Blockchain-based Cloud Research Articles

Cloud-Based Blockchain for Secure Data Sharing and Collaboration

Abstract: This study seeks to delve into the interrelation between user training and data security events in light of cloud-based blockchain technology improvement in terms of data security in collaborative contexts. A total of five firms was taken to collect data from a quantitative study, focusing more on variables that surrounded user training levels as well as data security events. This reflects that there exists a strong statistical negative correlation of frequency of security incidents and user training. Hence it has been established that the increase in the extent of training has considerably reduced vulnerabilities. Moreover, it was observed that there exists a positive relation between user participation and training. This means that to safe-guard data shared procedures, successful training activities can play an essential role. Such findings may be practically useful for firms who wish to take maximum advantage of their data security strategy.

Creation of an Anomaly Detection System for Blockchain-based Cloud Deployments that Consider Privacy and Delay.

Cloud-based deployments are increasingly vulnerable to many kinds of assaults; hence powerful anomaly detection systems are needed to prevent security breaches. While effective to some degree, current methods like RSSI, GTM, and APG have drawbacks in terms of scalability, precision, and accuracy. In order to improve the forecast accuracy of cloud assaults and optimize blockchain-based cloud installations, this study suggests a novel anomaly detection system that combines multimodal feature analysis, deep learning models, and QoS-aware sidechains. The suggested strategy considerably surpasses traditional approaches in terms of precision, accuracy, recall, and AUC performance by optimizing feature variance across various sample types and utilizing cutting-edge deep learning algorithms. Additionally, the framework shows increased efficiency in terms of throughput, energy usage, and block mining latency, makingcombining Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN), the system analyses system logs to find anomalous patterns of activity linked to various threats. The architecture guarantees the transparency and integrity of system records through the use of Blockchain technology, while Deep Learning models offer accurate and quick anomaly detection. The advantages of both Deep Learning and Blockchain technology support the choice to merge them. Blockchain technology ensures the accuracy of anomaly detection and prevents tampering with system records by providing a distributed, immutable ledger. On the other hand, deep learning models produce high precision, accuracy, recall, and AUC measures because of their remarkable pattern recognition skills and ability to adjust to shifting attack strategies. Experimental data analyses show the effectiveness of the suggested framework.

Investigating the potential of blockchain technology for geospatial data sharing: Opportunities, challenges, and solutions

Blockchain technology holds transformative potential for geospatial data sharing by offering enhanced security, transparency, and decentralization. This paper explores the integration of blockchain into managing geospatial data, focusing on its capabilities to revolutionize data storage, identification, property rights confirmation, and traceability. Through a comprehensive review of current blockchain applications and a detailed analysis of scalability, privacy, security, and cost concerns, this study identifies key challenges hindering blockchain adoption in geospatial data workflows. To address these issues, the research proposes solutions such as off-chain scaling, advanced encryption techniques, and cloud-based blockchain infrastructures. The study emphasizes the importance of aligning blockchain applications with existing legal and regulatory frameworks, including GDPR and other data protection laws. While blockchain presents significant opportunities for improving geospatial data management, this study concludes that successful implementation requires overcoming technical and regulatory hurdles. Future research should focus on developing standardized protocols and exploring innovative use cases to maximize the benefits of blockchain in geospatial contexts.

Cloud in Blockchain Technologies

Cloud computing and blockchain technology have become essential ideas in the field of IT, providing new ways to handle data. Cloud computing offers internet-based access to computing resources like servers and storage, while blockchain guarantees the accountability and immutability of data transactions with its distributed ledger system. Combining these technologies can enhance organizations' capabilities in data security and management. Businesses can utilize scalable infrastructure on cloud platforms by implementing blockchain technology, eliminating the need for large investments in physical resources. This integration improves the ability to access blockchain networks, making interactions easier across different locations and devices. Additionally, it enhances data security and privacy measures by enabling encrypted connections and strong authentication methods in cloud-based blockchain systems. Yet, obstacles remain in guaranteeing the authenticity and protection of information kept in multi-cloud settings, requiring effective authentication measures. To tackle these difficulties, this article presents a method for verifying data integrity in multi-cloud storage using blockchain technology, utilizing the decentralized aspect of blockchain to improve transparency and security. The plan automates verification procedures through smart contracts and cryptographic hashing, allowing for integrity checks at both a general and specific level across multiple Cloud Service Providers (CSPs). The proposed scheme has its effectiveness and reliability validated through theoretical analysis and experimental results, highlighting its potential to improve the security and efficiency of multi-cloud storage systems. INDEX TERMS: Cloud Computing, Blockchain Technology, Data Integrity Verification, Multi-Cloud Storage, Smart Contracts, Cryptographic Hashing, Security, Transparency.

