A Time Interval based Blockchain Model for Detection of Malicious Nodes in MANET Using Network Block Monitoring Node

Mobile Ad Hoc Networks (MANETs) are infrastructure-less networks that are mainly used for establishing communication during the situation where wired network fails. Security related information collection is a fundamental part of the identification of attacks in Mobile Ad Hoc Networks (MANETs). A no...

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Bibliographic Details
Published in2020 Second International Conference on Inventive Research in Computing Applications (ICIRCA) pp. 852 - 857
Main Authors Narayana, V.Lakshman, Midhunchakkaravarthy, Divya
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.07.2020
Subjects
Block Analysis
Conferences
Data communication
Malicious Node Detection
Mobile ad hoc networks
Monitoring
Network Block Monitoring Node
Routing
Routing table
Time Interval Based Blockchain Model
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Summary:Mobile Ad Hoc Networks (MANETs) are infrastructure-less networks that are mainly used for establishing communication during the situation where wired network fails. Security related information collection is a fundamental part of the identification of attacks in Mobile Ad Hoc Networks (MANETs). A node should find accessible routes to remaining nodes for information assortment and gather security related information during route discovery for choosing secured routes. During data communication, malicious nodes enter the network and cause disturbances during data transmission and reduce the performance of the system. In this manuscript, a Time Interval Based Blockchain Model (TIBBM) for security related information assortment that identifies malicious nodes in the MANET is proposed. The proposed model builds the Blockchain information structure which is utilized to distinguish malicious nodes at specified time intervals. To perform a malicious node identification process, a Network Block Monitoring Node (NBMN) is selected after route selection and this node will monitor the blocks created by the nodes in the routing table. At long last, NBMN node understands the location of malicious nodes by utilizing the Blocks created. The proposed model is compared with the traditional malicious node identification model and the results show that the proposed model exhibits better performance in malicious node detection.
DOI:10.1109/ICIRCA48905.2020.9183256