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Edge computing brings computational ability to network edges to enable low latency based on deploying devices close to the environment where the data is generated. Nevertheless, the limitation of size and energy consumption constrain the scalability and performance of edge device applications such as deep learning, although, cloud computing can be adopted to support high-performance tasks with centralized data collection. However, frequently communicating with a central cloud server brings potential risks to security and privacy issues by exposing data on the Internet. In this paper, we propose a secure continuous knowledge transfer approach to improve knowledge by collaborating with multiple edge devices in the decentralized edge computing architecture without a central server. Using blockchain, the knowledge integrity is maintained in the transfer process by recording the transaction information of each knowledge improvement and synchronizing the blockchain in each edge device. The knowledge is a trained deep-learning model that is derived by learning the local data. Using the local data of each edge device, the model is continuously trained to improve performance. Therefore, each improvement is recorded as the contribution of each edge device immutably in the decentralized edge computing architecture.

This is a study for applying Decentralized Finance (DeFi) operations in a real life Agricultural finance application focusing on how assets tokenization in general and crop insurance in particular may take advantage of fundraising, global capital markets, atomic swap operations over blockchain and finally peer-to-peer trading without intermediaries under standardized regulations and revolutionary custodial services. Descriptive statistical data presentations such as graphs and tables are used to do the analysis and evaluate the development of the sector. The paper is exploring the boundaries and the depth of Decentralized Finance while focusing on Asset Tokenization Application that are being deployed mainly in different agri-businesses starting with crop insurance and ending up with tokenizing the products over blockchain. In conclusion, asset tokenization as a representational digital asset for a traditional financial instrument is becoming an increasingly important part of modern finance and “blockchainization” of the real world. This paper addresses how agriculture sector as production sector can use asset tokenization in securing the crops by smart contracts and issuing digital tokens to fundraising for micro-insurance. Also, using blockchain to tokenize the crops for future contracts while in the same time boosting the efficiency of the agribusiness finance, crop insurance, trading in primary and secondary markets as well as exploring new markets without intermediaries, are aspects that are found in the present research.

Blockchain technology plays a pivotal role in the undergoing fourth industrial revolution or Industry 4.0. It is considered a tremendous boost to company digitalization, thus, considerable investments in blockchain are being made. However, there is no single blockchain technology, but various solutions exist, and they cannot interoperate with one each other. The ecosystem envisioned by the Industry 4.0 does not have centralized management or leading organization, so a single blockchain solution cannot be imposed. The various organizations hold their own blockchains, which must interoperate seamlessly. Despite some solutions for blockchain interoperability being proposed, the problem is still open. This paper aims to devise a secure solution for blockchain interoperability. The proposed approach consists of a relay scheme based on Trusted Execution Environment to provide higher security guarantees than the current literature. In particular, the proposed solution adopts an off-chain secure computation element invoked by a smart contract on a blockchain to securely communicate with its peered counterpart. A prototype has been implemented and used for the performance assessment, e.g., to measure the latency increase due to cross-blockchain interactions. The achieved and reported experimental results show that the proposed security solution introduces an additional latency that is entirely tolerable for transactions. At the same time, the usage of the Trusted Execution Environment imposes a negligible overhead.

This paper introduces a blockchain-based federated learning (FL) framework with incentives for participating nodes to enhance the accuracy of classification problems. Machine learning technology has been rapidly developed and changed from a global perspective for the past few years. The FL framework is based on the Ethereum blockchain and creates an autonomous ecosystem, where nodes compete to improve the accuracy of classification problems. With privacy being one of the biggest concerns, FL makes use of the blockchain-based approach to ensure privacy and security. Another important technology that underlies the FL framework is zero-knowledge proofs (ZKPs), which ensure that data uploaded to the network are accurate and private. Basically, ZKPs allow nodes to compete fairly by only submitting accurate models to the parameter server and get rewarded for that. We have conducted an analysis and found that ZKPs can help improve the accuracy of models submitted to the parameter server and facilitate the honest participation of all nodes in FL.

