Blockchain Protocol Research Articles

GT-Chain: A Fair Blockchain for Intelligent Industrial IoT Applications

In Industrial Internet of Things (IIoT), a number of mutually untrusted devices with diverse computing resources and application requirements often need to work together to serve industrial production. When applying permissionless blockchain to process transactions among these devices, we are concerned with two types of fairness: mining fairness (i.e., miners should obtain commensurate rewards according to their respective invested computing power) and transaction-processing fairness (i.e., transaction packing and confirming is in a desired fair order). To address the two types of fairness simultaneously, this paper proposes GT-Chain, in which miners select transactions according to <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">G</u> eometric-distribution and propagate transactions with a <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">T</u> ime-to-live limit for achieving transaction-processing fairness as well as balancing the processing efficiency and fairness. Besides, GT-Chain inherits properties of a famous blockchain called FruitChain for achieving mining fairness. We then conduct a probability analysis to quantify the efficiency of transaction processing and define a Euclidean-distance-based fair degree to measure the fairness of transaction processing. Extensive simulations verify that GT-Chain can well achieve our design objectives, and our theoretical model is accurate. This paper is helpful in better designing blockchain protocols for IIoT.

An approach for the automatic verification of blockchain protocols: the Tweetchain case study

This paper proposes a model-driven approach for the security modelling and analysis of blockchain based protocols. The modelling is built upon the definition of a UML profile, which is able to capture transaction-oriented information. The analysis is based on existing formal analysis tools. In particular, the paper considers the Tweetchain protocol, a recent proposal that leverages online social networks, i.e., Twitter, for extending blockchain to domains with small-value transactions, such as IoT. A specialized textual notation is added to the UML profile to capture features of this protocol. Furthermore, a model transformation is defined to generate a Tamarin model, from the UML models, via an intermediate well-known notation, i.e., the Alice &Bob notation. Finally, Tamarin Prover is used to verify the model of the protocol against some security properties. This work extends a previous one, where the Tamarin formal models were generated by hand. A comparison on the analysis results, both under the functional and non-functional aspects, is reported here too.

Neural Fairness Blockchain Protocol Using an Elliptic Curves Lottery

To protect participants’ confidentiality, blockchains can be outfitted with anonymization methods. Observations of the underlying network traffic can identify the author of a transaction request, although these mechanisms often only consider the abstraction layer of blockchains. Previous systems either give topological confidentiality that may be compromised by an attacker in control of a large number of nodes, or provide strong cryptographic confidentiality but are so inefficient as to be practically unusable. In addition, there is no flexible mechanism to swap confidentiality for efficiency in order to accommodate practical demands. We propose a novel approach, the neural fairness protocol, which is a blockchain-based distributed ledger secured using neural networks and machine learning algorithms, enabling permissionless participation in the process of transition validation while concurrently providing strong assurance about the correct functioning of the entire network. Using cryptography and a custom implementation of elliptic curves, the protocol is designed to ensure the confidentiality of each transaction phase and peer-to-peer data exchange.

Design of a Blockchain-Based Traceability System with a Privacy-Preserving Scheme of Zero-Knowledge Proof

With the fast development of the industrial Internet, its interconnectivity poses new challenges for the cooperation of industrial entities. Cooperation among these entities is built on trust, and trust is based on high-quality industrial products at reasonable prices. A traceability system can play an essential role in objectively reflecting the production process and promoting this trust. However, traditional traceability systems often have data privacy issues. Because traceability data are collected or generated during the production process (namely, production-related data), they could be considered privacy data. Several researchers have introduced privacy protection schemes into the traceability system, such as authentication or encryption. Nevertheless, when a privacy protection scheme is established, the original data are disclosed to the legal user of the system, but the data may still be leaked intentionally or unintentionally. Except for data privacy issues, a traditional traceability system can be vulnerable to network attacks, data unavailability, and reliability issues. The authors conducted a study to overcome these shortcomings, and this paper reports the results. We built a traceability prototype system using a blockchain protocol and a zero-knowledge proof method. First, we built a blockchain to record key production process data, aiming to maintain data reliability and availability. Second, through an analysis of traceability purpose using production knowledge, the traceability purpose could be divided into multiple provable statements. By introducing privacy protection through a zero-knowledge proof, the traceability process was converted to proving relative statements. Finally, the statements were validated by a smart contract that provided openness and reliability during the traceability process. Analysis has shown that our approach could meet the requirements for high security and privacy. In addition, the paper also discusses the calculation cost of the traceability process to show our work’s viability. The traceability system described in this paper creates new possibilities for constructing a healthy and reliable trust relationship between production entities to provide further support in the development of the industrial Internet.

