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

Author

Listed:
  • Throvagunta Srinija
  • Potnuru Asrith
  • Dandu Mohan Pavan Satyanarayana Raju
  • Bora Balaji Basanth
  • Krishnardhula Pavan Kumar

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.

Suggested Citation

  • Throvagunta Srinija & Potnuru Asrith & Dandu Mohan Pavan Satyanarayana Raju & Bora Balaji Basanth & Krishnardhula Pavan Kumar, 2024. "Malicious Data Injection Detection and Prediction in Wireless Sensor Network Using Improved Swarm Intelligence," International Journal of Scientific Research in Science and Technology, Technoscience Academy, vol. 11(2), pages 608-619, April.
    • Handle: RePEc:etm:ijsrst:v11:y2024:i2:id:107
    DOI: 10.32628/IJSRST24112112
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