Adaptive fuzzy inference system for detection and prevention of cooperative black hole attack in MANETs

Hiremath, P. S.; Anuradha, T.; Pattan, Prakash

doi:10.1109/infosci.2016.7845335

Cited by 14 publications

(19 citation statements)

References 9 publications

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“…The imitation results of define approach are being compared with that of adaptive technique, in which sender node checks each and every nodes activity via DAT table with the aim of maintenance from-node-tonext node's information and that declares black hole node all the way through channel overhearing method. It is observed that the define method depend on adaptive fuzzy logic system shows better performance as compared to adaptive method in terms of throughput, end-to-end delay and PDR [7].…”

Section: Literature Surveymentioning

confidence: 98%

Improved Technique for Prevention of Black Hole Attack in Mobile Ad Hoc Network

2017

IJAERD

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Section: Literature Surveymentioning

confidence: 98%

Improved Technique for Prevention of Black Hole Attack in Mobile Ad Hoc Network

2017

IJAERD

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“…P.S. Hiremath, T. Anuradha, and P. Pattan [14] has presented adaptive fuzzy interference system for detection and prevention of cooperative blackhole attack in MANETs. Adaptive Fuzzy interference system to prevent and detect the supportive black hole attack on MANETs.…”

Section: Related Workmentioning

confidence: 99%

“…There are many methods like an initially adaptive system of the fuzzy interface to discover and avoid the BH attack. The fuzzy logic deals with such applications more accurately because of its resemblance to human decision making, that is, its ability to produce an exact solution from incomplete or fairly inaccurate information [6]. In order to sense and stop selective BH attacks, the Intrusion detection system (IDS) nodes are organised in MANETs.…”

Section: Introductionmentioning

confidence: 99%

An Efficient Detection of BH Attack with Secured Routing Using ACO and DualRSA in MANETs

Shivamallaiah¹,

Karibasappa²

2018

IJIES

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Nowadays, wireless communication plays a major role in sending information from one area to another in an effective way. In wireless communication, the important parameters are coverage area, power consumption, lifetime, and Black Hole (BH) detection in network with interconnected mobile nodes. Ant Colony Optimization (ACO) is used for finding shortest path in the Network. ACO helps in choosing another path, if there is any malicious node in the network. Data is secured using Dual Rivest-Shamir-Adleman (DRSA) technique and Black Hole Detection (BD) is used for identifying malicious node in the network. For efficient wireless system these parameters have been optimized, several algorithms have been applied to optimize the performance parameters and detect the BH in the network. Efficient BH identification with optimized routing algorithm is implemented in secured environment by using Dual RSA. The ACO-DRSA-BD algorithm precisely detected the BH Node (BHN) in finding the proper solution for data transmission using ACO and secured environment using DRSA. Hence, "ACO-DRSA-BD" finds proper solutions for transmitting data in the presence of BH Attacks and enhancing better performance parameters in terms of throughput, routing overhead and energy consumption.

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“…Hiremath et al proposed an adaptive system of fuzzy interference to detect and prevent the black hole attack. In [12], four input used for the Fuzzy Interference System (FIS): trust, data loss, data rate, and energy (characterize the quality of next hop neighborhood). These information are sent periodically by each node to update neighbor information.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The system of fuzzy interference is used in the step of selecting of the next hop neighbor. This strategy is compared to an adaptive method [13] and the simulation results shows a better performance for the proposed solution.…”

Section: Literature Reviewmentioning

confidence: 99%