Community privacy estimation method based on key node method in space social Internet of Things

Chen, Guobin; Huang, Tangsen

doi:10.1177/1550147719883131

Cited by 3 publications

(3 citation statements)

References 23 publications

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“…The inference method is moderately simple. Chen and Huang (2019) has demonstrated to discover key nodes in information dispersal by learning the complete social data. The similarity rules of information between non-key hubs and key hubs are determined and the inference rule information set is obtained.…”

Section: B Privacy Preservation In S-iotmentioning

confidence: 99%

A Comprehensive Survey on Security, Trust Management and Privacy Preservation for Social-Internet-of-Things (S-IoT)

Rahul¹,

Venkatesh²,

Venugopal³

2023

Journal of Computer Science

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The Social Internet of Things (S-IoT) is a new paradigm that evolved with a convergence of social networking concepts and internet of things concepts. This paradigm helps develop intelligent devices and services with higher utility. The new paradigm enriches the social interaction between human's objects, heterogenous social objects interaction, the discovery of service and scalability. In recent years, S-IoT has been researching a hot topic and has drawn the attention of researchers, resulting in research on trust management, privacy preservation, service provisioning and security mechanisms. However, S-IoT faces new research challenges like interoperability, trustworthiness, security threats, scalability, navigability, service discovery and composition. In line with the research trend, this article provides a systematic survey of fundamental concepts of S-IoT and IoT, distinguishable characteristics of S-IoT and IoT and research challenges in S-IoT. This survey thoroughly reviews secure communication mechanisms, privacy-preservation techniques and the trust-evaluation model in S-IoT. Furthermore, we accentuate the privacy-preservation mechanism proposed in the literature for seven years and explored research areas. The holistic survey gives an overview of trust-evaluation models with respect to the service provider's perspective. This article overviews secure communication protocols and architecture in the S-IoT context. Finally, various research gaps, applications of S-IoT and research directions help a researcher to carry out research work in S-IoT.

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Section: B Privacy Preservation In S-iotmentioning

confidence: 99%

A Comprehensive Survey on Security, Trust Management and Privacy Preservation for Social-Internet-of-Things (S-IoT)

Rahul¹,

Venkatesh²,

Venugopal³

2023

Journal of Computer Science

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“…Aiming at formula (10), the greedy heuristic algorithm GG (greedy grouping) 32 is used to solve the optimal sensing period. While the sensing performance and energy consumption meet the minimum requirements, the balance between perception performance and energy consumption is achieved.…”

Section: Interleaved Grouping Algorithmmentioning

confidence: 99%

Energy-efficient and intelligent cooperative spectrum sensing algorithm in cognitive radio networks

Huang

Yin

2022

International Journal of Distributed Sensor Networks

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Green communication is the demand of current and future wireless communication. As the next-generation communication network, cognitive radio network also needs to meet the requirements of green communication. Therefore, improving energy efficiency is an inevitable requirement for the development of cognitive radio networks. However, there is a need to compromise sensing performance while improving energy efficiency. To take into account the two important indicators of sensing performance and energy efficiency, a grouping algorithm is proposed in this article, which can effectively improve the energy efficiency while improving the spectrum sensing performance. The algorithm obtains the initial value of the reliability of the nodes through training, and sorts them according to the highest reliability value, then selects an even number of nodes with the highest reliability value, and divides the selected nodes into two groups, and the two groups of nodes take turns in Alternate work. At this time, other nodes not participating in cooperative spectrum sensing are in a silent state, waiting for the instruction of the fusion center. The experimental results show that compared with the traditional algorithm, the proposed algorithm has a great improvement in the two indicators of sensing performance and energy efficiency.

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“…The experiment was carried out by the Monte Carlo simulation in this paper. This test runs VMware esxi 6.7.0 (build 8169922) bare metal virtual machine system on a workstation using two Intel Xeon Gold6128 3.7GHz processors, 256 Gb memory and Samsung SM961 / PM961 SSD [36].…”

Section: Analysis Of the Simulation Experimentsmentioning

confidence: 99%

A Blockchain-Based Node Selection Algorithm in Cognitive Wireless Networks

Huang

Ying

2020

IEEE Access

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In cognitive wireless networks, multi-node cooperative spectrum sensing can effectively improve the accuracy of spectrum sensing, but there is a non-linear relationship between the number of nodes and sensing accuracy. Nodes with low reliability participate in cooperative sensing, which is not conducive to the improvement of sensing accuracy, and reduces the energy efficiency of spectrum sensing, which poses challenges to the normal operation of cognitive wireless networks. In order to improve energy efficiency and sensing performance, this paper proposes the node evaluation and scheduling (NES) algorithm and the Secure Spectrum Sensing based on Blockchain (SSSB) algorithm, which can evaluate the reliability of sensing nodes in real time, and obtain the trust value of the node. The nodes information is stored in the management center of blockchain. Blockchain encrypts nodes information to ensure that a node corresponds to its own trust value without confusion. Fusion Center of cognitive wireless networks select good performance nodes to participate in cooperative spectrum sensing. Which can reduce energy consumption while improving the sensing performance. The simulation experiment results show that the new algorithm in this paper is far superior to the traditional algorithm. Under the same other conditions, the detection probability is increased by 5%, and the energy consumption is reduced by 10%, and the safety index has also been greatly improved.INDEX TERMS Cognitive wireless networks, blockchain, energy efficiency, sensing accuracy.

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Community privacy estimation method based on key node method in space social Internet of Things

Cited by 3 publications

References 23 publications

A Comprehensive Survey on Security, Trust Management and Privacy Preservation for Social-Internet-of-Things (S-IoT)

A Comprehensive Survey on Security, Trust Management and Privacy Preservation for Social-Internet-of-Things (S-IoT)

Energy-efficient and intelligent cooperative spectrum sensing algorithm in cognitive radio networks

A Blockchain-Based Node Selection Algorithm in Cognitive Wireless Networks

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