Jameel Almalki, Saeed M. Alshahrani, Nayyar Ahmed Khan
Recently, the use of the Internet of Medical Things (IoMT) has gained popularity across various sections of the health sector. The historical security risks of IoMT devices themselves and the data flowing from them are major concerns. Deploying many devices, sensors, services, and networks that connect the IoMT systems is gaining popularity. This study focuses on identifying the use of blockchain in innovative healthcare units empowered by federated learning. A collective use of blockchain with intrusion detection management (IDM) is beneficial to detect and prevent malicious activity across the storage nodes. Data accumulated at a centralized storage node is analyzed with the help of machine learning algorithms to diagnose disease and allow appropriate medication to be prescribed by a medical healthcare professional. The model proposed in this study focuses on the effective use of such models for healthcare monitoring. The amalgamation of federated learning and the proposed model makes it possible to reach 93.89 percent accuracy for disease analysis and addiction. Further, intrusion detection ensures a success rate of 97.13 percent in this study.
Electronic Health Records (EHRs) have become an increasingly significant source of information for healthcare professionals and researchers. Two technical challenges are addressed: motivating federated learning members to contribute their time and effort, and ensuring accurate aggregation of the global model by the centralized federated learning server. To overcome these issues and establish a decentralized solution, the integration of blockchain and federated learning proves effective, offering enhanced security and privacy for smart healthcare. The proposed approach includes a gamified element to incentivize and recognize contributions from federated learning members. This research work offers a solution involving resource management within the Internet of Medical Things (IoMT) using a newly proposed trust decentralized loop federated learning consensus blockchain. The obtained raw data is pre-processed by using handling missing values and adaptive min-max normalization. The appropriate features are selected with the aid of hybrid weighted-leader exponential distribution optimization algorithm. Because, data with multiple features exhibits varying levels of variation across each feature. The selected features are then forwarded to the training phase through the proposed pyramid squeeze attention generative adversarial networks to classify the EHR as positive and negative. The proposed classification model demonstrates high flexibility and scalability, making it applicable to a wide range of network architectures for various computer vision tasks. The introduced model provides better outcomes in terms of 98.5% in the training accuracy and 99% in the validation accuracy over Medical Information Mart for Intensive Care III (MIMIC-III) dataset, which is more efficient than the other traditional methods.
Nabil Tazi Chibi, Omar Ait Oualhaj, Wassim Fassi Fihri, Hassan El Ghazi
Smart Grids (SGs) rely on advanced technologies, generating significant data traffic across the network, which plays a crucial role in various tasks such as electricity consumption billing, actuator activation, resource optimization, and network monitoring. This paper presents a new approach that integrates Machine Learning (ML), Blockchain Technology (BT), and Markov Decision Process (MDP) to improve the security of SG networks while ensuring accurate storage of events reported by various network devices through BT. The enhanced version of the Proof of Work (PoW) consensus mechanism ensures data integrity by preventing tampering and establishing the reliability of known and unknown attack detection. The proposed versions of PoW, namely GPoW 1.0 and GPoW 2.0, aim to make the consensus process more environmentally friendly.
In a smart city environment, various intelligent devices, applications, and digital networks collaborate to provide technological solutions for the public good. The exponential data generated from intelligent interactions among stakeholders within the smart city ecosystem raises concerns regarding security and privacy. Maintaining data openness while safeguarding it against social engineering attacks, network breaches, and data masking threats is paramount to achieving resilience. Blockchain technology has demonstrated great promise in addressing these challenges due to its decentralized, consistent, and tamper-proof nature. Our paper explores how blockchain can address the challenges of integrity, security, and privacy in smart city operations. Despite significant research efforts, the subject remains in need of a comprehensive survey. Consequently, we conduct a study on state-of-the-art blockchain-based reputation and trust management methods within the three fundamental components of a smart city: energy, healthcare, and transportation. The trust and reputation mechanisms are analyzed to identify their strengths and limitations. The investigation reveals that the existing trust schemes are resource-constrained and encounter scalability limitations, high energy consumption, and incompatibility with existing systems.
