Secure Data Management Via Lightweight Cryptographic Frameworks : A Comparative Study of ChaCha20 for Encryption and SHA-256 for Hashing Secure Using a Big Data

Abstract

With the advent of large-scale data applications, the security and efficiency of cryptographic systems have become two critical concerns. In this paper we present a cryptographic solution that combines the ChaCha20 encryption algorithm and SHA-256 hashing to provide data confidentiality and integrity. The system works on data in chunks to optimize for memory usage and scaling from 10 MB to 1 GB datasets. While achieving low resource utilization (CPU usage < 12% and a memory footprint < 50 MB) the proposed technique achieves cipher and decipher rates up to 88 MB/s with significant performance gain. SHA-256 based integrity verification achieved 100% accuracy, preventing tampering and corruption. The comparison with conventional systems (e.g., AES, MD5) reflected the superiority of the proposed system in various factors (i.e., speed, resource efficiency, and robustness). The system also proved capable of supporting large datasets through scalability testing, enabling uses in cloud storage, IoT security, and secure communications. These findings highlight the proposed system's ability as a lightweight and scalable cryptographic solution to meet the data security demands of the advanced digital era. With the rise of IoT and cloud computing, traditional encryption like AES struggles with high memory usage in resource-constrained devices. This paper proposes a lightweight framework combining ChaCha20 (for encryption) and SHA-256 (for integrity), optimized for big data. Our chunk-based approach achieves 88 MB/s throughput with <12% CPU usage, outperforming AES in software environments. Experimental results on datasets up to 1GB demonstrate 100% tamper detection accuracy, making it ideal for IoT and real-time applications