This study aims to explore the potential of Blockchain to transform healthcare, build the patient-driven healthcare ecosystem rather than the current institutional driven and enhance the privacy, security, and interoperability of healthcare data and check the counterfeit drugs. Interview excerpts from Industry experts/developers in the field of IT and experience from the implementation of the technology in the financial world will help understand its viability in healthcare. Consulting with domain experts is a qualitative process that involves comprehending the perception of the experts. The research paper will help the healthcare sector lay down future business strategies to redefine its businesses by overcoming the increasing threat on patients��� private data and resolving complex supply chain issues. A decentralized ledger can prevent massive revenue loss due to counterfeit drugs to track and verify each drug���s movement on the unchangeable record. The primary and secondary research is original, adding its authenticity with interview excerpts of domain experts. The results of this research paper will help identify the transparency, immutability, cost-saving, and streamlining of business to be brought by Blockchain in health care. It would be the transformational journey from innovation to market the quality products to the end consumer., CARDIOMETRY, ������������ 20 2021, Pages 80-88

Use of Unmanned Aerial Vehicles (UAVs) is rapidly increasing in various domains such as disaster management, delivery of goods, surveillance, military, etc. Significant issues in the expansion of UAV-based applications are the security of (IoT to UAV) communication, and the limited flight time of the UAVs and IoT devices considering the limited battery power. Standalone UAVs are not capable of accomplishing several tasks, and therefore swarm of UAVs is being explored. Security issues in the swarm of UAVs do not allow the applications to leverage the full benefits that one can offer. Several recent studies have proposed the use of a distributed network of UAVs to upgrade the level of security in the swarm of UAVs. In this paper, a framework for secure and reliable energy trading among UAVs and charging stations is presented. Advanced blockchain, based on the tangle data structure is used to create a distributed network of UAVs and charging stations. The proposed model allows the UAVs to buy energy from the charging station in exchange for tokens. If the UAV does not have sufficient tokens to buy the energy, then the model allows the UAV to borrow tokens from the charging station. The borrowed tokens can be repaid back to the charging station with interest or late fees. A game-theoretic model is used for deciding the buying strategy of energy for UAVs. Numerical analysis shows that the proposed model helps in providing increased utility for the swarm of UAVs and charging stations in a secure and cost-optimal way as compared to the conventional schemes. The results can eventually be applied to IoT devices that constantly need energy to perform under ideal conditions. This work was supported by Qatar National Research Fund (a member of The Qatar Foundation) under Grant NPRP10-1205-160012. The review of this article was coordinated by Dr. F. Tang.

Background One of the tasks in the iDASH Secure Genome Analysis Competition in 2018 was to develop blockchain-based immutable logging and querying for a cross-site genomic dataset access audit trail. The specific challenge was to design a time/space efficient structure and mechanism of storing/retrieving genomic data access logs, based on MultiChain version 1.0.4 (https://www.multichain.com/). Methods Our technique uses the MultiChain stream application programming interface (which affords treating MultiChain as a key value store) and employs a two-level index, which naturally supports efficient queries of the data for single clause constraints. The scheme also supports heuristic and binary search techniques for queries containing conjunctions of clause constraints, and timestamp range queries. Of note, all of our techniques have complexity independent of inserted data set size, other than the timestamp ranges, which logarithmically scale with input size. Results We implemented our insertion and querying techniques in Python, using the MultiChain library Savoir (https://github.com/dxmarkets/savoir), and comprehensively tested our implementation across a benchmark of datasets of varying sizes. We also tested a port of our challenge submission to a newer version of MultiChain (2.0 beta), which natively supports multiple indices. Conclusions We presented creative and efficient techniques for storing and querying log file data in MultiChain 1.0.4 and 2.0 beta. We demonstrated that it is feasible to use a permissioned blockchain ledger for genomic query log data when data volume is on the order of hundreds of megabytes and query times of dozens of minutes is acceptable. We demonstrated that evolution in the ledger platform (MultiChain 1 to 2) yielded a 30%-40% increase in insertion efficiency. All source code for this challenge has been made available under a BSD-3 license from https://github.com/sandialabs/idash2018task1/.