Supply chain as an industry has gone through four-fold changes in the last century. Born as a bare-bones structure in 1.0 it grew to incorporate some form of record preservation in 2.0 and then integrated communication between two entities in 3.0. Supply chain 4.0, the current one, has total global integration of multiple entities with the records digitised. But increasing entities and pipelines, means increasing complexities, overhead and soft spots. In this paper, a systematic literature review is done with the objective of analysing existing Supply Chain 4.0. The focus of the paper is the usage of blockchain technology in the electronic industry to provide a decentralised architecture. Several papers were compared on the basis of different schemas like the type of blockchain network used, platform deployed on, security of frameworks, representation of unique identity, testing authenticity, working implementation, cost of implementation, etc. The pros and cons of various privacy and security methodologies are also explored and discussed. The paper also discusses the open issues and challenges in the same area of interest. Finally, the paper outlines the future scope to be delved into as a part of the future research.
In terms of digital transformation, organizations today are aware of the critical role that data and information play in their expansion and development in light of the Internet of Things. To increase network performance and stability, many applications are moving from cloud computing to edge computing (EC). However, in order to satisfy customers, applications like intelligent transportation systems, smart grids, smart cities, and healthcare call for even more effective services. This survey addresses extensive research on two aspects: firstly, we present the advancements of two application domains namely maritime areas and aerial systems in terms of integration with EC architecture. Secondly, we cover the most recent technologies, artificial intelligence (AI) and blockchain, combined into the EC paradigm by discussing several experiments conducted in various fields to demonstrate the value of utilizing them in the edge computing architecture. We analyze the results of eleven experiments in each technology from 2015 to 2023.
This article addresses the dynamic landscape of smart supply chain management, characterized by the integration of cutting-edge technologies. It proposes an IoT-Blockchain system for monitoring equipment status in a smart supply chain environment. The system utilizes IoT sensors to collect temperature and humidity data from the equipment. This collected data is then processed and stored in the cloud using the InfluxDB database. To further enhance security and transparency in the monitoring process, the system incorporates blockchain technology. This ensures the tamper-proof nature of collected data through the deployment of smart contracts. The monitoring platform developed on Grafana provides users with an intuitive dashboard for accessing real-time information about the equipment’s status. The proposed system offers a comprehensive monitoring solution for sensitive supply chain operations, allowing stakeholders to track the equipment’s journey along the supply chain and monitor its status in real-time. This system has the potential to revolutionize supply chain monitoring, providing an efficient and secure way to optimize equipment performance and improve overall supply chain efficiency.
Ahmad Y. A. Bani Ahmad, Neha Verma, Nadia Sarhan, Emad Mahrous Awwad · 6 authors
The process of controlling the flow of products and services from a company by encompassing each stage involved in transforming raw materials and parts into finished items, also delivering them to the final consumer is known as Supply Chain Management (SCM). The development of numerous smart city applications including smart grids, smart homes, smart supply chains, and smart healthcare has drawn attention to the Internet of Things (IoT). Nowadays, researchers are considering the smart healthcare system’s role as a Public Emergency Service (PES) to treat patients promptly. A distributed smart fire brigade system receives little attention like PES to save lives and property from catastrophic fire damage. The conventional PES methods are created using a centralized method that needs a lot of processing power and doesn’t offer timely services. The traditional systems developed for managing the supply chain have drawbacks like single-point failure issues, data integrity, transparency, and lack of trust. To alleviate the existing issues, in this paper, a Blockchain and IoT Enable Secure and Transparent Supply Chain Management framework is utilized for PES in the smart city environment. Further, two edge computing servers, like a service controller and an IoT controller are adapted. The local storage is handled by the service and IoT controller. Thus, it enhances the data processing speed of PES requests and PES fulfillment. The service controller utilizes the Optimal Queue Model to manage the PES requests based on the minimum service queue length. The efficiency of the network is improved by fine-tuning the parameters from the Queue model with the aid of a Revised Fitness-based Political Optimizer (RF-PO). The multi-objective constraints like queue length, utilization, actual arrival time, expected arrival time, and end-to-end delay are utilized for the efficient supply chain system. These stimulated results show the feasibility and effectiveness of the supply chain framework.