Private Equity and Innovations in Blockchain

Advocates of blockchain claim widespread impact will be forthcoming shortly. However, the path of innovation in blockchain is uncharted. Investors will assess where blockchain innovation will profit first and most. The timing and impact of each blockchain innovation is a key consideration for business managers. Link, Ruhm, and Siegel (2014) suggest private equity investments forecast which innovations are likely to succeed. Previous research on private equity gives insight on why that ownership structure is especially successful. Private equity investments are collected for two periods and categorized according to basic blockchain components, basic cryptocurrency payment components, and decentralized applications, particularly applications in financial services. The results suggest investors have acted prudently, investing strongly in building blocks, payment systems and fundamental applications, showing a primary emphasis on refining blockchain and realizing standard blockchain protocols before investing in highly complex applications. Further, financial services applications dominate, suggesting investors see financial services as far and away the most likely industry for imminent deconstruction.

Building DeFi Applications Using Cross-Blockchain Interaction on the Wish Swap Platform

Blockchain is a developing technology that can provide users with such advantages as decentralization, data security, and transparency of transactions. Blockchain has many applications, one of them is the decentralized finance (DeFi) industry. DeFi is a huge aggregator of various financial blockchain protocols. At the moment, the total value locked in these protocols reaches USD 82 billion. Every day more and more new users come to DeFi with their investments. The concept of decentralized finance involves the creation of a single ecosystem of many blockchains that interact with each other. The problem of combining and interacting blockchains becomes crucial to enable DeFi. In this paper, we look at the essence of the DeFi industry, the possibilities of overcoming the problem of cross-blockchain interaction, present our approach to solving this problem with the Wish Swap platform, which, in particular, provides improved fault-tolerance for cross-chain interaction by using multiple backend nodes and multisignatures. We analyze the results of the proposed solution and demonstrate how a prototype pre-sale application can be created based on the proposed concept.

Sender anonymity: Applying ring signature in gateway-based blockchain for IoT is not enough

Over the last decade, there has been extensive research into the security and privacy of blockchain technology, from the use of ring signatures to ring confidential transactions. Although existing cryptographic methods perform well on traditional blockchain architectures, they do not provide complete privacy in a hierarchical blockchain architecture for Internet of Things (IoT) devices. The blockchain technology is centered at the gateway layer in the hierarchical blockchain architecture, which can easily reveal the transaction sender using network traffic information, thereby violating the sender’s anonymity. Furthermore, the gateway can perform eclipse attacks against transaction senders on a case-by-case basis. To this end, this paper proposes a novel security and privacy blockchain protocol that is better suited to the hierarchical blockchain architecture and thus more appropriate for the IoT environment. Specifically, it leverages the relationship among IoT devices at the perception layer of the hierarchical blockchain architecture for IoT, and constructs an overlay social IoT network by exploiting devices’ multi-agent capabilities. Furthermore, circuit establishment based on multilayered encryption is applied to conceal the transaction propagation path through the overlay social IoT. Theoretical analysis shows that our novel protocol is flexible, evades a malicious gateway, and is secure under the decisional Diffie-Hellman assumption.

Securing Internet of Things devices by enabling Ethereum blockchain using smart contracts

The development of the IoT is rapidly growing. These IoT devices are mainly deployed to control and report environmental changes, prevent risks, and bring many beneficial services. However, these benefits may open doors to the adversaries in conjunction with security vulnerabilities and privacy issues. In the recent past, Blockchain has been an emerging technology that reaches several use-cases apart from cryptocurrency. For instance, IoT integration with Blockchain implementation yet indefinite required further research because of resource-constrained IoT devices and ledger-based Blockchain protocol design. This paper presents the systematic implementation of securing IoT devices by enabling the Ethereum Blockchain smart contract. The results show that the collected information is securely stored in the Blockchain after successful authentication. Practical Application: Blockchain innovations have the power to transform manufacturing, construction, healthcare and building supply chains by eliminating the middleman, streamlining operations, improving overall security, and simplifying data management. Onboarding, recordkeeping, client screening, data management, security, privacy, and transaction and trade processing are examples of several practice applications in the financial, insurance, and eHealth services industries. Thus, this study ensures security by enabling Ethereum blockchain and smart contracts in an authentic blockchain applications for building sustainable environments to improve readability and trustworthiness of the transactions.

