Hierarchical game-based secure data collection with trust and reputation management in the cognitive radio network

Bennaceur, Jihen; Idoudi, Hanen; Saı̈dane, Leı̈la Azouz

doi:10.1016/j.compeleceng.2021.107463

Cited by 4 publications

(2 citation statements)

References 9 publications

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“…The main challenge was the user acquirement of different channels at various times, which divided the network into various clusters. In [71], authors illustrated the study of various machine learning algorithms like Artificial Neural Network (ANN), SVM, k-nearest neighbor (KNN), random forest tree, Hoeffding tree and Naïve Bayes method for Automatic modulation recognition (AMR). Particularly, a Nonnegative Matrix Factorization (NMF) technique [72] was presented in this proposed work and the comparative results were evaluated using the mentioned traditional techniques.…”

Section: Literature Surveymentioning

confidence: 99%

Analysis of Secure Cognitive Radio Network with Optimal Resource Management

Kumar,

Sharanya

2023

ijmst

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During the last decade, Cognitive Radio Network (CRN) technology has been a significant advance in addressing the ever-increasing spectrum demand. As the number of licensed and unlicensed users in a network rises to complete a certain activity, the information exchange between various types of traffic becomes more complex and difficult. Congestion in CRN is also caused by the conflict among several users for channel access (PUs and SUs). In a very crowded network, many applications perform badly owing to packet collisions and, as a result, packet loss before significant buffer queue building. This circumstance is aggravated by an increase in network users. Congestion control is a vital and essential aspect of the present research issue in communication networks. Several recent reviews in the literature indicate that the congestion issue in the CRN has not been thoroughly studied. Thus, effective and efficient congestion control strategies are sought to optimize network resource usage and management. To prevent congestion, it is crucial for CRN to do research on the creation of an efficient congestion management system. This will improve the network's resource consumption and performance. "Performance improvement via efficient spectrum management through optimum resource management and congestion control in the CRN by mitigating different threats" is the primary target of this project. This research also focused on enhancing performance by addressing security issues in an IoT-based CRN environment. This study provides a comprehensive review of several similar studies and their limitations, which may be used to formulate a new research target.

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Section: Literature Surveymentioning

confidence: 99%

Analysis of Secure Cognitive Radio Network with Optimal Resource Management

Kumar,

Sharanya

2023

ijmst

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“…SeRINS is used for obtaining the simulation results. "Hierarchical Multi Game-based Architecture (HMGA)" [31] is proposed for secured data management through sensing, data collection, and routing of data packets. Cognitive features were fetched from every game layer, and malicious nodes' behavior was fetched.…”

Section: Literature Reviewmentioning

confidence: 99%

Diligence Eagle Optimization Protocol for Secure Routing (DEOPSR) in Cloud-Based Wireless Sensor Network

Ramkumar¹,

Vadivel

Mani³

et al. 2022

Preprint

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Wireless sensor networks (WSN) are essential for various applications that collect and analyze data from the physical environment. Cloud computing particularly provides a benchmarks method for distributed resource sharing. The concept of “Sensor Clouds” has emerged due to extending the paradigm of cloud computing to include sharing the sensed data through WSN. Data collected by these many sensor-based applications is enormous. Routing is significant in cloud-based WSN (CWSN). Poor routing protocol affects the performance of CWSN severely. In this paper, Diligence Eagle Optimization Protocol for Secure Routing (DEOPSR) is proposed for CWSN. DEOPSR is inspired from natural foraging characteristics of eagle. DEOPSR hold two different types of searching to send data to destination which are local search and global search. Parameter adaption schemes present in DEOPSR assist in selecting the best route and avoiding the selfish nodes in routing. In NS3, the performance of DEOPSR was examined using performance measures prevalently used in computer networks. DEOPSR outperforms the present routing protocols, according to the data.

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Trust-based Energy Aware Routing Protocol to Improve Network Lifetime in CRNs

Kumar,

Singh

2023

2023 7th International Conference on I-Smac (IoT in Social, Mobile, Analytics and Cloud) (I-Smac)

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Hierarchical game-based secure data collection with trust and reputation management in the cognitive radio network

Cited by 4 publications

References 9 publications

Analysis of Secure Cognitive Radio Network with Optimal Resource Management

Analysis of Secure Cognitive Radio Network with Optimal Resource Management

Diligence Eagle Optimization Protocol for Secure Routing (DEOPSR) in Cloud-Based Wireless Sensor Network

Trust-based Energy Aware Routing Protocol to Improve Network Lifetime in CRNs

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