Secure Watermarking Schemes and Their Approaches in the IoT Technology: An Overview

Wazirali, Raniyah; Ahmad, Rami; Al-Amayreh, Ahmed; Al-Madi, Mohammad; Khalifeh, Ala’

doi:10.3390/electronics10141744

Cited by 41 publications

(20 citation statements)

References 112 publications

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“…In the process of informatization construction of the public service system of national fitness, big data technology can help integrate, utilize and analyze the information of national fitness. The national fitness information platform based on big data can better serve the national fitness movement, bring development impetus to the construction of the national fitness information service system, and promote the development of national fitness [19]. The platform includes a three-tier architecture, namely the user layer, the service layer and the data layer, as shown in Figure 5.…”

Section: Data Acquisition Of Sports Big Data Platformmentioning

confidence: 99%

Structure Optimization of National Fitness Sports Big Data Platform Based on IOT Technology

Song

2022

Preprint

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With the development of the times, sports are more and more favored by people, and national fitness has become a new trend in the development of the times. In this context, to win the long-term development of sports, it must realize the integration with big data. At present, data acquisition in the sports field mainly relies on manual capture and machine intelligence recognition. However, the data capture capabilities of the two are limited and cannot provide real-time data support for the intelligent sports big data platform. The IOT is an expandable network with intelligent perception capability, which can sense and acquire sports data in time. Based on this, the article proposed a big data platform for national fitness and sports that integrated the IOT technology. It aimed to optimize the sports big data platform from the perspective of the IOT. And finally an intelligent sports big data platform was realized. The article firstly optimized the underlying structure of the sports big data platform. Then, the data acquisition strategy of the big data platform was improved by using the IOT technology, and the intelligent data acquisition was realized at the technical level. Finally, the article also optimized the structure of the intelligent resources of the sports big data platform, and initially built an intelligent sports big data platform. After data inspection and testing, the article found that the intelligent sports big data platform relying on the Internet of Things technology could further reduce the time and space complexity of data processing, and the running time was reduced by 50% year-on-year. This fully shows that the Internet of Things technology can promote the structural optimization of the sports big data platform.

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Section: Data Acquisition Of Sports Big Data Platformmentioning

confidence: 99%

Structure Optimization of National Fitness Sports Big Data Platform Based on IOT Technology

Song

2022

Preprint

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“…When there are similar values in a spatial field and there is a tendency of aggregation between these values, the spatial field will show a strong positive autocorrelation. On the contrary, if the spatial field has two values whose attributes are mutually exclusive, the spatial field will show negative autocorrelation [ 16 ]. Spatial autocorrelation represents the relationship between the observed values of two adjacent regions.…”

Section: Agricultural Intensive Development In the Context Of Iotmentioning

confidence: 99%

The Panel Spatial Econometric Analysis for Development of Green Intensive Agriculture Based on Edge Computing and Internet of Things

Shi

2022

Journal of Environmental and Public Health

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To further promote the modernization of agriculture and the prosperity of green industry, the analyses are made on the intensive level of agriculture by using spatial econometric model under the Internet of Things (IoT), and the optimal defense strategy is adopted for edge network equipment to ensure the security of agricultural information. Initially, the present work introduces the related concepts of agricultural intensive development and analyzes the important role of IoT in the development process of agricultural modernization. Next, it briefly explains the spatial econometric analysis method, introduces two basic spatial analysis models-spatial lag model (SLM) and spatial error model (SEM), and explains their principles in detail. Then, it signifies the characteristics of IoT and edge computing (EC) and designs the optimal defense strategy of edge network equipment from the perspective of IoT. Finally, the simulation experiment is carried out based on the edge network defense strategy, and the spatial econometric analysis is carried out by taking the agricultural intensive development of counties in a Chinese province as an example. The experimental results show that with the increase of the number of edge network devices, the optimal strategy of edge network defense can be adopted while consuming certain computing resources. The agricultural technology input and intensive level in the jurisdiction have high spatial correlation, so it is necessary to establish a spatial econometric model for analysis. Additionally, the statistics of SLM is higher than that of SEM, which shows that SLM can better reflect the technology investment and spatial correlation than SEM does. Both industrial and agricultural division of labor and agricultural production link division of labor can promote the level of intensification, among which the promotion of industrial and agricultural division of labor is not very significant, while the promotion of agricultural production link division of labor is very significant.

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“…Wireless Sensor Network (WSN) is one of the most effective methods for many realtime applications, due to its compactness, cost-effectiveness, and ease of deployment [1]. The function of the WSN is to monitor the field of interest, collect the data, and transmit it to the base station (Access point) for post-processing analysis [2].…”

Section: Introductionmentioning

confidence: 99%

Machine Learning for Wireless Sensor Networks Security: An Overview of Challenges and Issues

Ahmad

Wazirali

Abu-Ain

2022

Sensors

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Energy and security are major challenges in a wireless sensor network, and they work oppositely. As security complexity increases, battery drain will increase. Due to the limited power in wireless sensor networks, options to rely on the security of ordinary protocols embodied in encryption and key management are futile due to the nature of communication between sensors and the ever-changing network topology. Therefore, machine learning algorithms are one of the proposed solutions for providing security services in this type of network by including monitoring and decision intelligence. Machine learning algorithms present additional hurdles in terms of training and the amount of data required for training. This paper provides a convenient reference for wireless sensor network infrastructure and the security challenges it faces. It also discusses the possibility of benefiting from machine learning algorithms by reducing the security costs of wireless sensor networks in several domains; in addition to the challenges and proposed solutions to improving the ability of sensors to identify threats, attacks, risks, and malicious nodes through their ability to learn and self-development using machine learning algorithms. Furthermore, this paper discusses open issues related to adapting machine learning algorithms to the capabilities of sensors in this type of network.

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Secure Watermarking Schemes and Their Approaches in the IoT Technology: An Overview

Cited by 41 publications

References 112 publications

Structure Optimization of National Fitness Sports Big Data Platform Based on IOT Technology

Structure Optimization of National Fitness Sports Big Data Platform Based on IOT Technology

The Panel Spatial Econometric Analysis for Development of Green Intensive Agriculture Based on Edge Computing and Internet of Things

Machine Learning for Wireless Sensor Networks Security: An Overview of Challenges and Issues

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