Rapid jamming detection approach based on fuzzy in WSN

Kanagasabapathy, P.; Poornachary, Vijayakumar Kedalu; Murugan, Saravanan; Natesan, Arivazhagan; Ponnusamy, Vijayakumar

doi:10.1002/dac.4205

Cited by 12 publications

(4 citation statements)

References 24 publications

(30 reference statements)

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“…It can be designed to cover the frequency bands of 2.61, 3.12, 4.32, 6.54, and 7.62 GHz. It can be designed using advanced design system (ADS) and measured using vector network analyzer (VNA). “Rapid Jamming Detection in approach based on fuzzy in WSN”—Authored by K , Pradeep Mohan Kumar; K P , Vijayakumar; M , Saravanan; N , Arivazhagan; P , Vijayakumar: This paper [11] proposes two approaches in the cluster‐based sensor network to detect the maliciousness level of nodes to secure sensor networks from jamming attacks. First approach detects maliciousness level of nodes using two modules, namely, certification module, and monitoring module.…”

Section: Discussionmentioning

confidence: 99%

CapsNet‐based computing in cognitive communications

Raj¹,

Chen

Kotuliak

et al. 2021

Int J Communication

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Section: Discussionmentioning

confidence: 99%

CapsNet‐based computing in cognitive communications

Raj¹,

Chen

Kotuliak

et al. 2021

Int J Communication

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“…Kanagasabapathy et al [2] proposed two approaches in the cluster-based sensor system to identify the maliciousness level of hubs to verify sensor systems from jamming assaults. The first methodology recognizes maliciousness level of hubs utilizing two modules, in particular, affirmation module and checking module.…”

Section: Literature Reviewmentioning

confidence: 99%

Enhanced Lion Optimization with Efficient Path Routing Equalization Technique against DoS Attack in Wireless Sensor Network

Elavarasan

Chitra

Adigo

2022

Wireless Communications and Mobile Computing

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In WSN, DoS (denial of service) attack makes shortcoming system. The packets travel over and over in the sensor network. By that, all the assets like data transmission, memory, and vitality are squandered by this attack. However, the attacker ought to optimize its attacker plan for request to boost the impact on the system performance because of the deficiency of vitality at the aggressor side. Denial of service (DoS) attack on the Internet has become a squeezing issue. By staying away from these sorts of attacks, network performance can be improved. Therefore, security is a fundamental requirement for these networks. Effective routing is necessary in order to overcome the issued faced by the crosslayer in the DOS attack of the WSN network for the purpose of good transmission. This research work mainly focuses on performance evaluation using optimization methods. To establish the efficient path in the crosslayer against DoS attack, this paper has proposed enhanced lion optimization with an efficient path routing equalization technique (LOEPRE). If any failure node occurs in the network, then the node is recognized and the transfer of the data packet is done to the other node. Retransmission of data causes overload in the network. The proposed model focuses on these issues and overcomes these issues by improving the path efficiently with robust security. It consists of three phases: the initial phase includes the route discovery in the network. In the second phase, the transfer of data is done in the high router path for security purposes. Finally, the efficient path routing equalization technique is used for minimizing the overload in the network; it provides the equalized path length in the network and is highly efficient. Hence, the proposed LOEPRE technique is used to achieve energy efficiency in wireless network for prolonged network lifetime and minimum packet latency and minimize consumption of energy. Moreover, the simulation outcome of the proposed LOEPRE method is highly robust while comparing to the existing methods EFCRS, SSPRA ELOER, EFLOR, and TSTP. It achieves better performance than existing algorithms in comparing metric connectivity ratio, end-to-end delay, overhead, throughput, and packet delivery ratio.

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“…Another approach for protecting WSNs from jamming attacks is provided in [82], which introduced two schemes to identify the maliciousness level of nodes in clustered WSNs. The first scheme contains two modules named monitoring and certification modules.…”

Section: Ai Based Solutions To Security Challenges In Wsnsmentioning

confidence: 99%

Recent Advances and Future Prospects of Using AI Solutions for Security, Fault Tolerance, and QoS Challenges in WSNs

et al. 2022

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The increasing relevance and significant acceptance of Wireless Sensor Network (WSN) solutions have aided the creation of smart environments in a multitude of sectors, including the Internet of Things, and offer ubiquitous practical applications. We examine current research trends in WSN using Artificial Intelligence (AI) technologies and the potential application of these methods for WSN improvement in this study. We emphasize the security, fault detection and tolerance, and quality of service (QoS) concerns in WSN, and provide a detailed review of current research that used different AI technologies to satisfy particular WSN objectives from 2010 to 2022. Specifically, this study’s purpose is to give a current review that compares various AI methodologies in order to provide insights for tackling existing WSN difficulties. Furthermore, there has been minimal existing related work concentrating employing AI approaches to solve security, fault detection and tolerance, and quality of service (QoS) concerns associated to WSN, and our goal is to fill the gap in existing studies. The application of AI solutions for WSN is the goal of this work, and we explore all parts of it in order to meet different WSN challenges such as security, fault detection and tolerance, and QoS. This will lead to an increased understanding of current AI applications in the areas of security, fault detection and tolerance, and QoS. Secondly, we present a comprehensive study and analysis of various AI schemes utilized in WSNs, which will aid the researchers in recognizing the most widely used techniques and the merits of employing various AI solutions to tackle WSN-related challenges. Finally, a list of open research issues has been provided, together with considerable bibliographic information, which provides useful recent research trends on the topics and encourages new research directions and possibilities.

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Rapid jamming detection approach based on fuzzy in WSN

Cited by 12 publications

References 24 publications

CapsNet‐based computing in cognitive communications

CapsNet‐based computing in cognitive communications

Enhanced Lion Optimization with Efficient Path Routing Equalization Technique against DoS Attack in Wireless Sensor Network

Recent Advances and Future Prospects of Using AI Solutions for Security, Fault Tolerance, and QoS Challenges in WSNs

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