A Blockchain-Based Cloud File Storage System Using Fuzzy-Based Hybrid-Flash Butterfly Optimization Approach for Storage Weight Reduction

A Blockchain-Based Cloud File Storage System Using Fuzzy-Based Hybrid-Flash Butterfly Optimization Approach for Storage Weight Reduction

Transforming Healthcare Data Management: A Blockchain-Based Cloud EHR System for Enhanced Security and Interoperability

The adoption of cloud-based electronic health record (EHR) systems and blockchain technology in healthcare is gaining attention for enhancing data security and interoperability. This research focuses on designing and implementing a blockchain-based cloud EHR system. It explores selecting suitable blockchain technology, cloud infrastructure, and data management methods to ensure patient data confidentiality, integrity, and availability. The architecture and components of the system, including the blockchain network, cloud storage layer, and user interface, are thoroughly discussed. A pilot study evaluates the system’s feasibility and performance, showcasing improved data protection, sharing, and management compared to traditional EHR systems. The potential benefits, drawbacks, and barriers to adoption of a blockchain-based cloud EHR system are examined. This research provides valuable insights and recommendations for healthcare institutions considering the implementation of such systems, addressing the challenges, and offering guidance for successful adoption.

Inherent Insights using Systematic Analytics of Developments Tools in Ethereum Blockchain Smart Contract

Abstract: Ethereum is an open-source, public, blockchain-based distributed computing platform and operating system that allows the development and execution of distributed applications without the risk of downtime, fraud, control, or intervention from a third party. Along with serving as a platform, Ethereum also offers a Turing-complete Blockchain programming language that aids in the publication of distributed applications. One of the major Ethereum projects is Microsoft's collaboration with Consensus, which provides Ethereum Blockchain as a Service (EBaaS) on Microsoft Azure to give enterprise clients and developers access to a cloud-based blockchain development environment with a single click. Only the implementation determines the size of the Ethereum blockchain. Geth's Ethereum blockchain is around 11 GB in size, compared to Parity's 6 GB. Although the total size of the Ethereum blockchain, in its entirety, may reach 60GB+. Even though the toolset you require may vary depending on the specific blockchain, the majority of tools are compatible with Ethereum, therefore here we highlighted the various enhancement tools that we use for implementing blockchain applications on the Ethereum platform.

Retracted: IOT and Blockchain-Based Cloud Model for Secure Data Transmission for Smart City

Retracted: IOT and Blockchain-Based Cloud Model for Secure Data Transmission for Smart City

Cost-Benefit Modeling of Smart Contracts Applied to the Accounting and Auditing Field

Abstract Blockchain technology is increasingly pervasive in social production and life, and its influence on the accounting and auditing industry is undeniable. The article extensively researches blockchain technology and smart contracts, and it constructs a blockchain-based cloud data auditing model. Combining it with the evolutionary game model completes the construction of the blockchain-based cloud data auditing system. The running cost of the auditing model is analyzed in terms of communication and computation overhead, smart contract cost, time cost, etc., and how it affects the strategies of auditing clients and auditors is studied from the aspects of cost and benefit, respectively. In this paper, the audit model’s average communication overhead and computation overhead are 9.86 KB and 0.82 seconds, respectively. The cost of the smart contract model is relatively low and shows a steady trend. The average query time of this paper’s auditing model is 0.78ms, and none of the validation times on the validator exceeds 5ms, while the average validation times on the blockchain and cloud servers are 11.01ms and 534.35ms, respectively. The auditing client and the auditor tend to adopt the blockchain technology strategy when the cost reduces, or the benefit increases, with a probability of adoption approaching 1 after numerous games.

Design of an Anomaly Detection Framework for Delay and Privacy-Aware Blockchain-Based Cloud Deployments

Design of an Anomaly Detection Framework for Delay and Privacy-Aware Blockchain-Based Cloud Deployments

An Integrated Cloud-based Blockchain Model for Supply Chain Management

An Integrated Cloud-based Blockchain Model for Supply Chain Management

A blockchain-based cloud forensics architecture for privacy leakage prediction with cloud