The healthcare industry is exponentially growing its dependence on smart wearables and remote devices for efficient treatment and diagnosis. These smart devices benefit the healthcare industry, but they raise serious security and integrity concerns while exchanging healthcare data. These devices are primarily meant for data dissemination; hence, they are equipped with weak security protocols that are susceptible to attacks like distributed denial-of-service (DDoS), data injection, and man-in-the-middle (MiTM) attacks. To circumvent the aforementioned security challenges, this article proposed a secure and intelligent data exchange framework for smart healthcare systems. For that, we amalgamate artificial intelligence (AI) and blockchain technology to strengthen the security of data dissemination between smart medical devices. Further, we adopted fuzzy logic that extracts the essential features from the healthcare security dataset to enhance the detection rate of AI models. We used different AI algorithms such as logistic regression (LR), random forest (RF), decision trees (DT), stochastic gradient descent (SGD), and Gaussian naive Bayes (GNB) to classify healthcare data into malicious and non-malicious. The predicted data can still be maneuvered by adversaries that introduce subtle changes that skew the results to their advantage. Therefore, we employed blockchain technology that stores non-malicious healthcare data (predicted data) from data tampering attacks. The developed smart contract validates the non-malicious healthcare data and only allows them to be securely stored inside the interplanetary file system (IPFS)-based public blockchain. The proposed framework is evaluated by considering various evaluation metrics like recall, precision, accuracy, F1 score, area under the curve (AUC) score, and blockchain scalability.
The integration of blockchain technology in the Industrial Internet of Things (IIoT) for sustainable supply chain management in the context of Industry 4.0 offers several potential benefits. A public and auditable record of the environmental impact of each supply chain stage can be made using blockchain technology. A more streamlined and effective supply chain is made possible by blockchain's decentralized structure. Delays, mistakes, and the need for middlemen are decreased by real-time access to a shared ledger. IIoT devices like sensors and RFID tags can provide real-time data on the location, condition, and environmental parameters of goods. Blockchain can then be used to record and incentivize sustainable practices, such as reducing energy consumption or minimizing waste. The integration of blockchain with IIoT can develop the supply chain management for enabling real-time tracking of goods, optimizing inventory management, and ensuring compliance with sustainability standards. The paper provides a comprehensive overview of the key challenges facing traditional supply chains and how the combined use of Blockchains and IIoT technologies. The review also evaluates the environmental, social, and economic implications of adopting Blockchain-enabled IIoT solutions in supply chain operations. Furthermore, the review assesses the current state of research and development, identifying gaps in existing literature and proposing avenues for future exploration. As a results, by highlighting the synergies between these technologies, it seeks to inspire further innovation and adoption, ultimately fostering a more resilient, transparent, and environmentally conscious industrial ecosystem.
Mohammed L. Khalaf, Israa M. Hayder, Taief Alaa Al-Amiedy, Hussain A. Younis · 8 authors
The Internet of Thing (IoT) is an innovative technology designed to integrate tangible artefacts with the digital era, resulting in the development of new digital services to improve and ease our lives. Despite the advantages of IoT technology in a variety of industries. The existing centralised IoT architecture has a number of issues, including single point of failure, stability, safety, accountability, and data integrity. Such issues are impeding the growth of IoT in the future. To address the a forementioned issues, distributed ledger technologies are regarded as promising and feasible solutions. The blockchain is one of the most prevalent and widely used forms of distributed ledger technology. The combination of IoT and blockchain technology has numerous advantages. The combination of IoT and blockchain technologies will provide numerous benefits. This article demonstrates the fundamentals of IoT and blockchain technology in order to provide a thorough analysis of the architecture of the combination of IoT and blockchain technology. In addition, this study provided a comprehensive description of the combination of the blockchain with the IoT platform from a variety of perspectives in order to address IoT's shortcoming. The service function of blockchain in IoT applications is demonstrated. Finally, the prospective applications of blockchain technology to IoT fields are discussed.
