An Optimized Congestion Retrieval Mechanism for Cognitive Radio Sensor Networks

Janani, S.; Ramaswamy, M.; Manoharan, J. Samuel

doi:10.1166/jctn.2019.8076

Cited by 7 publications

(3 citation statements)

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“…As long as PU communication is unaffected, CR users have unrestricted access to the spectrum [29] [30]. The spectrum is regularly checked for PU activity to make sure of this.…”

Section: Cognitive Radio Networkmentioning

confidence: 99%

A Novel Grasshopper Optimization-based Particle Swarm Algorithm for Effective Spectrum Sensing in Cognitive Radio Networks

2023

KSII TIIS

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In CRNs, SS is of utmost significance. Every CR user generates a sensing report during the training phase beneath various circumstances, and depending on a collective process, either communicates or remains silent. In the training stage, the fusion centre combines the local judgments made by CR users by a majority vote, and then returns a final conclusion to every CR user. Enough data regarding the environment, including the activity of PU and every CR's response to that activity, is acquired and sensing classes are created during the training stage. Every CR user compares their most recent sensing report to the previous sensing classes during the classification stage, and distance vectors are generated. The posterior probability of every sensing class is derived on the basis of quantitative data, and the sensing report is then classified as either signifying the presence or absence of PU. The ISVM technique is utilized to compute the quantitative variables necessary to compute the posterior probability. Here, the iterations of SVM are tuned by novel GO-PSA by combining GOA and PSO. Novel GO-PSA is developed since it overcomes the problem of computational complexity, returns minimum error, and also saves time when compared with various state-of-the-art algorithms. The dependability of every CR user is taken into consideration as these local choices are then integrated at the fusion centre utilizing an innovative decision combination technique. Depending on the collective choice, the CR users will then communicate or remain silent.

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“…As long as PU communication is unaffected, CR users have unrestricted access to the spectrum [29] [30]. The spectrum is regularly checked for PU activity to make sure of this.…”

Section: Cognitive Radio Networkmentioning

confidence: 99%

A Novel Grasshopper Optimization-based Particle Swarm Algorithm for Effective Spectrum Sensing in Cognitive Radio Networks

2023

KSII TIIS

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“…2 Furthermore, people want to keep their information private. 3 The privacy of vehicles must be safeguarded to prevent spectators from learning the true identities of the vehicles, tracking their movements, and deriving sensitive data. The primary goal is to progress a security system that specifically addresses one of the deadliest threats (the Sybil attack) while simultaneously protecting VANET users' privacy.…”

Section: Introductionmentioning

confidence: 99%

“…Since the VANET is connected to important life events, security is more important than it is for other wireless applications, which makes safety applications more challenging 1 2 . Furthermore, people want to keep their information private 3 . The privacy of vehicles must be safeguarded to prevent spectators from learning the true identities of the vehicles, tracking their movements, and deriving sensitive data.…”

Section: Introductionmentioning

confidence: 99%

Developing an optimized routing protocol with rumor riding technique for detection of Sybil attack in VANET environment

Navinkumar,

Somasundaram

2024

Int J Communication

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SummaryAn attack on VANET known as a Sybil attack involves the attacker claiming or stealing multiple identities with the intent of causing havoc on the network's operation by disseminating false information. To protect the VANET network from Sybil attack, a variety of methods have been proposed. In order to compensate for the Sybil attack on VANETs, a rumor riding with salp swarm optimization (SSO) based Routing protocol is developed in this research work. The primary goal of this investigation is to discover how VANETs are vulnerable to the Sybil attack in order to improve their security. Rumor riding will be used to identify the Sybil attack in the suggested strategy. VANETs are protected by the Blowfish Algorithm, which uses SSO to select the best key for each network. The collective intelligence and dynamic adaptation of SALP swarm optimization algorithm enable efficient identification of rumor sources in complex networks. The algorithm is scalable, flexible, and adept at reducing false positives and negatives, making it suitable for large‐scale monitoring. Its parallel processing capabilities and robustness ensure rapid and reliable detection. Using the NS2 platform, the proposed method is compared to existing benchmark in terms of delay, packet delivery ratio (PDR), packet loss, throughput, and attack detection rate. The proposed SSO has reduced the packet loss by nearly 5% and delay by nearly 7%, when compared with existing techniques. The delivery ratio of packet for proposed model is increased up to 8% of PDR, when compared with ACO, PSO, and FA. According to this evidence, it is clear that the proposed SSO outperformed existing approaches in a variety of performance metrics.

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Computational Overhead Analysis for Mitigation of Content Poisoning Attack in NDN-based IoT Body Area Networks

Priya,

Castro,

Sathesh Kumar

et al. 2023

Procedia Computer Science

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An Optimized Congestion Retrieval Mechanism for Cognitive Radio Sensor Networks

Cited by 7 publications

References 0 publications

A Novel Grasshopper Optimization-based Particle Swarm Algorithm for Effective Spectrum Sensing in Cognitive Radio Networks

A Novel Grasshopper Optimization-based Particle Swarm Algorithm for Effective Spectrum Sensing in Cognitive Radio Networks

Developing an optimized routing protocol with rumor riding technique for detection of Sybil attack in VANET environment

Computational Overhead Analysis for Mitigation of Content Poisoning Attack in NDN-based IoT Body Area Networks

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