The exponential growth of digital data and the escalating sophistication of cyber threats have intensified the demand for secure yet computationally efficient encryption methods. Conventional algorithms (e.g., AES-based schemes) are cryptographically strong and widely deployed; however, some implementations can face performance bottlenecks in large-scale or real-time workloads. While many modern systems seed from hardware entropy sources and employ standardized cryptographic PRNGs/DRBGs, security can still be degraded in practice by weak entropy initialization, misconfiguration, or the use of non-cryptographic deterministic generators in certain environments. To address these gaps, this study introduces FileCipher. This novel file-encryption framework integrates a chaos-enhanced Cryptographically Secure Pseudorandom Number Generator (CPRNG) based on the State-Based Tent Map (SBTM). The proposed design achieves a balanced trade-off between security and efficiency through dynamic key generation, adaptive block reshaping, and structured confusion–diffusion processes. The SBTM-driven CPRNG introduces adaptive seeding and multi-key feedback, ensuring high entropy and sensitivity to initial conditions. A multi-threaded Java implementation demonstrates approximately 60% reduction in encryption time compared with AES-CBC, validating FileCipher’s scalability in parallel execution environments. Statistical evaluations using NIST SP 800-22, SP 800-90B, Dieharder, and TestU01 confirm superior randomness with over 99% pass rates, while Avalanche Effect analysis indicates bit-change ratios near 50%, proving strong diffusion characteristics. The results highlight FileCipher’s novelty in combining nonlinear chaotic dynamics with lightweight parallel architecture, offering a robust, platform-independent solution for secure data storage and transmission. Ultimately, this paper contributes a reproducible, entropy-stable, and high-performance cryptographic mechanism that redefines the efficiency–security balance in modern encryption systems.
Sanjalawe et al. (Mon,) studied this question.