Latifa Albshaier, Alanoud Budokhi, Ahmed Aljughaiman
The integration of the Internet of Things (IoT) and cloud computing, which play essential roles in our everyday routines, is expected to emerge as a fundamental element of the forthcoming internet, realizing increased usage and acceptance. This fusion is anticipated to revolutionize various applications, offering The integration of IoT and cloud may pose challenges. Cloud computing’s capacity to distribute resources and data across diverse locations, facilitating access from different industrial settings, has significantly enhanced IoT functionality. However, rapid migration to the cloud has raised security concerns, as conventional security measures for computers are not always applied effectively to cloud-based systems. Overcoming these obstacles can be achieved by integrating cloud and IoT technologies, as the vast resources available on the cloud can greatly benefit IoT, helping the cloud transcend current limitations related to physical objects in a more dynamic, distributed manner. Several discoveries from the research were made by exploring the facilitation of a smooth shift of IoT initiatives to the cloud by studying IoT and cloud computing, investigating various cloud-related challenges and resolutions derived from recent scholarly works, and analyzing the most recent advancements in attacks targeting cloud-based IoT systems. Identifying gaps in the research on IoT-based cloud infrastructure and addressing cybersecurity in cloud computing is important for future research directions, necessitating a review of the technological challenges mentioned in the literature. As such, this research explores how blockchain technology effectively addresses security concerns within this combination, emphasizing its capacity to improve data integrity and privacy and to ensure secure transactions. The exploration delves into the multifaceted implications and potential applications of blockchain, elucidating its role in reinforcing the overall security of these interconnected systems.
Thanks to developments in artificial intelligence (AI), cloud computing, cyber security, and other game-changing technologies, the information technology (IT) landscape is changing quickly. With an emphasis on artificial intelligence (AI), multi-cloud strategies, cybersecurity resilience, quantum computing, the Internet of Things (IoT), DevOps, blockchain, and Environmental, Social, and Governance (ESG) activities, this article offers a thorough examination of current IT developments influencing companies in 2024. Business operations are being completely transformed by artificial intelligence (AI) and machine learning (ML), which improve automation and personalization while bringing up moral questions of justice and transparency. Organizations are using AI-driven threat detection and zero-trust architecture more frequently as cyber threats increase in order to strengthen cybersecurity resilience. As cloud computing advances toward multi-cloud and hybrid models, businesses can benefit from increased scalability, flexibility, and reduced vendor lock-in. Though they are still in the experimental stage, emerging technologies like quantum computing offer promising improvements in computational capacity and the ability to solve complicated problems. Furthermore, the integration of 5G with IoT devices is improving real-time data processing in a number of industries, including logistics and healthcare. Initially restricted to cryptocurrencies, blockchain technology is increasingly being used in secure data management and decentralized finance (DeFi) applications. Lastly, companies are embracing green IT solutions and sustainable practices as part of the growing popularity of ESG activities. This paper clarifies these important IT trends through a detailed literature study, industry research, and expert insights, offering a thorough picture of how companies should strategically navigate the continuing digital revolution.
This paper provides a comprehensive approach to Bitcoin price, returns, direction and volatility forecasting. It compares ARIMA and GARCH models to neural network (NN) autoregression and Jordan NN in their forecasting performances, using internal and external factors. Robustness of the results is verified across bearish, bullish and stable market conditions. The results are not unambiguous considering price, returns or volatility forecasting, when compared using different performance measures or through different periods. Return and volatility forecasting yields to stable results no matter the model or period observed. NNs in general emerge as optimal for return and direction forecasting, ARIMAX and NNARX for price forecasting, while for volatility forecasting all models yield comparable results. Price forecasting yields the best prediction accuracies, while JNNX performed poorly. However, the inclusion of other machine learning methods and/or different variables as well as recent crisis emerged from war circumstances can be seen as limiting factors.
