106 research outputs found
Is Blockchain for Internet of Medical Things a Panacea for COVID-19 Pandemic?
The outbreak of the COVID-19 pandemic has deeply influenced the lifestyle of
the general public and the healthcare system of the society. As a promising
approach to address the emerging challenges caused by the epidemic of
infectious diseases like COVID-19, Internet of Medical Things (IoMT) deployed
in hospitals, clinics, and healthcare centers can save the diagnosis time and
improve the efficiency of medical resources though privacy and security
concerns of IoMT stall the wide adoption. In order to tackle the privacy,
security, and interoperability issues of IoMT, we propose a framework of
blockchain-enabled IoMT by introducing blockchain to incumbent IoMT systems. In
this paper, we review the benefits of this architecture and illustrate the
opportunities brought by blockchain-enabled IoMT. We also provide use cases of
blockchain-enabled IoMT on fighting against the COVID-19 pandemic, including
the prevention of infectious diseases, location sharing and contact tracing,
and the supply chain of injectable medicines. We also outline future work in
this area.Comment: 15 pages, 8 figure
Convergence of Blockchain and Edge Computing for Secure and Scalable IIoT Critical Infrastructures in Industry 4.0
This is the author accepted manuscript. The final version is available from IEEE via the DOI in this recordCritical infrastructure systems are vital to underpin
the functioning of a society and economy. Due to ever-increasing
number of Internet-connected Internet-of-Things (IoTs) / Industrial IoT (IIoT), and high volume of data generated and collected,
security and scalability are becoming burning concerns for
critical infrastructures in industry 4.0. The blockchain technology
is essentially a distributed and secure ledger that records all
the transactions into a hierarchically expanding chain of blocks.
Edge computing brings the cloud capabilities closer to the
computation tasks. The convergence of blockchain and edge
computing paradigms can overcome the existing security and
scalability issues. In this paper, we first introduce the IoT/IIoT
critical infrastructure in industry 4.0, and then we briefly present
the blockchain and edge computing paradigms. After that, we
show how the convergence of these two paradigms can enable
secure and scalable critical infrastructures. Then, we provide a
survey on state-of-the-art for security and privacy, and scalability
of IoT/IIoT critical infrastructures. A list of potential research
challenges and open issues in this area is also provided, which
can be used as useful resources to guide future research.Engineering and Physical Sciences Research Council (EPSRC
Privacy-Preserving Blockchain-Based Federated Learning for IoT Devices
Home appliance manufacturers strive to obtain feedback from users to improve
their products and services to build a smart home system. To help manufacturers
develop a smart home system, we design a federated learning (FL) system
leveraging the reputation mechanism to assist home appliance manufacturers to
train a machine learning model based on customers' data. Then, manufacturers
can predict customers' requirements and consumption behaviors in the future.
The working flow of the system includes two stages: in the first stage,
customers train the initial model provided by the manufacturer using both the
mobile phone and the mobile edge computing (MEC) server. Customers collect data
from various home appliances using phones, and then they download and train the
initial model with their local data. After deriving local models, customers
sign on their models and send them to the blockchain. In case customers or
manufacturers are malicious, we use the blockchain to replace the centralized
aggregator in the traditional FL system. Since records on the blockchain are
untampered, malicious customers or manufacturers' activities are traceable. In
the second stage, manufacturers select customers or organizations as miners for
calculating the averaged model using received models from customers. By the end
of the crowdsourcing task, one of the miners, who is selected as the temporary
leader, uploads the model to the blockchain. To protect customers' privacy and
improve the test accuracy, we enforce differential privacy on the extracted
features and propose a new normalization technique. We experimentally
demonstrate that our normalization technique outperforms batch normalization
when features are under differential privacy protection. In addition, to
attract more customers to participate in the crowdsourcing FL task, we design
an incentive mechanism to award participants.Comment: This paper appears in IEEE Internet of Things Journal (IoT-J
Beyond oracles â a critical look at real-world blockchains
