participate in the mining process, whereas in the second round only runners-up can take part. Thus, the overall mining energy consumption can be reduced to nearly $50\%$. To the best of our knowledge, our proposed scheme is the first to considerably improve the energy consumption of the original PoW algorithm. Our analysis demonstrates the effectiveness of our scheme in reducing energy consumption, the probability of fork occurrences, the level of mining centralization presented in the original PoW algorithm, and the effect of transaction censorship attack.
Artificial intelligence (AI) has a limitation in that it is only in the passive cognition area, so its operating process is not transparent; therefore, the technology relies on learning data. Since raw data for AI learning are processed and inspected manually to assure high quality for sophisticated AI learning, human errors are inevitable, and damaged and incomplete data and differences from the original data may lead to unexpected outputs of AI learning for which processed data are used. In this context, this research examines cases where AI learning data were inaccurate, in terms of cybersecurity, and the need for learning data management before machine learning through analysis of cybersecurity attack techniques, and we propose the direction of establishing a data-preserving AI system, which is a blockchain-based learning data environment model to verify the integrity of learning data. The data-preserving AI learning environment model is expected to prevent cyberattacks and data deterioration that may occur when data are provided and utilized in an open network for the processing and collection of raw data.
Universal connectivity is still unavailable or expensive for half of the global population, despite being critical for social participation. The deployment of crowdsourced networking infrastructures creates an opportunity for local development, where anyone can deploy a new device. In such infrastructures connectivity offer can expand incrementally and be sustainable through investment and fees resulting from the demand and consumption of content and services, including Internet access, that compensate the cost of the underlying network. While routing coordinates network data flows, economic flows can be coordinated by smart contracts built over a local distributed ledger. We define crowdsourced networks, the concept, architecture, and implementation using a local Ethereum PoA blockchain with Solidity smart contracts that compensate the data traffic contribution and consumption recorded by a traffic monitoring system, on a wireless mesh network. The prototype software has been validated in a controlled mesh network environment. Functional tests show its ability to account and route economic flows with small resource consumption, and therefore confirms these networks can develop organically by the addition of consumer and provider participants to reach the typical scale of most wireless mesh access networks and deliver networking services that aim to be socially and economically sustainable.
Blockchain is viewed as one of the most promising and disruptive inventions and is considered to have the potential to significantly change current auditing profession and reshape the business ecosystem. With the advancement of blockchain, it has been concerned in some studies that auditing could be significantly impacted and eventually replaced. Meanwhile, another viewpoint argues that blockchain technology would push the existing auditing industry to a new direction rather than eliminating the need for auditing in the immediate future. This discussion can hardly be settled without evaluation, however, studies exploring how blockchain technology can be employed in auditing practice or how continuous auditing can be conducted using blockchain technology are limited. This paper analyses the impact of blockchain features on existing audit processes and discusses the possibility of applying blockchain characteristics including immutability, distributed ledger, real-time settlement to the auditing domain. Based on the systematic analysis, this study proposes a conceptual model for blockchain-based auditing information system, which provides solutions to employ blockchain technology in auditing profession, significantly improving the efficiency and effectiveness of auditing and promoting the transformation of the auditing paradigm to real-time, continuous and intelligent auditing.
There has been revolutionary developments in the healthcare industry with the advancement of technology over the past years. Internet of Things, Cloud Computing, Blockchain technology, lab-on-chip, non-invasive and minimally invasive surgeries and so on has simplified several dreadful diseases. The research as well as healthcare industry have been greatly impacted by these new technologies. Clinical exams and self-health tracking can be done by means of miniaturized healthcare sensors that are powered by IoT. They help in early diagnosis and treatment guidance by clinicians at remote locations without directly being in contact with the users. The access control structures and inconsistent security policies have been a hinderance in meeting the security requirements of these data. Blockchain based smart contracts and enterprise-distributed ledger framework can be used for monitoring the vital signs of the patient. This enables accessing medical information of patients globally at any time along with immutable and extensive history log. In comparison with the traditional patient monitoring system, the proposed system offers better monitoring, improved connectivity and enhanced data security.