Malicious Data Injection Detection and Prediction in Wireless Sensor Network Using Improved Swarm Intelligence

Throvagunta Srinija, Potnuru Asrith, Dandu Mohan Pavan Satyanarayana Raju, Bora Balaji Basanth and Krishnardhula Pavan Kumar

International Journal of Scientific Research in Science and Technology, 2024, vol. 11, issue 2, 608-619

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's 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 swarm intelligence 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.

Keywords: WSN; Malicious Data Injection Detection; Prediction; Improved Swarm Intelligence (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:etm:ijsrst:v11:y2024:i2:id:107

DOI: 10.32628/IJSRST24112112

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