Malicious Node Detection Using Convolution Technique: Authentication in Wireless Sensor Networks (WSN)

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Author(s): Priyanka Ahlawat (National Institute of Technology, Kurukshetra, India), Pranjil Singhal (National Institute of Technology, Kurukshetra, India), Khushi Goyal (National Institute of Technology, Kurukshetra, India), Kanak Yadav (National Institute of Technology, Kurukshetra, India)and Rohit Bathla (National Institute of Technology, Kurukshetra, India)
Copyright: 2022
Pages: 18
Source title: Advances in Malware and Data-Driven Network Security
Source Author(s)/Editor(s): Brij B. Gupta (National Institute of Technology, Kurukshetra, India)
DOI: 10.4018/978-1-7998-7789-9.ch006

Keywords: Cyber and Network Security / Information Science Reference / Information Security & Privacy / Security & Forensics

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Abstract

Considering the situation when the node which is entering in the network is a malicious node, it can check and record the various operations of the network which could be responsible for some serious security issues. In order to safeguard the network, the author propose an approach which is in view of the advanced encoding strategy, termed as convolution coding approach. According to the requirement of network, the initial bits are assigned, and by applying the convolution technique, the final code is generated for each and every node. Considering the fact that it is a digital method, the codes can be represented by using the binary number system. All the nodes that are a part of the network will be having their corresponding final binary code, say C. The verification of each node is carried out by matching the generated code C with the security code within a particular time period before transmitting the data. This process enables the detection of malicious or attacker node. Furthermore, to enhance the versatility and execution, the system is organized into clusters.

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Malicious Node Detection Using Convolution Technique: Authentication in Wireless Sensor Networks (WSN)

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