This thesis intends to provide answers to the following questions: 1) What is the oracle problem, and how do the limitations of oracles affect different real-world applications? 2) What are the characteristics of the portion of the literature that leaves the oracle problem unaddressed? 3) Who are the main contributors to solving the oracle problem, and which issues are they focusing on? 4) How can the oracle problem be overcome in real-world applications? The first chapter aims to answer the first question through a literature review of the most current papers published in the field, bringing clarity to the blockchain oracle problem by discussing its effects in some of the most promising real-world blockchain applications. Thus, the chapter investigates the sectors of Intellectual Property Rights (IPRs), healthcare, supply chains, academic records, resource management, and law. By comparing the different applications, the review reveals that heterogeneous issues arise depending on the sector. The analysis supports the view that the more trusted a system is, the less the oracle problem has an impact. The second chapter presents the results of a systematic review intended to highlight the state-of-the-art of real-world blockchain applications using the oracle problem as a lens of analysis. Academic papers proposing real-world blockchain applications were reviewed to see if the authors considered the oracleâs role in the applications and related issues. The results found that almost 90% of the inspected literature neglected the role of oracles, thereby proposing incomplete or irreproducible projects. Through a bibliometric analysis, the third chapter sheds light on the institutions and authors that are actively contributing to the literature on oracles and promoting progress and cooperation. The study shows that, although there is still a lack of collaboration worldwide, there are dedicated authors and institutions working toward a similar and beneficial cause. The results also make it clear that most areas of oracle research are poorly addressed, with some remaining untouched. The fourth and last chapter focuses on a case study of a dairy company operating in the northeast region of Italy. The company applied blockchain technology to support the traceability of their products worldwide, and the study investigated the benefits of their innovation from the point of view of sustainability. The study also considers the role of oracle management, as it is a critical aspect of a blockchain-based project. Thus, the relationship between the company, the blockchain oracle, and the supervising authority is discussed, offering insight into how sustainable innovations can positively impact supply chain management. This work as a whole aims to shed light on blockchain oracles as an academic area of research, explaining why the study of oracles should be considered the backbone of blockchain literature development
Decentralized brokered enabled ecosystem for data marketplace in smart cities towards a data sharing economy
Presently data are indispensably important as cities consider data as a commodity which can be traded to earn revenues. In urban environment, data generated from internet of things devices, smart meters, smart sensors, etc. can provide a new source of income for citizens and enterprises who are data owners. These data can be traded as digital assets. To support such trading digital data marketplaces have emerged. Data marketplaces promote a data sharing economy which is crucial for provision of available data useful for cities which aims to develop data driven services. But currently existing data marketplaces are mostly inadequate due to several issues such as security, efficiency, and adherence to privacy regulations. Likewise, there is no consolidated understanding of how to achieve trust and fairness among data owners and data sellers when trading data. Therefore, this study presents the design of an ecosystem which comprises of a distributed ledger technology data marketplace enabled by message queueing telemetry transport (MQTT) to facilitate trust and fairness among data owners and data sellers. The designed ecosystem for data marketplaces is powered by IOTA technology and MQTT broker to support the trading of sdata sources by automating trade agreements, negotiations and payment settlement between data producers/sellers and data consumers/buyers. Overall, findings from this article discuss the issues associated in developing a decentralized data marketplace for smart cities suggesting recommendations to enhance the deployment of decentralized and distributed data marketplaces.publishedVersio
Achieving cybersecurity in blockchain-based systems: a survey
With The Increase In Connectivity, The Popularization Of Cloud Services, And The Rise Of The Internet Of Things (Iot), Decentralized Approaches For Trust Management Are Gaining Momentum. Since Blockchain Technologies Provide A Distributed Ledger, They Are Receiving Massive Attention From The Research Community In Different Application Fields. However, This Technology Does Not Provide With Cybersecurity By Itself. Thus, This Survey Aims To Provide With A Comprehensive Review Of Techniques And Elements That Have Been Proposed To Achieve Cybersecurity In Blockchain-Based Systems. The Analysis Is Intended To Target Area Researchers, Cybersecurity Specialists And Blockchain Developers. For This Purpose, We Analyze 272 Papers From 2013 To 2020 And 128 Industrial Applications. We Summarize The Lessons Learned And Identify Several Matters To Foster Further Research In This AreaThis work has been partially funded by MINECO, Spain grantsTIN2016-79095-C2-2-R (SMOG-DEV) and PID2019-111429RB-C21 (ODIO-COW); by CAM, Spain grants S2013/ICE-3095 (CIBERDINE),P2018/TCS-4566 (CYNAMON), co-funded by European Structural Funds (ESF and FEDER); by UC3M-CAM grant CAVTIONS-CM-UC3M; by the Excellence Program for University Researchers, Spain; and by Consejo Superior de Investigaciones CientĂficas (CSIC), Spain under the project LINKA20216 (âAdvancing in cybersecurity technologiesâ, i-LINK+ program)
- âŠ