Digital forensics has intelligently evolved into cloud forensics, which protects against cybercrime. However, centralized evidence gathering and maintenance reduces the credibility of digital evidence. This article suggests a unique digital forensic architecture for the Infrastructure as a Service (IaaS) cloud combining rapidly expanding Software Defined Networking (SDN) and Blockchain technologies to address this serious issue. Blockchain helps to store the gathered evidence, which means it is shared among many peers in the proposed forensic architecture. The Secure-Ring-Verification-based Authentication (SRVA) technique is recommended to ensure security from suspicious accounts. The Harmony Search Optimization (HSO) technique helps to produce secret keys that strengthen the cloud environment. Depending on their level of sensitivity, all information is encrypted and kept on a cloud server. Sensitive Aware Deep Elliptic Curve Cryptography (SAD-ECC) method was used for encryption. In the cloud, a piece of information is saved, and the SDN manager creates the blocks and stores the history of that piece of data as metadata. Utilizing Secure Hashing Algorithm-3 (SHA-3), a Merkle Hash Tree is constructed for each block. The proposed technology uses Fuzzy-based Smart Contracts (FSCs) to enable clients to trail their data. At last, evidence analysis is made possible by creating a Logical-Graph of Evidence (LGoE) using data collected through Blockchain. The network simulator-3.26 and java (for cloud and Blockchain) environment are used for experiments. A thorough investigation shows that the suggested forensic architecture exhibits favorable response, evidence insertion, and verification times.

IOT and Blockchain-Based Cloud Model for Secure Data Transmission for Smart City

The widespread use of the Internet of Things (IoT) technology has both good and bad things about it. There must be a full and reliable security system in place for the Internet of Things so that things can work together in a safe way and intrusions cannot happen. There are now many more ways to keep the Internet of Things safe, thanks to a detecting system. As machine learning and deep learning technologies have become better, a lot of good intrusion detection systems have been made. This kind of study is covered. These two types of security are compared in this study. The current machine-based intrusion detection system is broken down into more detailed categories based on detection technology, data source, architecture, and operating method. These categories are as follows: It is talked about how IoT security will grow in the future and how to understand its intrusion detection system too. In this paper, a cloud-based blockchain security model has been presented for secure data transmission over IoT.

A Case Study of How Maersk Adopts Cloud-Based Blockchain Integrated with Machine Learning for Sustainable Practices

In the last six years, there has been a rise in research interest with regard to the applications of blockchain technology in supply chains and how these applications bring benefits to supply chain management. In a broader sense, an essential research focus that has been discussed in the literature is the way in which this emerging blockchain technology in supply chains brings sustainable benefits to a community. The rationale for incorporating cloud technology into a blockchain and integrating the blockchain with machine learning for supply chain applications is to maintain technical sustainability. While previous studies suggested and reported sustainable practices of applying blockchain technology in supply chains, the means with which these practices are brought about by the cloud-based blockchain integrated with machine learning (CBML) have not been thoroughly explored in the literature. The case study presented in this paper aims to fill this gap by exploring technically, environmentally, economically, and socially sustainable practices through the use cases of CBML for supply chain management by the international leading container shipping company Maersk. The use cases by Maersk presented in published documents were collected from the Internet and then analyzed. This document analysis was performed in two ways. The first way was a technical review of the blockchain technology used by Maersk with a consideration of technical sustainability to ensure scalability and big data analytics. The other way was to analyze the applications of the CBML by Maersk to indicate how environmental sustainability, economic sustainability, and social sustainability can be achieved. On the other hand, this paper also highlights the negative technical, environmental, economic, and social sustainability impacts caused by Maersk and discusses implications for future research directions.

A novel multi-objective service composition architecture for blockchain-based cloud manufacturing

AbstractIn recent years, many core technologies of Industry 4.0 have advanced significantly, particularly the integration of big data technology and cloud manufacturing (CMfg). The decentralization and traceability features of blockchain technology (BCT) provide an effective solution to provide trusted resource service in CMfg. Service composition is a core issue of CMfg to increase the value of digital assets. However, existing research on service composition based on BCT suffers from both the blockchain proof-of-work (PoW) mechanism and the service composition problem need to consume large computational overheads, as well as the blockchain fork problem affecting the system’s reliability, which reduces the usefulness of these schemes. To solve these problems, this paper proposes a novel multi-objective service composition architecture for blockchain-based CMfg (MOSC-BBCM). In MOSC-BBCM, first, a blockchain-chained storage structure is designed for the actual manufacturing cloud service constraint and scale dynamic changes, which can fully use the historical service information and accelerate the search for high-quality solutions. Second, to reduce the squandered computing resources in the PoW, a mining mechanism based on multi-objective service composition and optimal selection is proposed, where miners competitively solve a nondeterminate polynomial-hard problem to replace the mathematical puzzle. Finally, an incentive mechanism based on the environment selection method is proposed, which can avoid the fork problem while distributing on a labor basis. The effectiveness of the proposed MOSC-BBCM is verified in simulated numerical experiments of CMfg, which shows that the architecture provides a flexible and configurable scheme for blockchain-based CMfg with high availability.