Abstract This paper addresses the critical challenges of scalability, interoperability, and user adoption in IoT-blockchain integration for urban energy systems. Existing frameworks often rely on energy-intensive consensus mechanisms (e.g., Proof of Work) or centralized architectures, limiting their applicability to large-scale, sustainable smart cities. To bridge these gaps, we propose a novel IoT blockchain framework that uniquely combines hybrid consensus mechanisms (Proof of Stake + Practical Byzantine Fault Tolerance), K-means clustering for demand-response optimization, and lightweight IoT protocols (MQTT/CoAP) to ensure energy efficiency, scalability, and user-centric design. Our approach leverages real-world datasets (UK-DALE, PECAN Street) to train predictive models, cluster energy consumption patterns, and automate decentralized energy trading via blockchain smart contracts. Simulations demonstrate a 15% reduction in energy costs for high-consumption clusters, 80% lower energy use (50 kWh/tx vs. 500 kWh/tx for PoW), and near-linear scalability for 500+ IoT devices. A secure dashboard with AI-driven recommendations (e.g., peak-load alerts) further enhances stakeholder engagement. By addressing technical limitations of previous works, such as computational bottlenecks, lack of user interfaces, and poor interoperability, our framework provides actionable insights for policymakers to advance sustainable urban energy systems. These results position the proposed architecture as a transformative solution for scalable, eco-friendly smart cities.
Likhitha Amasala, Mahesh Datta Sai Ponnuru, P. Srideviponmalar
At present, technological systems lack a secure and transparent method for tracking goods and preventing theft in e-commerce, leading to trust issues and data vulnerabilities. There is a pressing need for a comprehensive solution that integrates Ethereum blockchain, IPFS, and advanced cryptographic techniques to address these challenges and enhance the security and transparency of transactions. This research paper presents a robust system that harnesses the Ethereum blockchain, IPFS (Interplanetary File System), and advanced cryptographic algorithms to create a secure, decentralized approach for tracking goods and preventing theft incidents. Unique identifiers and related information will be sent to the mail of the customer and same should entered by the customer for successful transaction. By assigning unique identifiers to purchased products and employing cryptographic techniques to encrypt sensitive data, our system ensures both user privacy and the creation of an immutable transaction ledger. Users can efficiently manage their purchased goods, block stolen items, and communicate with sellers through an intuitive interface. Additionally, the system provides sellers with a comprehensive transaction history, enhancing accountability and transparency within the supply chain. Through this research, we demonstrate the effectiveness of our blockchain based anti-theft measures, underpinned by Ethereum, IPFS, and cutting-edge cryptographic algorithms, in fostering secure, trustless transactions. This work highlights the transformative potential of blockchain technology and decentralized protocols in revolutionizing security and transparency across diverse sectors.
In the current digital landscape, almost everyone is on social media or various social media platforms. People use social media for a plethora of purposes, which include staying connected with friends and family, accessing information and updates about ongoing events, entertainment, networking with professionals, expressing themselves to a wide range of users, promoting businesses, joining online communities and engaging in various activities which has led to an increase in the consumption and usage of online social networks (OSN). One of the reasons for such a growth is their features such as ubiquitous access, on-demand service, friendship networks, user engagement strategies like recommendation engines, etc. However, there are various limitations to the current approach, such as the centralization of control, lack of data ownership, poor access control, fake news, bot accounts, censorship, digital rights management issues, etc. To address these limitations, a paradigm shift is necessary. This paper aims to develop a social media application where every post can be converted to a Non-Fungible Token (NFT) and be sold to earn money. Interplanetary File System (IPFS) is used as the decentralized storage. Algorithms for all the functionalities of the applications are given along with an algorithm for a reputation score for every user and their posts in social media are also proposed.