A hybrid with distributed pooling blockchain protocol for image storage

As a distributed storage scheme, the blockchain network lacks storage space has been a long-term concern in this field. At present, there are relatively few research on algorithms and protocols to reduce the storage requirement of blockchain, and the existing research has limitations such as sacrificing fault tolerance performance and raising time cost, which need to be further improved. Facing the above problems, this paper proposes a protocol based on Distributed Image Storage Protocol (DISP), which can effectively improve blockchain storage space and reduces computational costs in the help of InterPlanetary File System (IPFS). In order to prove the feasibility of the protocol, we make full use of IPFS and distributed database to design a simulation experiment for blockchain. Through distributed pooling (DP) algorithm in this protocol, we can divide image evidence into recognizable several small files and stored in several nodes. And these files can be restored to lossless original documents again by inverse distributed pooling (IDP) algorithm after authorization. These advantages in performance create conditions for large scale industrial and commercial applications.

Towards Detection of Selfish Mining Using Machine Learning

Selfish mining is an attack against a blockchain where miners hide newly discovered blocks instead of publishing them to the rest of the network. The selfish miners continue to mine on their private chain while the honest miners waste resources mining on a shorter chain. According to the blockchain protocol, a longer chain takes precedent and shorter chains are discarded which allows the selfish miners to gain an advantage by keeping their chain secret. This attack can be used by malicious miners to earn a disproportionate share of the mining rewards or in conjunction with other attacks to steal money from cryptocurrency exchanges. Several of these attacks were launched in 2018 and 2019 with the attackers stealing as much as $18 Million. Developers made several different attempts to fix this issue, but the effectiveness of the fixes is currently unknown. Although this attack is possible against both Proof-of-Work and Proof-of-Stake blockchains, this research concentrates on detection in Proof-of-Work blockchains. As is difficult to evaluate security advances in the real-time blockchain, it is imperative to focus on simulation to evaluate blockchain security properties. To this end, we extend a blockchain simulator and add the ability to simulate selfish mining attacks. Several existing simulators are examined before choosing SimBlock for this research. Our goal is to identify the factors that identify selfish mining. Using existing research, we choose several factors that could identify an attack in an unlaunched state, an active state, or historically. We plan to use simulated data to train a machine learning model to detect selfish mining. Using the modified simulator, we generate training and test data for unlaunched and active attacks. For historical attacks, we will use historical data from known selfish mining attacks. While some existing research has examined the detection of selfish mining, it only examines active attacks. In this paper, we seek to lay the groundwork for future research into detecting attacks that are unlaunched, active, or historical.

Tri-op redactable blockchains with block modification, removal, and insertion

In distributed computations and cryptography, it is desirable to record events on a public ledger, such that later alterations are computationally infeasible. An implementation of this idea is called blockchain, which is a distributed protocol that allows the creation of an immutable ledger. While such an idea is very appealing, the ledger may be contaminated with incorrect, illegal, or even dangerous data, and everyone running the blockchain protocol has no option but to store and propagate the unwanted data. The ledger is bloated over time, and it is not possible to remove redundant information. Finally, missing data cannot be inserted later. Redactable blockchains were invented to allow the ledger to be mutated in a controlled manner. To date, redactable blockchains support at most two types of redactions: block modification and removal. The next logical step is to support block insertions. However, we show that this seemingly innocuous enhancement renders all previous constructs insecure. We put forward a model for blockchains supporting all three redaction operations and construct a blockchain that is provably secure under this formal definition.

