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ISSN Approved Journal No: 2320-2882 | Impact factor: 7.97 | ESTD Year: 2013
Call For Paper - Volume 14 | Issue 3 | Month- March 2026
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Published Paper Details:
Paper Title
Malicious Data Injection Detection And Prediction In Wireless Sensor Network Using Improved Swarm Intelligence
Authors
Parlapalli Sulochana, Dr. P. Abdul Khayum, Kotekallu Pallavi, Rupanagudi Suniya Kumari
Keywords
WSN, Malicious Data Injection Detection, Prediction, Improved Particle Swarm Intelligence (IPSO).
Abstract
Due to their weakness, wireless sensor networks (WSNs) may be subject to detrimental effects both physically and remotely. Stated differently, a great deal of applications requiring wireless sensor networks require security. Sensor measurements are used to locate events such as floods and fires. Wireless sensor networks are vulnerable, so it is important to protect the network by detecting when fake data is entered. An algorithm to identify and eliminate malicious network traffic has been developed. The suggested Improved Particle Swarm Intelligence (IPSO) method is applied to multiple datasets in order to assess its performance. A simulator is used to test the algorithm. The study and simulation results show how to identify and remove malicious data from wireless sensor networks. In this project, the simulation of a data injection attack in a WSN achieved an accuracy of 95% using MATLAB.
IJCRT's Publication Details
Unique Identification Number - IJCRT25A4459
Paper ID - 283630
Page Number(s) - m474-m480
Pubished in - Volume 13 | Issue 4 | April 2025
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Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882
E-ISSN Number - 2320-2882
Cite this article
Parlapalli Sulochana, Dr. P. Abdul Khayum, Kotekallu Pallavi, Rupanagudi Suniya Kumari, "Malicious Data Injection Detection And Prediction In Wireless Sensor Network Using Improved Swarm Intelligence", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.13, Issue 4, pp.m474-m480, April 2025, Available at :http://www.ijcrt.org/papers/IJCRT25A4459.pdf
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Volume 14 | Issue 3
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Submit Manuscript Online Impact Factor: 7.97 Review Results : Within 02-03 Days Paper Publication : Within 02-03 Days
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ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
ISSN and 7.97 Impact Factor Details
ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
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