Sanghyeok Lim and Taeho Cho
Department of Electrical and Computer Engineering, Sungkyunkwan University,
Republic of Korea
ABSTRACT
WSN consists of a number of nodes and base stations and is used for event monitoring in various fields
such as war situations, forest fires, and home networks. WSN sensor nodes are placed in fields that are
difficult for users to manage. It is therefore vulnerable to attackers, and attackers can use false nodes or
MAC injection attacks through the hijacked nodes to reduce the lifetime of the network or trigger false
alarms. In order to prevent such attacks, several security protocols have been proposed, and all of them
have been subjected to MAC-dependent validation, making it impossible to defend against false report
attacks in extreme attack circumstances. As attacks have recently become more diverse and more
intelligent, WSNs require intelligent methods of security. Based on the report information gathered from
the base station, the proposed method provides a technique to prevent attacks that may occur where all
MAC information is damaged by carrying out verification of a false report attack through the machine
learning based prediction model and the evaluation function.
KEYWORDS
Network Protocols, Wireless Sensor Network, simulation, machine learning, neural network
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