Blockchain for Securing Healthcare Data Using Squirrel Search Optimization Algorithm

The Healthcare system is an organization that consists of important requirements corresponding to security and privacy, for example, protecting patients’ medical information from unauthorized access, communication with transport like ambulance and smart e-health monitoring. Due to lack of expert design of security protocols, the healthcare system is facing many security threats such as authenticity, data sharing, the conveying of medical data. In such situation, block chain protocol is used. In this manuscript, Efficient Block chain Network for securing Healthcare data using Multi-Objective Squirrel Search Optimization Algorithm (MOSSA) is proposed to generate smart and secure Healthcare system. In this the block chain is a decentralized and the distributed ledger device that consists of various blocks linked with digital signature schemes, consensus mechanisms and chain of hashing, offers highly reliable storage capabilities. Further the block chain parameters, such as block size, transaction size and number of block chain channels are optimized with the help of MOSSA. With the evolution of the MOSSA provide new features for enhancing security and scalability. The simulation process is executed in the JAVA platform. The experimental result of the proposed method shows higher throughput of 26.87%, higher efficiency of 34.67%, lowest delay of 22.97%, lesser computational overhead of 37.03%, higher storage cost of 34.29% when compared to the existing method such as Block chain-ECIES-HSO, Block chain-hybrid GO-FFO, Block chain-SDN-HSO algorithm for healthcare technologies.

A Secure Blockchain Platform for Supporting AI-Enabled IoT Applications at the Edge Layer

In this study, a new blockchain protocol and a novel architecture that integrate the advantages offered by edge computing, artificial intelligence (AI), IoT end-devices, and blockchain were designed, developed, and validated. This new architecture has the ability to monitor the environment, collect data, analyze it, process it using an AI-expert engine, provide predictions and actionable outcomes, and finally share it on a public blockchain platform. For the use-case implementation, the pandemic caused by the wide and rapid spread of the novel coronavirus COVID-19 was used to test and evaluate the proposed system. Recently, various authors traced the spread of viruses in sewage water and studied how it can be used as a tracking system. Early warning notifications can allow governments and organizations to take appropriate actions at the earliest stages possible. The system was validated experimentally using 14 Raspberry Pis, and the results and analyses proved that the system is able to utilize low-cost and low-power flexible IoT hardware at the processing layer to detect COVID-19 and predict its spread using the AI engine, with an accuracy of 95%, and share the outcome over the blockchain platform. This is accomplished when the platform is secured by the honesty-based distributed proof of authority (HDPoA) and without any substantial impact on the devices’ power sources, as there was only a power consumption increase of 7% when the Raspberry Pi was used for blockchain mining and 14% when used to produce an AI prediction.

Hybrid lightning protocol: An approach for blockchain scalability issue

Blockchain is the latest disruptive innovation. It is the underlying technology of cryptocurrency. However, the facts show that most cryptocurrencies are stuck in big issues such as scalability issues, resulting in longer transaction times. A two-layer solution was offered in previous studies to solve the scalability problem, but many issues emerged from this idea. Some of the 2 Layer proposals use the Proof of Work (PoW) protocol model, and some other studies use the Proof of Stake (PoS) protocol model. In this study, the authors propose the Hybrid Lightning Protocol to solve the scalability problem of Blockchain networks by combining the Proof of Work (PoW) and Proof of Stake (PoS) protocols without sharding. The author analyzes and designs the development of the Blockchain protocol based on previous research. This research is a Blockchain protocol model that can achieve a maximum throughput of around 1,668,000 transactions/second on a 2 Gbps Fiber network, which can reduce cryptocurrency volatility and shorten transaction times by solving scalability problems.

A Systematic Literature Review Toward a Blockchain Benchmarking Framework

Blockchain is a disruptive technology that focuses on the safe exchange of data between several distributed applications. Despite its widespread adoption, there are areas that require further research towards the understanding of their performance characteristics. In addition, consensus algorithms, a vital part of blockchain, require a more comprehensive understanding of their technical principles and characteristics. Along with the design of different types of consensus algorithms, several challenges, such as system scalability and power consumption, have been raised. Therefore, more comprehensive research is needed to investigate the degree to which consensus algorithms are built and how they perform. To this end, this study extends the body of knowledge and contributes towards the assessment of blockchain protocol performance. We present a comprehensive taxonomy of selected studies on blockchain performance, identifying similarities and differences while attempting to identify existing work on simulators and benchmarking frameworks that aim to explore the performance of blockchain-enabled consensus algorithms.