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Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
The sixth generation (6G) wireless cellular networks are anticipated to include the most recent advancements in network infrastructure and new technological discoveries.In addition to exploring more spectrum at high-frequency bands, it will bring together cutting-edge technical trends like blockchain, artificial intelligence (AI), and connected robotics.6G and Next-Generation Internet: Under Blockchain Web3 Economy by Abdeljalil Beniiche explores the human-centeredness of blockchain and Web3 economy for the 6G era.
Blockchain technology has emerged as a transformative solution to enhancing data security, privacy, and transparency, especially in cloud computing environments. As cloud computing continues to grow in popularity for its flexibility, scalability, and cost-effectiveness, its reliance on centralized data management systems creates significant security vulnerabilities. Blockchain, a decentralized and distributed ledger technology, offers an innovative approach to mitigate these concerns by providing immutable and transparent data transactions. This paper examines the integration of blockchain technology with cloud computing, exploring its role in revolutionizing data security, privacy, and transparency. Through case studies and research findings, the paper evaluates the potential benefits and challenges of adopting blockchain for securing cloud infrastructures, improving service integrity, and fostering trust in cloud environments.
Ibegbulam C.M, O.J Aigbovbiosa, J. A. Olowonubi, S. A. Fatounde
The research explores the relationship between Artificial Intelligence (AI) and electrification in Africa, focusing on the challenges and emerging trends. The electrification deficit in Africa poses a significant impediment to economic development and social progress. This paper explores the pivotal role that Artificial Intelligence (AI) plays in addressing the challenges associated with electrification initiatives across the African continent. With its capacity for innovation and optimization, AI emerges as a transformative force capable of revolutionizing the planning, deployment, and management of electrification projects in a region characterized by diverse geographical landscapes and economic constraints. The paper investigates the potential of AI in addressing financial barriers associated with electrification projects. By facilitating innovative financing models, reducing operational costs, and attracting investments, AI contributes to creating sustainable and economically viable electrification solutions. The focus extends to decentralized energy systems and microgrids, exploring how AI can empower remote and underserved communities with reliable access to electricity. The socio-economic impact of AI-driven electrification initiatives is also scrutinized, emphasizing the potential for job creation, economic growth, and improved living standards. The paper discusses the importance of capacity building and local empowerment to ensure that AI technologies are effectively integrated into electrification projects while fostering inclusive and sustainable development. It highlights the role of AI in revolutionizing electrification, predicting electricity consumption and enabling decentralized solutions. AI-driven electrification has shown economic and social benefits, including enhanced productivity, improved quality of life, and increased market access. However, it also raises ethical concerns and privacy implications. The research emphasizes the need for proactive mitigation strategies and collaborations across sectors to drive regulatory frameworks, technological innovations, and global impact. The research envisions a future where AI plays a central role in fostering inclusive growth, connecting communities, and illuminating a digitally transformed and sustainable continent. Keywords: Artificial Intelligence, Electrification, Africa, Electricity, Energy
A. Anitha, M. Priya, M. K. Nallakaruppan, Deepa Natesan · 6 authors
INTRODUCTION: Supply chain management is the management process of the flow of goods, and services related to financial functionalities, procurement of raw materials delivery to the final destination. OBJECTIVES: Since the traditional supply chain process lacks data visibility, trustworthiness, and distributed ledger, the need for the blockchain mechanism to ensure the time-stamped transactions to provide a secured supply chain process has been introduced and integrated. METHODS: The distributed nature of the blockchain helps in organizing the supply chain and engaging the customers with real, verifiable, and immutable data. Blockchain technology enables these transactions to be tracked in a very secure and transparent manner. In this paper, we, therefore, propose a framework that utilizes blockchain and key Escrow encryption systems to optimize the security of supply chains to improve services for global business survivability. RESULTS: The comparative analysis with the existing benchmarking techniques with respect to the key size, key generation time, and key distribution time was carried out with the proposed model and found that proposed work provides better results. CONCLUSION: This proposed system can track the authenticity of the product and details about the manufacturer of that particular product. Thus, the paper concludes the proposed work enhances data’s integrity, traceability, and availability and single-point failure can be resolved or reduced using blockchain mechanism.