Abstract
Wireless Sensor Networks (WSNs) comprises tiny sensor nodes which have been used for various applications such as Health Monitoring, Forest Fire Detection, Data Collection, Temperature Sensing, Military Application, and Security applications. Among the applications, Security in WSNs is the most challenging one because faulty information can be easily injected into the network by the intruder/attacker. Faulty information injection at the sink level may reduce the lifetime of the network and also energy wastage due to the difficulty in updating information with Base Station (BS). Two algorithms are proposed to detect and drop the false data such as Prevention of False Data Injection using Advanced Encryption Standard (PFDIAES) and Prevention of False Data Injection with Fuzzy-based method (PFDIF). The proposed improved energy-efficient faulty information extraction using PFDIF and PFDIAES algorithms is used to filter and prevent false data at the destination node. To analyze the performance of the network in critical condition, the gang attack is also considered. From the simulation results, PFDIAES has an average energy efficiency value of 1.7% and PFDIF has 5.5% of energy efficiency than the existing algorithms such as AES and FUZZY-based method.
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Kalaivaani, P.T., Krishnamoorthy, R. (2020). An Improved Energy-Efficient Faulty Information Extraction Scheme Using PFDIAES and PFDIF Algorithms. In: Pant, M., Kumar Sharma, T., Arya, R., Sahana, B., Zolfagharinia, H. (eds) Soft Computing: Theories and Applications. Advances in Intelligent Systems and Computing, vol 1154. Springer, Singapore. https://doi.org/10.1007/978-981-15-4032-5_79
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DOI: https://doi.org/10.1007/978-981-15-4032-5_79
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