Improved Big Data Security Using Quantum Chaotic Map of Key Sequence - Kotangale, Archana; Kumar, Meesala Sudhir; Bhagat, Amol P. (Computers (Basel), 2025)
In the era of ubiquitous big data, ensuring secure storage, transmission, and processing has become a paramount concern. Classical cryptographic methods face increasing vulnerabilities in the face of quantum computing advancements. This research proposes an enhanced big data security framework integrating a quantum chaotic map of key sequence (QCMKS), which synergizes the principles of quantum mechanics and chaos theory to generate highly unpredictable and non-repetitive key sequences. The system incorporates quantum random number generation (QRNG) for true entropy sources, quantum key distribution (QKD) for secure key exchange immune to eavesdropping, and quantum error correction (QEC) to maintain integrity against quantum noise. Additionally, quantum optical elements transformation (QOET) is employed to implement state transformations on photonic qubits, ensuring robustness during transmission across quantum networks. The integration of QCMKS with QRNG, QKD, QEC, and QOET significantly enhances the confidentiality, integrity, and availability of big data systems, laying the groundwork for a quantum-resilient data security paradigm. While the proposed framework demonstrates strong theoretical potential for improving big data security, its practical robustness and performance are subject to current quantum hardware limitations, noise sensitivity, and integration complexities.