A Model for Enhancing Security and Privacy in Pervasive Computing using Homomorphic Encryption - Egerton, Taylor Onate; Nelson, Davies Isobo (International Journal of Computer Sciences and Engineering, 2025)
Pervasive computing seamlessly integrates computational capabilities into everyday environments, enhancing user experiences while simultaneously exposing systems to critical security and privacy risks. These vulnerabilities such as unauthorized access, data interception, and exploitation of device-level weaknesses demand encryption methods capable of preserving data confidentiality even during active computation. This paper proposed a novel security model built on Fully Homomorphic Encryption (FHE), enabling operations on encrypted information without decryption, thus ensuring privacy during its lifecycle. The model is structured into a four layered architecture comprising of data collection, encryption, encrypted computation (cloud/edge), and decryption. The study utilized Brakerski/Fan-Vercauteren (BFV) scheme and implemented it using Microsoft SEAL library with VB.NET and C++ for secure, exact integer arithmetic. An experimental evaluation was conducted across 10 to 50 simulated devices using synthesized smart environment data. Experimental finding showed developed model achieved a security accuracy of 95.8%, privacy loss of just 0.6%, and a processing overhead of 720ms, confirming its effectiveness and scalability. To further validate the performance of the developed HE model, a detailed comparative analysis was conducted against that of the traditional cryptographic techniques including AES, RSA, and ECC. While the developed HE model incurs higher computational overhead, it outperformed all baseline methods in terms of security accuracy and privacy preservation. Specifically, the developed HE model showed the lowest privacy leakage and highest resistance to unauthorized access, making it more suitable for sensitive applications despite the trade-off in processing speed. The empirical results highlight the model’s strong potential for deployment in real-world domains such as smart cities, healthcare systems, and the Internet of Things (IoT). However, future work should focus on optimizing the model through hybrid FHE–lightweight encryption combinations and integration with real-time IoT protocols.