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

Authors

  • Throvagunta Srinija B.TECH Student, Department of Computer Science and Engineering [CSO], Raghu Engineering College, Visakhapatnam, India Author
  • Potnuru Asrith B.TECH Student, Department of Computer Science and Engineering [CSO], Raghu Engineering College, Visakhapatnam, India Author
  • Dandu Mohan Pavan Satyanarayana Raju B.TECH Student, Department of Computer Science and Engineering [CSO], Raghu Engineering College, Visakhapatnam, India Author
  • Bora Balaji Basanth B.TECH Student, Department of Computer Science and Engineering [CSO], Raghu Engineering College, Visakhapatnam, India Author
  • Krishnardhula Pavan Kumar M.TECH [Ph. D] and Guide, Department of Computer Science and Engineering [CSO], Raghu Engineering College, Visakhapatnam, India Author

Keywords:

WSN, Malicious Data Injection Detection, Prediction, Improved Swarm Intelligence

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.

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Published

16-04-2024

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Section

Research Articles

How to Cite

Malicious Data Injection Detection and Prediction in Wireless Sensor Network Using Improved Swarm Intelligence. (2024). International Journal of Scientific Research in Science and Technology, 11(2), 608-619. https://ijsrst.com/index.php/home/article/view/IJSRST24112112

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