Design and Evaluation of a Secure Data Communication Framework Using Hybrid Cryptography Techniques for Privacy Protection

Abstract

In the modern digital era, the rapid growth of interconnected systems, cloud platforms, and Internet of Things (IoT) environments has significantly increased the risk of unauthorized data access and privacy breaches. Traditional cryptographic approaches, which rely on fixed combinations of symmetric and asymmetric algorithms, often fail to adapt to dynamic security requirements and emerging threats such as quantum-based attacks. To address these limitations, this paper proposes an Adaptive Triple Hybrid Cryptographic Framework that integrates Advanced Encryption Standard (AES), Elliptic Curve Cryptography (ECC), and a Post-Quantum Cryptographic (PQC) layer within a unified, privacy-aware architecture. The framework dynamically selects appropriate encryption strategies based on data sensitivity, system constraints, and communication context, thereby optimizing both security and performance. In addition, a privacy-aware data protection module is introduced to ensure minimal exposure of sensitive information during transmission and processing. The proposed system is evaluated in terms of encryption time, key security strength, computational efficiency, and resistance to modern cyber threats. Experimental results demonstrate that the proposed framework achieves enhanced security robustness while maintaining acceptable computational overhead when compared to conventional hybrid cryptographic models. The findings highlight the effectiveness of adaptive, multi-layered cryptographic systems in achieving secure and privacy-preserving data communication, making the proposed framework suitable for next-generation secure communication environments.