Experimental Evaluation of a Secured Privacy Preservation Scheme using IP Traceback Logic in Wireless Sensor Networks

This research work proposes a secured privacy preservation scheme for wireless sensor networks (WSNs) that integrates multiple advanced techniques to ensure robust data confidentiality, integrity, and traceability. The methodology encompasses secure network initialization, symmetric key cryptography for data encryption and decryption, probabilistic packet marking for IP traceback, and secure routing protocols. Additionally, the scheme employs privacy-preserving data aggregation methods and an intrusion detection system (IDS) enhanced by machine learning for real-time threat detection and mitigation. The combination of these techniques addresses the critical security challenges in WSNs, making the model particularly suitable for sensitive applications such as military operations, healthcare, and critical infrastructure monitoring. A key feature of the proposed model is its superior performance, with encryption and decryption times of 1 ms and 0.9 ms respectively, which are significantly better than those of existing models. This comprehensive approach ensures that the WSN remains secure and reliable, even in the face of evolving cybersecurity threats.