This paper investigates the crucial challenges associated with secure and efficient data fusion techniques in wireless sensor networks (WSNs). With the rapid expansion of WSN applications, ensuring the integrity, confidentiality, and reliability of data fusion processes has become increasingly important. The paper presents a comprehensive overview of existing data fusion techniques and discusses their limitations in terms of security and efficiency. It proposes a novel framework that combines cryptographic mechanisms with optimized algorithms to enhance the overall performance of WSNs. The framework is designed to address the trade-off between security and efficiency, ensuring that sensitive data is protected while minimizing the communication overhead. Simulation results demonstrate that the proposed framework achieves better fusion accuracy, reduced latency, and improved energy efficiency compared to the state-of-the-art methods. Furthermore, a case study is conducted to evaluate the practicality of the framework in real-world scenarios.
Johnson, S. Secure and Efficient Data Fusion Techniques in Wireless Sensor Networks. Information Sciences and Technological Innovations, 2023, 5, 43. https://doi.org/10.69610/j.isti.20230922
AMA Style
Johnson S. Secure and Efficient Data Fusion Techniques in Wireless Sensor Networks. Information Sciences and Technological Innovations; 2023, 5(2):43. https://doi.org/10.69610/j.isti.20230922
Chicago/Turabian Style
Johnson, Sophia 2023. "Secure and Efficient Data Fusion Techniques in Wireless Sensor Networks" Information Sciences and Technological Innovations 5, no.2:43. https://doi.org/10.69610/j.isti.20230922
APA style
Johnson, S. (2023). Secure and Efficient Data Fusion Techniques in Wireless Sensor Networks. Information Sciences and Technological Innovations, 5(2), 43. https://doi.org/10.69610/j.isti.20230922
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References
Burbules, N. C., & Callister, T. A. (2000). Watch IT: The Risks and Promises of Information Technologies for Education. Westview Press.
Saha, S. K., Das, S. K., & Subudhi, B. (2006). A survey on secure data aggregation in wireless sensor networks. IEEE Communications Surveys & Tutorials, 8(1), 48-63.
Bar-Shalom, Y., Li, X. R., & Kirubarajan, T. (2001). Estimation with Applications to Tracking and Navigation: Algorithms, Theory, and Implementation. John Wiley & Sons.
Wang, X., Wang, K., & Zhou, Z. (2009). A robust Kalman filter for motion estimation in presence of outliers. IEEE Transactions on Image Processing, 18(12), 2638-2650.
Chaudhary, A., Bandyopadhyay, S., & Das, S. K. (2011). A survey on data fusion in wireless sensor networks. IEEE Communications Surveys & Tutorials, 13(2), 453-480.
Wang, J., & Wang, Y. (2012). A secure and efficient data aggregation scheme in wireless sensor networks. Journal of Network and Computer Applications, 35(3), 745-753.
Stinson, D. R. (2006). Cryptography: Theory and Practice. Chapman & Hall/CRC.
Khan, M. A., Khan, F. A., & Khan, Z. A. (2010). A secure and energy-efficient data aggregation scheme for wireless sensor networks. International Journal of Distributed Sensor Networks, 2010.
Li, W., Cao, J., & Wang, J. (2013). An adaptive symmetric key cryptography scheme for secure data fusion in wireless sensor networks. IEEE Transactions on Information Forensics and Security, 8(4), 665-678.
Li, W., & Lu, X. (2014). Energy-efficient data aggregation in wireless sensor networks: A survey and new directions. Ad Hoc Networks, 17, 1-18.
He, X., & Ma, J. (2011). A novel clustering-based energy-efficient data aggregation algorithm for wireless sensor networks. International Journal of Distributed Sensor Networks, 2011.