A Secure and Energy-Efficient Framework for Environmental Monitoring Data Using Laplace Transform–Based Encryption

Abstract

Recent years, environmental monitoring systems have become increasingly dependent on continuous data acquisition from distributed sensor networks to evaluate air quality, water pollution, and climate-related parameters. The reliability of such assessments strongly depends on the security and integrity of the collected data. However, environmental monitoring infrastructures often operate in open and resource-constrained environments, making transmitted data vulnerable to interception and manipulation.
The present study introduces a secure and computationally efficient framework for protecting environmental monitoring data using Laplace Transform–based encryption and inverse Laplace Transform–based decryption. The proposed approach preserves data confidentiality while maintaining low computational overhead, which is essential for long-term and real-time environmental monitoring applications. Performance analysis indicates that the framework achieves secure transmission with minimal processing delay, making it suitable for sustainable environmental data management.