Trust-aware FuzzyClus-Fuzzy NB: intrusion detection scheme based on fuzzy clustering and Bayesian rule

Veeraiah, Neenavath; Krishna, B. T.

doi:10.1007/s11276-018-01933-0

Cited by 35 publications

(27 citation statements)

References 17 publications

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“…Fuzzy clustering is also called soft clustering or soft kmeans is one of the clustering technique in which each node can belong to multi cluster. In fuzzy clustering [1] the clustered nodes belongs to a cluster based on the membership degree. The advantages the Fuzzy clustering technique isi suitable for imprecated data and the individual point of data chimes to either unique or multi cluster center because of the enrolment functions.…”

Section: 1fuzzy Clusteringmentioning

confidence: 99%

“…Generally we are considering the nodes initial energy, residual energy, energy consumption rate and average energy of the network for CH selection. Along these parameters we are proposed trust [1] factors defines the accurate selection of the CH's. a) CH selection depending upon on the data bytes forwarded from one node to another node: The cluster head selection based on datum send by Transceivers' node.…”

Section: Trust Factors For Ch Selectionmentioning

confidence: 99%

“…a) CH selection depending upon on the data bytes forwarded from one node to another node: The cluster head selection based on datum send by Transceivers' node. The element of trust [1] is given as,…”

Section: Trust Factors For Ch Selectionmentioning

confidence: 99%

“…The cluster head selection stands on the error in the connection of network. The formulae for the error [1] in network connection is given as,…”

Section: B) Ch Selection Hinge On the Error In Connection Of Networkmentioning

confidence: 99%

“…The CH selection is based on the packet delivery [1] of data which is the sum of packets of data remitted in between the nodes that hinges on the scale of the quantity of data packets retrieved from the nodes to the number of the data packets forwarded between the nodes. The element of trust is represented as,…”

Section: C) Ch Selection Stands On the No Of Data Packet Delivery Amimentioning

confidence: 99%

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A Fuzzy Clustering with Optimized Cluster Head Selection Method in MANET

Veeraiah¹,

Krishna²

2019

IJRTE

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MANET’S are a kind of Wireless ad hoc networks. The nodes in the networks are randomly move to different directions, self configurable and the network topology is various continuously and its act as a point-to-point, self-organisable, selfhealing network.The network that assembled as an integral will be easily motile along with the nodes available in the network be capable of diagnosing the existence of remnant nodes and implement the establishment of decisive network to facilitate communications. Large networks are divided into various subnetworks and this segregation is called clustering which plays a compelling role in ad hoc networks. Clustering technique was primarily implemented to decrease the consumption of energy, efficient realization of MAC is enhanced, for security mechanisms and gathering of data. A mob of nodes that are interconnected together are called cluster. A committed node consisting of nodes that are interconnected is defined as CH (Cluster Head). Cluster head is crucially helpful for operating network in a desired way.This sweeping survey cynosures principally on the different clustering, Cluster head selection methodologies and compare with the proposed Fuzzy clustering with optimized cluster head selection method in terms of delay, energy, and throughput parameters

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Section: 1fuzzy Clusteringmentioning

confidence: 99%

Section: Trust Factors For Ch Selectionmentioning

confidence: 99%

Section: Trust Factors For Ch Selectionmentioning

confidence: 99%

“…The cluster head selection stands on the error in the connection of network. The formulae for the error [1] in network connection is given as,…”

Section: B) Ch Selection Hinge On the Error In Connection Of Networkmentioning

confidence: 99%

Section: C) Ch Selection Stands On the No Of Data Packet Delivery Amimentioning

confidence: 99%

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A Fuzzy Clustering with Optimized Cluster Head Selection Method in MANET

Veeraiah¹,

Krishna²

2019

IJRTE

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Capitulation of mitigation techniques of packet drop attacks in MANET to foreground nuances and ascertain trends

Singh¹,

Bhasin

Kalia³

2021

Int J Communication

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MANET is a kind of wireless ad hoc networks, in which mobile nodes operate in dynamic, distributed, and cooperative environment. Open nature of MANET makes it vulnerable to various kinds of attacks. Of these, the most severe are the packet drop attacks such as Blackhole attack, Cooperative Blackhole, and Grayhole attacks. The malicious nodes drop the packets as these packets are routed through them in accordance with the malefic strategy of the particular packet drop attack, which adversely affects the network performance. A substantial amount of research papers focus on dealing with packet drop attacks in the last few years, but security is still an impending issue. In this paper, we have presented the systematic review of the literature of last 6 years on all variants of packet drop attacks. We have classified these techniques into four categories, namely, mathematical based, monitoring based, network dependent, and amalgamation based which are further sub divided into 12 categories. These papers are categorized in a well-defined structure to bring out their contribution, to underline the left-out things, and to foreground the emerging issues for future research. Detailed observations are recorded following a panoptic study in order to identify and divulge more eligible and effective mitigation techniques in a particular environment.

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A Framework of Blockchain-Based Collaborative Intrusion Detection in Software Defined Networking

Tan²,

Wang

2020

Network and System Security

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Trust-aware FuzzyClus-Fuzzy NB: intrusion detection scheme based on fuzzy clustering and Bayesian rule

Cited by 35 publications

References 17 publications

A Fuzzy Clustering with Optimized Cluster Head Selection Method in MANET

A Fuzzy Clustering with Optimized Cluster Head Selection Method in MANET

Capitulation of mitigation techniques of packet drop attacks in MANET to foreground nuances and ascertain trends

A Framework of Blockchain-Based Collaborative Intrusion Detection in Software Defined Networking

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