Blockchain Based Key Exchange Mechanism for Cloud Storage

A cloud storage system is a system that saves information for an individual or company. The cloud system enables the owner of data to control and share his or her information with specific users. Because of the irrevocable consequences of inaccurate information, the integrity or interfere resistance characteristic is critical for cloud systems. Owing to its immutability and irreversibility, blockchain technology has emerged as a viable solution. Unfortunately, significant technological hurdles remain, such as limited storage, privacy concerns, irrevocable permission, poor performance, and high energy usage. The goal of this study is to address these blockchain disadvantages and offer a blockchain-based cloud storage paradigm. To ensure tamper resistance, the suggested model is designed with blockchain technology. To protect privacy, the master-key exchange method and other cryptographic approaches are used. Perfectly fine and dynamic access control, consent that may be revoked, integrity, and fraud resistance are all features of the proposed paradigm. A thorough security study demonstrates that this proposed paradigm is prove that its secure in terms of confidentiality and fraud resistance. The performance study reveals that this research methodology outperforms the existing technique in the literature in terms of overall performance.

Proposed Model for Secured Data Storage in Decentralized Cloud by Blockchain Ethereum

Since cloud computing is an essential component of any modern company (usually accounting for a considerable share of information technology (IT) infrastructure investment), consumers rely on cloud services. Data privacy and security are worries when data remains in third-party storage. Existing document version control systems are centralized and at risk from data loss, as seen by higher time utilization and incorrect document update procedures that allow modifications to a document without the awareness of other network operators. Underutilized peer resources might be leveraged to construct storage. According to this argument, an elevated level of data security may be obtained by encrypting the data and dispersing it among numerous nodes. In this study, we attempted to review the security of cloud systems when using the blockchain Ethereum, and cloud computing was briefly discussed with its advantages and disadvantages. The idea of a decentralized cloud was briefly demonstrated with blockchain technology. Furthermore, previous papers were reviewed and presented in tabular form. This dictated that there are still research gaps in the field of blockchain-based cloud computing systems. This study proposed a model for secured data storage over a decentralized cloud by blockchain Ethereum.

SPM: A Novel Hierarchical Model for Evaluating the Effectiveness of Combined ACDs in a Blockchain-Based Cloud Environment

Cloud computing provides blockchain a flexible and cost-effective service by on-demand resource sharing, which also introduces additional security risks. Adaptive Cyber Defense (ACD) provides a solution that continuously changes the attack surface according to the cloud environments. The dynamic characteristics of ACDs give defenders a tactical advantage against threats. However, when assessing the effectiveness of ACDs, the structure of traditional security evaluation methods becomes unstable, especially when combining multiple ACD techniques. Therefore, there is still a lack of standard methods to quantitatively evaluate the effectiveness of ACDs. In this paper, we conducted a thorough evaluation with a hierarchical model named SPM. The proposed model is made up of three layers integrating Stochastic Reward net (SRN), Poisson process, and Martingale theory incorporated in the Markov chain. SPM provides two main advantages: (1) it allows explicit quantification of the security with a straightforward computation; (2) it helps obtain the effectiveness metrics of interest. Moreover, the hierarchical architecture of SPM allows each layer to be used independently to evaluate the effectiveness of each adopted ACD method. The simulation results show that SPM is efficient in evaluating various ACDs and the synergy effect of their combination, which thus helps improve the system configuration accordingly.

Block the Chain: Software Weapons of Fighting Against COVID-19

This article proposes an architecture for vaccination information validation and tracking with a fog and cloud-based blockchain system, providing a privacy-aware and scalable approach for interoperable and effective data management. It evaluates the scalability of the underlying blockchain system by means of simulation.

Blockchain-Based Cloud Manufacturing SCM System for Collaborative Enterprise Manufacturing: A Case Study of Transport Manufacturing

Sheet metal part manufacture is a precursor to various upstream assembly processes, including the manufacturing of mechanical and body parts of railcars, automobiles, ships, etc., in the transport manufacturing sector. The (re)manufacturing of railcars comprises a multi-tier manufacturing supply chain, mainly supported by local small and medium enterprises (SMEs), where siloed information leads to information disintegration between supplier and manufacturer. Technology spillovers in information technology (IT) and operational technology (OT) are disrupting traditional supply chains, leading to a sustainable digital economy, driven by new innovations and business models in manufacturing. This paper presents application of industrial DevOps by merging industry 4.0 technologies for collaborative and sustainable supply chains. A blockchain-based information system (IS) and a cloud manufacturing (CM) process system were integrated, for a supply chain management (SCM) system for the railcar manufacturer. A systems thinking methodology was used to identify the multi-hierarchical system, and a domain-driven design approach (DDD) was applied to develop the event-driven microservice architecture (MSA). The result is a blockchain-based cloud manufacturing as a service (BCMaaS) SCM system for outsourcing part production for boxed sheet metal parts. In conclusion, the BCMaaS system performs part provenance, traceability, and analytics in real time for improved quality control, inventory management, and audit reliability.