With the advent of the Internet, the gaming industry has grown tremendously in business, which also raises concerns for cheating and unfair gameplay. In this paper, we propose a novel approach (GiNA) using Blockchain technology to address a few problems with online Peer-to-Peer (P2P) games. GiNA uses two different data packet transfer schemes to ensure the security and authenticity of the data packet sent and received by game clients. More sensitive data uses a Smart contract-based ON-CHAIN data packet transfer solution and less sensitive data uses an OFF-CHAIN data packet transfer solution with end-to-end encryption for data security. A marketplace where peers can buy and sell purchasable assets with the help of Gicoins. Gicoins is a stable token with compliance with the ERC 20 token of Etheruem Blockchain. Later, a low cost and low bandwidth utilization data storage solution is proposed for storing data in a decentralized and distributed manner. Results show that the performance of the proposed approach GiNA is better in comparison to the traditional approaches with parameters such as latency, scalability, packet loss percentage, Blockchain (BC) performance, and data storage comparison.

Financial institutions have made lives easier for a lot of individuals and organizations that would earlier use to face capital shortage now and then. Therefore, it becomes necessary to make the financial systems more reliable, secure, time-conserving, and cost-effective. Although several approaches have already been proposed, all of these tend to fail on at least one of the key features, i.e., trust. Motivated by this, in this paper, we propose DeLend, an Ethereum blockchain-based peer-to-peer (P2P) lending system. In DeLend, the problems of security, trust, and reliability have been solved with the help of Ethereum-based smart contracts (SCs). To make the system middlemen-free and much more cost-effective, we use the interplanetary file system (IPFS) protocol as a data storage. Through extensive simulation, we show that DeLend requires less bandwidth, which makes it a suitable enabling technology for the next generation of cellular networks, i.e. 6G. Finally, DeLend’s performance evaluation demonstrates its efficacy compared to traditional lending schemes.

The rapid growth and advancement of technology in industries provide a better quality of services to the end-user in the industrial Internet of Things (IIoT). The digital twin (DT) is an innovative technology recently developed in Industry 4.0 to provide a virtual representation of physical components, products, or equipment such as computer numerical control (CNC) machines. It can be used to run simulations before manufacturing. However, traditional DT platforms lack data privacy, traceability, immutability, authentication of stakeholders. Moreover, manual prediction of the wearing of the tool condition of the CNC machine is challenging. Motivated from these gaps, in this paper, we propose a six-layered architecture for DT of CNC, which predicts CNC tool wear detection using a novel ensemble technique based soft voted prediction model consisting of XGBoost, random forest, and AdaBoost models. The proposed architecture also incorporates the public Ethereum blockchain (BC) to maintain the aforementioned issues of authentication, traceability, and transparency through constraints and automation programmed into the smart contracts (SC) developed. We evaluate the proposed scheme’s performance through simulation and compare it with other traditional approaches concerning several performance parameters (accuracy, F1-score, precision, and recall). The result shows that the proposed approach outperforms the traditional approaches on these same performance parameters such as accuracy, F1-score, precision, and recall.

The COVID-19 pandemic has adversely affected the lives of millions of people worldwide. With an alarming increase in COVID-19 cases, it is important to detect and diagnose COVID-19 in its early stages to prevent its spread. To diagnose remote patients, the Internet can be useful for accessing data of that patient. But, the Internet has also had issues related to data security, reliability, and privacy. Motivated by these challenges, in this paper, we propose a Blockchain (BC) based COVID-19 detection scheme (BCovX) for fast and reliable diagnosis of COVID-19 using chest X-Ray (CXR) images. For fast and accurate detection of COVID-19 using CXR, BCovX consists of a Convolutional Neural Network (CNN) model, using which a patient can be diagnosed for COVID-19 remotely. CNNs have performed successfully in medical imaging classification. BCovX provides reliable and secure data access and exchange using BC and smart contracts (SC). To solve issues related to data storage and its associated cost, the InterPlanetary File System (IPFS) protocol is used to store medical data. We also present a real-time SC developed in Solidity to govern the transaction between the patient and the doctor. The SC has been compiled and deployed on Remix Integrated Development Environment (IDE). Finally, we have evaluated the performance of BCovX with traditional schemes in terms of storage cost, bandwidth requirements, and accuracy of the CNN model.

The next-generation energy system, i.e., Smart Grid (SG), empowers the real-time transfer of information using advanced metering infrastructure (AMI) and smart meter (SM) between end-consumers and grid. It accelerates various services such as automatic meter reading, time-of-use (TOU) pricing, demand-response management, and many more. Though it has growing security and privacy concerns and the detection of malicious activity is a critical security task that sacrifices the overall Quality-of-Service (QoS) of SG and Quality-of-Experience (QoE) for customers. To address the aforementioned issues, we propose a data analytics Scheme ArMor for malicious activity detection on the blockchain (BC)-based SG system. The ArMor detects data integrity issues in real-time like false data injection attack and SM failure. Here, we proposed a unique ARIMA-based malicious activity detection model and classified the customer. Then, we proposed a Smart Contract (SC)-based incentive mechanism for utility providers handling the malicious activity at their end. It prevents the entry of malicious data into the SG system as transactional data once stored in BC, it is secured using SC. The obtained results are compared against parameters like prediction accuracy, latency, and data storage cost compared to the state-of-the-art approaches to designate the efficacy of the proposed scheme.

Blockchain technology has emerged to provide immense security solutions and create trust between the stakeholders. In a multi-application scenario, fair resource allocation is complex and challenging. Various Resource Allocation Schemes (RAS) have been proposed by the researchers across the globe, but these solutions are not sufficient to handle the security, trust, latency, and bandwidth issues in the network, which introduces vulnerabilities in the system. Motivated from the aforementioned issues, this paper proposes Block-RAS, a blockchain-based RAS to manage the demand-supply of resources between the users and resource providing companies (RPC) in a secured and trusted environment. Block-RAS provides a highly reliable, low-latency, and bandwidth optimum communication between users and RPC with embedded 6G network infrastructure. In Block-RAS, the security, trust, and transparency are achieved using ethereum blockchain, whereas the cost-effective and optimum bandwidth utilization is achieved using the Interplanetary File System (IPFS). Finally, the performance evaluation of Block-RAS is done by a comparative analysis of the proposed approach with traditional approaches that are dependent on centralized 5G based schemes where the Block-RAS outperforms in terms of delay, packet-loss, blockchain block-size, scalability, and network bandwidth utilization.