Securing medical records based on inter-planetary file system and blockchain

In general, health records include important information like the patient’s history, findings of examinations and assessments, diagnosis reports, documentation of consent, and treatment plans. Sharing this information has grown to be a challenge concerning data security, as it could result in compromising patient privacy. Therefore, the patient's information should not be misused or tampered with. In this paper, a full process of storing and retrieving medical records is proposed using a decentralized system through the integration of two emerging technologies: Blockchain and Inter-Planetary File System (IPFS). The system provides solutions for the major security concerns associated with medical files, including authentication and authorization, database breaches, data integrity of local and cloud storage, and data availability. The obtained results indicate a high level of safety by adding security layers such as confidentiality, authentication, authorization and access control, based on different factors. All these aspects contribute to reaching the aim of the proposed system, which is storing and retrieving medical records in a decentralized and safe manner

Continued implementation and testing of a Neighborhood Office Center (NOC) and integration of the NOC with an administrative correspondence management information system

The concept of decentralized (remote) neighborhood offices, linked together through a self-sustaining communications network for exchanging voice messages, video images, and digital data was quantitatively evaluated. Hardware and procedures for the integrated multifunctional system were developed. The configuration of the neighborhood office center (NOC) is explained, its production statistics given, and an experiment for NOC network integration via satellite is described. The hardware selected for the integration NOC/management information system is discussed, and the NASA teleconferencing network is evaluated

Blockchain-Enabled Federated Learning Approach for Vehicular Networks

Data from interconnected vehicles may contain sensitive information such as location, driving behavior, personal identifiers, etc. Without adequate safeguards, sharing this data jeopardizes data privacy and system security. The current centralized data-sharing paradigm in these systems raises particular concerns about data privacy. Recognizing these challenges, the shift towards decentralized interactions in technology, as echoed by the principles of Industry 5.0, becomes paramount. This work is closely aligned with these principles, emphasizing decentralized, human-centric, and secure technological interactions in an interconnected vehicular ecosystem. To embody this, we propose a practical approach that merges two emerging technologies: Federated Learning (FL) and Blockchain. The integration of these technologies enables the creation of a decentralized vehicular network. In this setting, vehicles can learn from each other without compromising privacy while also ensuring data integrity and accountability. Initial experiments show that compared to conventional decentralized federated learning techniques, our proposed approach significantly enhances the performance and security of vehicular networks. The system's accuracy stands at 91.92\%. While this may appear to be low in comparison to state-of-the-art federated learning models, our work is noteworthy because, unlike others, it was achieved in a malicious vehicle setting. Despite the challenging environment, our method maintains high accuracy, making it a competent solution for preserving data privacy in vehicular networks.Comment: 7 page

Web3Recommend: Decentralised recommendations with trust and relevance

Web3Recommend is a decentralized Social Recommender System implementation that enables Web3 Platforms on Android to generate recommendations that balance trust and relevance. Generating recommendations in decentralized networks is a non-trivial problem because these networks lack a global perspective due to the absence of a central authority. Further, decentralized networks are prone to Sybil Attacks in which a single malicious user can generate multiple fake or Sybil identities. Web3Recommend relies on a novel graph-based content recommendation design inspired by GraphJet, a recommendation system used in Twitter enhanced with MeritRank, a decentralized reputation scheme that provides Sybil-resistance to the system. By adding MeritRank's decay parameters to the vanilla Social Recommender Systems' personalized SALSA graph algorithm, we can provide theoretical guarantees against Sybil Attacks in the generated recommendations. Similar to GraphJet, we focus on generating real-time recommendations by only acting on recent interactions in the social network, allowing us to cater temporally contextual recommendations while keeping a tight bound on the memory usage in resource-constrained devices, allowing for a seamless user experience. As a proof-of-concept, we integrate our system with MusicDAO, an open-source Web3 music-sharing platform, to generate personalized, real-time recommendations. Thus, we provide the first Sybil-resistant Social Recommender System, allowing real-time recommendations beyond classic user-based collaborative filtering. The system is also rigorously tested with extensive unit and integration tests. Further, our experiments demonstrate the trust-relevance balance of recommendations against multiple adversarial strategies in a test network generated using data from real music platforms

On the Convergence of Blockchain and Internet of Things (IoT) Technologies

The Internet of Things (IoT) technology will soon become an integral part of our daily lives to facilitate the control and monitoring of processes and objects and revolutionize the ways that human interacts with the physical world. For all features of IoT to become fully functional in practice, there are several obstacles on the way to be surmounted and critical challenges to be addressed. These include, but are not limited to cybersecurity, data privacy, energy consumption, and scalability. The Blockchain decentralized nature and its multi-faceted procedures offer a useful mechanism to tackle several of these IoT challenges. However, applying the Blockchain protocols to IoT without considering their tremendous computational loads, delays, and bandwidth overhead can let to a new set of problems. This review evaluates some of the main challenges we face in the integration of Blockchain and IoT technologies and provides insights and high-level solutions that can potentially handle the shortcomings and constraints of both IoT and Blockchain technologies.Comment: Includes 11 Pages, 3 Figures, To publish in Journal of Strategic Innovation and Sustainability for issue JSIS 14(1

Survival Study on Blockchain Based 6G-Enabled Mobile Edge Computation for IoT Automation

Internet of Things (IoT) and Mobile Edge Computing (MEC) technology acts as a significant part of daily lives to facilitate control and monitoring of objects to revolutionize the ways that human interacts with physical world. IoT system includes large volume of data with network connectivity, power, and storage resources to transform data into meaningful information. Blockchain has decentralized nature to provide useful mechanism for addressing IoT challenges. Blockchain is distributed ledger with fundamental attributes, namely recorded, transparent, and decentralized. Blockchain formed participants in distributed ledger to record the transactions and communicate with other through trustless method. Security is considered as the most valuable features of Blockchain. IoT and Blockchain are emerging ideas for creating the applications to share the intrinsic features. Several existing works has been developed for the integration of blockchain with IoT. But, Blockchain protocols in the state-of-the-art works with IoT failed to consider the computational loads, delays, and bandwidth overhead which lead to new set of problems. The review estimates main challenges in integration of Blockchain and IoT technologies to attain high-level solutions by addressing the shortcomings and limitations of IoT and Blockchain technologies

Domain-based distributes mediation system for large-scale data integration

The increasing use of computers and the development of communication infrastructures resulted in abundance of information on the networks and extremely need for querying and integrating data from large number of data sources, especially for scientific applications. Distributed mediation system performs this task fragmentally, where each mediator in the system architecture responsible for querying subset of data sources.To make such type of systems success in large scale, we must deal with two issues: logical distribution of the data sources and mediators in the system architecture, and logical interaction between the mediators.To handle these issues, this paper proposes a domain based distributed mediation system called Multi-Mediators System for Large scale Data Integration (MMSLDI).MMSLDI enables the reducing of the general query response time by eliminating unnecessary visits to the data sources that do not contribute to the answer of the query.Moreover, it satisfies the requirements of adaptation to various kinds of domains, decentralized control, and automation of its processes