Malicious Data Injection Detection and Prediction in Wireless Sensor Network using Optimized Swarm Intelligence
Objective
This project aims to contribute to the security and reliability of Wireless Sensor Networks, making them more resilient to malicious data injection attacks while maintaining efficient resource utilization through optimized swarm intelligence techniques
Abstract
Wireless sensor networks (WSNs) are weak, meaning that they could be remotely or physically exposed to harmful impacts. In other words, security is essential for many applications involving wireless sensor networks. Events like fires and floods are located using sensor measurements. Due to the vulnerability of wireless sensor networks, it is necessary to safeguard the network by identifying the entry of false data. We have created an algorithm to locate and remove harmful network data. To evaluate the performance of the proposed optimized swarm intelligence algorithm, it is deployed to several datasets. The algorithm is tested with a simulator. The research and simulation findings demonstrate how harmful data in wireless sensor networks can be found and fixed. In this paper we test simulation of data injection attack in WSN and reach the accuracy of 95% using Matlab.
Keywords: WSN, Malicious Data Injection Detection, Prediction, Optimized Swarm Intelligence.
NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.
Block Diagram
Specifications
Software: Matlab 2020a or above
Hardware:
Operating Systems:
- Windows 10
- Windows 7 Service Pack 1
- Windows Server 2019
- Windows Server 2016
Processors:
Minimum: Any Intel or AMD x86-64 processor
Recommended: Any Intel or AMD x86-64 processor with four logical cores and AVX2 instruction set support
Disk:
Minimum: 2.9 GB of HDD space for MATLAB only, 5-8 GB for a typical installation
Recommended: An SSD is recommended A full installation of all MathWorks products may take up to 29 GB of disk space
RAM:
Minimum: 4 GB
Recommended: 8 GB
Learning Outcomes
· Introduction to Matlab
· What is EISPACK & LINPACK
· How to start with MATLAB
· About Matlab language
· Matlab coding skills
· About tools & libraries
· Application Program Interface in Matlab
· About Matlab desktop
· How to use Matlab editor to create M-Files
· Features of Matlab
· Basics on Matlab
· What is Communication?
· About Communication
· Introduction to Communication
· How Communication Works?
· Importing the System Design, Characterization and Visualization
· Analyzing of BER tool
· Analyzing of Error Rate Test Console
· Generation of WSN
· WSN network creation
· Nodes Communication
· Clustering
· Routing
· Convolutional
· Equalization and Synchronization etc.,
· How to extend our work to another real time applications
· Project development Skills
o Problem analyzing skills
o Problem solving skills
o Creativity and imaginary skills
o Programming skills
o Deployment
o Testing skills
o Debugging skills
o Project presentation skills
o Thesis writing skills
Paper Publishing
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Disclaimer - Takeoff Edu Group Projects are not associated or affiliated with IEEE in any way. The IEEE Projects mentioned here are mentioned in the context of student projects, whose ideas are derived from IEEE publications, not projects of or by IEEE.
