Cluster Based Malicious Node Detection System for Mobile Ad-Hoc Network Using ANFIS Classifier

Gopalakrishnan, S.; Duraivelu, Hemanand; Raveendran, Arun Prasath; Arunachalam, Rajesh; Kongara, Deepika; Thangavel, Chitra

doi:10.1080/19361610.2021.2002118

Cited by 29 publications

(10 citation statements)

References 20 publications

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“…Subburayalu et al 16 have used adaptive neuro fuzzy inference system (ANFIS) classifier to identify defected nodes. The proposed mechanism extracts the conviction factors of consistent and malicious nodes and qualifies them using the ANFIS classifier.…”

Section: Related Workmentioning

confidence: 99%

Z number improved reference ideal method‐based decision‐making process for enforcing cooperation during data dissemination in mobile ad hoc networks

Mylsamy¹,

Jayaprakash²

2023

Int J Communication

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Summary In mobile ad hoc networks (MANETs), cooperative communication and resource constraint are the two important core characteristics essential to guarantee trusted data dissemination. The cooperative communication between mobile nodes depends on the trust rendered by them towards the process of reliable data routing. However, stringent resource constraints of mobile nodes such as energy, memory, communications, and computations result in the introduction of selfish and malicious node that completely degrades the network performance in different dimensions. In this paper, Z number improved reference ideal method (RIM)‐based decision‐making process (NIRIMDMP) is proposed with the merits of maximizing deviation method (MDM) and best–worst method (BWM) to ensure reliable data routing by modeling the cooperation degree in terms of Z number. This NIRIMDMP adopted Z number to represent the information reliability and handle the problem of inherent uncertainty during the process of evaluating each mobile node in the routing process. In specific, MDM and BWM are included into the proposed NIRIMDMP to determine comprehensive attribute weights based on the calculated objective and subjective weights that could be possible derived in routing. It extended the merits of classical RIM using Z numbers to confirm reliable ranking of mobile nodes, even when the optimal solution exists amid extreme values taken into consideration for assessing the mobile nodes during decision making. Simulation investigations of the proposed NIRIMDMP confirmed improved throughput and network lifetime with reduced control overhead, energy consumptions, and delay independent of the amount of malicious and non‐cooperative nodes.

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Section: Related Workmentioning

confidence: 99%

Z number improved reference ideal method‐based decision‐making process for enforcing cooperation during data dissemination in mobile ad hoc networks

Mylsamy¹,

Jayaprakash²

2023

Int J Communication

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“…In addition, there are several specific challenges to control the project based on the proposed multiagent, which are related to multiple sets of DG units and loads, coordination techniques and scalability. [35]. Sandia frequency switch (SFS) two types of inverter in anti-islanding mode, based on distributed generation (DG) interface controllers based on impact inverters equipped with an SFS scheme, the anti-islanding detection performance of fixed powercontrolled DG and fixed-current controlled DG is compared and analyzed.…”

Section: Protectionmentioning

confidence: 99%

Interaction between Technical and Economic Benefits in Distributed Generation

Vimala¹,

Ramachandran²,

Selvam³

2022

EAE

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The definition of a restricted power supply area for a distribution network disqualifies this scheme as a distributed product even though it is a very common dg scheme. Power system quality is a key issue for low and medium voltage power companies and consumers, to minimize power network losses; this paper provides guidelines for guaranteed allocation and distribution of distributed generation (DG) in distribution systems for an acceptable reliability level and voltage profile. The optimization process involves the use of genetic algorithms (GA) techniques and is solved by combining systems to estimate system reliability, losses and dg impacts on the voltage profile. The fitness evaluation process leads to the determination of the ga's relationship between investment and operating costs as a benefit of setting numerical units. Estimation based on current flow method for radial networks reconciliation of scattered generator losses with profile of voltage profile

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“…In general, big data analysis facilitates the sharing of information between different organizations in the community, identifies links between social events and integrates and analyzes information in real time to assist decision making. If companies are to generate real value, big data must be used to provide input to analytics and decision support capabilities are disappointed with the word Big Data [20]. This is a marketing term and not a technical term.…”

Section: Big Data Analyticsmentioning

confidence: 99%

Exploring the recent trends in Big Data Analysis

Suresh¹,

Ramachandran²,

Sivaji³

2022

Data Analytics and Artificial Intelligence

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Big Data is a collection of technologies developed to store, analyze and manage this data. It is a macro tool. Today it is used in fields as diverse as medicine, agriculture, gambling and environmental protection. Machine learning, forecasting Companies use big data to streamline their marketing campaigns and techniques. Modeling and other advanced analytics applications enable big data organizations to generate valuable insights. Companies use it in machine learning. Programs cannot balance large data in any particular database. When datasets are large in size, velocity, and volume, the following three distinct dimensions constitute "big data." Examples of big data analytics include stock markets, social media platforms, and jet engines. But it is growing exponentially with time. Traditional data management tools cannot store or process it efficiently. It is a large scale technology developed by Story, Analysis and Manoj, Macro-Tool. Find patterns of exploding confusion in information about smart design, however, implying that various big data structures are structured, whether this includes the amount of information, the speed with which it is generated and collected, or the variety or scope of related data points. In the past, data was collected only from spreadsheets and databases of large, disparate information that grew at an ever-increasing rate. Very large, complex data refers to large amounts of data for sets that are impossible to analyze with traditional data processing applications. Is software configuration used to handle the problem? Apache is an advanced application for storing and processing large, complex data sets and analyzing big data. Analytical techniques against very large, heterogeneous databases containing varying amounts of data, big data analytics help businesses gain insights from today's massive data sources. Defined as software tools for processing and extraction. People, companies and more and more machines are now developing technologies to analyze more complex and large databases that cannot be handled by traditional management tools. It is designed to discover patterns of chaos that explode in information in order to design smart solutions.

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Cluster Based Malicious Node Detection System for Mobile Ad-Hoc Network Using ANFIS Classifier

Cited by 29 publications

References 20 publications

Z number improved reference ideal method‐based decision‐making process for enforcing cooperation during data dissemination in mobile ad hoc networks

Z number improved reference ideal method‐based decision‐making process for enforcing cooperation during data dissemination in mobile ad hoc networks

Interaction between Technical and Economic Benefits in Distributed Generation

Exploring the recent trends in Big Data Analysis

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