New Blockchain Protocol for Partial Confidentiality and Transparency (PPCT)

Running behind new technologies is increasingly becoming a non-circumventable requirement for organisms’ survival. This is not only a strategy to gain a competitive advantage in the market but it is a determinant key for their continuity and persistence. The Blockchain is at the heart of this technological revolution for which transparency, accessibility to the public and the sense of sharing are fundamental properties of its design. Despite its importance, leveraging this technology in an ethical and secure manner by ensuring confidentiality and privacy is a top concern. Through this work, we try to design a new approach to validate transactions within the Blockchain. Entitled "Protocol for Partial Confidentiality & Transparency PPCT", this new protocol makes possible to seek a compromise between the two requirements: Confidentiality & Transparency. It allows introducing a new notion of confidentiality that we have named partial confidentiality. Subsequently, it applies it on the transactions exchanged while ensuring the process of their validations by the different nodes of the Blockchain. In addition, and through the use of hashing and digital signature functions, this protocol also ensures integrity and authentication within its validation process. To present this work, we will first discuss the state of the art on the different current privacy approaches and our motivation behind this work. Then we will explain more about the different stages of this process, its benefits and areas for improvement.

Digital Governance as Recombination: The Institutional Generativity of Blockchain Protocols

Digital Governance as Recombination: The Institutional Generativity of Blockchain Protocols

An Intelligent Distributed Ledger Construction Algorithm for IoT

Blockchain is the next generation of secure data management that creates near-immutable decentralized storage. Secure cryptography created a niche for blockchain to provide alternatives to well-known security compromises. However, design bottlenecks with traditional blockchain data structures scale poorly with increased network usage and are extremely computation-intensive. This made the technology difficult to combine with limited devices, like those in Internet of Things networks. In protocols like IOTA, replacement of blockchain’s linked-list queue processing with a lightweight dynamic ledger showed remarkable throughput performance increase. However, current stochastic algorithms for ledger construction suffer distinct trade-offs between efficiency and security. This work proposed a machine-learning approach with a multi-arm bandit that resolved these issues and was designed for auditing on limited devices. This algorithm was tested in a reinforcement-learning environment simulating the IOTA ledger’s construction with a decision tree. This study showed through regret analysis and experimentation that this approach was secure against impulse manipulation attacks while remaining energy-efficient. Although the IOTA protocol was a pioneer for lightweight distributed ledgers, it is expected that future blockchain protocols will adopt techniques similar to those presented in this work.

Security and performance evaluation of master node protocol based reputation blockchain in the bitcoin network

Bitcoin is a digital currency based on a peer-to-peer network to propagate and verify transactions. Bitcoin is gaining wider adoption than any previous crypto-currency. However, the mechanism of peers randomly choosing logical neighbours without any knowledge about the underlying physical topology can cause a delay overhead in information propagation which makes the system vulnerable to double spend attacks. Aiming at alleviating the propagation delay problem, this paper introduces a proximity-aware extension to the current Bitcoin protocol, named Master Node Based Clustering (MNBC). The ultimate purpose of the proposed protocol, which is based on how clusters are formulated and how nodes can define their membership, is to improve the information propagation delay in the Bitcoin network. In the MNBC protocol, physical internet connectivity increases as well as the number of hops between nodes decreases through assigning nodes to be responsible for maintaining clusters based on physical Internet proximity. Furthermore, a reputation-based blockchain protocol is integrated with MNBC protocol in order to securely assign a master node for every cluster. We validate our proposed methods through a set of simulation experiments and the findings show how the proposed methods run and their impact in optimising the transaction propagation delay.

Blockchain Ecosystem for Credit Transfer in Education

Data is the key to measuring educational effectiveness promptly. But data and education are trapped and siloed across centralized systems, causing information discrepancies and inaccuracies. This has caused countless delayed opportunities, academic credential disagreements, and never-ending confusion around learning potency. This lack of transparency, despite having its fair share of usefulness, has also been quite burdensome. To alleviate this issue, our team has developed a blockchain protocol that verifies professional certifications that have been earned both locally and through another well-established online educational portal. This system allows accuracy, reliability, and immutability that has never been implemented. This foundation of clear, verified data will then be used further to power blockchain-based applications. The result is that our attempt at a versatile, holistic, and decentralized view of educational performance ensures the best e-learning outcome for students and teachers alike.