Data Transmission and Access Protection of Community Medical Internet of Things

On the basis of Internet of Things (IoT) technologies, Community Medical Internet of Things (CMIoT) is a new medical information system and generates massive multiple types of medical data which contain all kinds of user identity data, various types of medical data, and other sensitive information. To effectively protect users’ privacy, we propose a secure privacy data protection scheme including transmission protection and access control. For the uplink transmission data protection, bidirectional identity authentication and fragmented multipath data transmission are used, and for the downlink data protection, fine grained access control and dynamic authorization are used. Through theoretical analysis and experiment evaluation, it is proved that the community medical data can be effectively protected in the transmission and access process without high performance loss

Exploring the Role of Industry 4.0 on Global Logistics:Challenges in Big Data and IoT

The globalization of the economy and consumers' increasing demand for customized products have led to a rise in the complexity of global logistics chains. In response to these challenges, the integration of logistics with the Internet of Things (IoT) and Big Data, known as Logistics 4.0, offers opportunities for more efficient planning, control, and adaptation of logistics processes. Industry 4.0, with its emphasis on IoT and Big Data analytics, significantly influences the logistics sector, making it a pioneer in the digital transformation of the entire economy. This paper seeks to review and analyze the role and impacts of Industry 4.0 on global logistics, while also addressing the main challenges related to IT security, data protection, and successful implementation of Big Data Analytics in the supply chain. Additionally, it aims to explore the changes in work systems within companies due to digital transformation in logistics

State regulation of the IoT in the Russian Federation: Fundamentals and challenges

The purpose of this section is to study the problems with implementing technical and legal regulations for the development of public administration functions in the Russian Federation when using the internet of things (IoT). The introduction is based on an analysis of regulatory legal acts and presents the main strategic directions for the development of public administration functions in the Russian federation when using IoT. State reports, scientific literature, a system of technical and legal regulation are analyzed, and the main problems of implementing the IoT that impede the achievement of effective public administration are studied. The Russian practice of using IoT in various economic areas is investigated. Based on an analysis of the mechanisms for ensuring data safety of information technology users in the Russian federation, problems were investigated, such as the collecting data through IoT, including publicly available personal data in order to profile human activities, and creating of a digital twin of a person. The social constraints for introducing distributed registry technologies are users' distrust in the field of data privacy protection and mathematical algorithms that are used to establish trust in a digital environment instead of trusted centralized intermediaries; these problems were also analyzed. The Russian approach was analyzed in comparison to European experience in this field. To ensure information security and the possibility of its distribution, the IoT is revealed

Strategies for Improving Data Protection to Reduce Data Loss from Cyberattacks

Accidental and targeted data breaches threaten sustainable business practices and personal privacy, exposing all types of businesses to increased data loss and financial impacts. This single case study was conducted in a medium-sized enterprise located in Brevard County, Florida, to explore the successful data protection strategies employed by the information system and information technology business leaders. Actor-network theory was the conceptual framework for the study with a graphical syntax to model data protection strategies. Data were collected from semistructured interviews of 3 business leaders, archival documents, and field notes. Data were analyzed using thematic, analytic, and software analysis, and methodological triangulation. Three themes materialized from the data analyses: people--inferring security personnel, network engineers, system engineers, and qualified personnel to know how to monitor data; processes--inferring the activities required to protect data from data loss; and technology--inferring scientific knowledge used by people to protect data from data loss. The findings are indicative of successful application of data protection strategies and may be modeled to assess vulnerabilities from technical and nontechnical threats impacting risk and loss of sensitive data. The implications of this study for positive social change include the potential to alter attitudes toward data protection, creating a better environment for people to live and work; reduce recovery costs resulting from Internet crimes, improving social well-being; and enhance methods for the protection of sensitive, proprietary, and personally identifiable information, which advances the privacy rights for society