In recent years, there has been an increasing interest in employing chaotic-based random number generators for cryptographic purposes. However, many of these generators produce sequences that lack the necessary strength for cryptographic systems, such as Tent-Map. However, these generators still suffer from common issues when generating random numbers, including issues related to speed, randomness, lack of statistical properties, and lack of uniformity. Therefore, this paper introduces an efficient pseudo-random number generator, called State-Based Tent-Map (SBTM), based on a modified Tent-Map, which addresses this and other limitations by providing highly robust sequences suitable for cryptographic applications. The proposed generator is specifically designed to generate sequences with exceptional statistical properties and a high degree of security. It utilizes a modified 1D chaotic Tent-Map with enhanced attributes to produce the chaotic sequences. Rigorous randomness testing using the Dieharder test suite confirmed the promising results of the generated keystream bits. The comprehensive evaluation demonstrated that approximately 97.4% of the tests passed successfully, providing further evidence of the SBTM’s capability to produce sequences with sufficient randomness and statistical properties.

Smartphones, digital cameras, and other imaging devices generate vast amounts of high-resolution colored images daily, stored on devices equipped with multi-core central processing units or on the cloud. Safeguarding these images from potential attackers has become a pressing concern. This paper introduces a set of six innovative image ciphers designed to be stronger, faster, and more efficient. Three of these algorithms incorporate the State-Based Tent Map (SBTM) Chaotic Pseudo Random Number Generator (CPRNG), while the remaining three employ a proposed modified variant, SBTMPi. The Grayscale Image Cipher (GIC), Colored Image Cipher Single-Thread RGB (CIC1), and Colored Image Cipher Three-Thread RGB (CIC3) showcase the application of the proposed algorithms. By incorporating novel techniques in the confusion and diffusion phases, these ciphers demonstrate remarkable performance, particularly with large colored images. The study underscores the potential of SBTM-based image ciphers, contributing to the advancement of secure image encryption techniques with robust random number generation capabilities.

This paper focuses on the evolution of ARTMAP architectures, using genetic algorithms, with the objective of improving generalization performance and alleviating the ART category proliferation problem. We refer to the resulting architectures as GFAM, GEAM, and GGAM. We demonstrate through extensive experimentation that evolved ARTMAP architectures exhibit good generalization and are of small size, while consuming reasonable computational effort to produce an optimal or a sub-optimal network. Furthermore, we compare the performance of GFAM, GEAM and GGAM with other competitive ARTMAP architectures that have appeared in the literature and addressed the category proliferation problem in ART. This comparison indicates that GFAM, GEAM and GGAM have superior performance (generalize better, are of smaller size, and require less computations) compared with other competitive ARTMAP architectures.

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.

As our dependency on the digital world increases, our private information becomes widely visible and an easy target. The digital world is never safe and is full of adversaries who are eager to invade our privacy and learn our secrets. Leveraging the great advantages of the digital world must necessarily be accompanied by effective techniques for securing our information. Although many techniques are available, the need for more effective ones is, and will remain, essential. This paper proposes a new, robust and efficient encryption technique. Our technique has an innovative computational model that makes it unique and extremely effective. This computational model offers (1) a fuzzy substitution method augmented with distortion operations that introduce deep changes to their input and (2) a key manipulation method, which produces key echoes whose relationships to the original encryption key are highly broken. These operations work synergistically to provide the highest degree of diffusion and confusion. Experiments on our proof-of-concept prototype showed that the output (cipheredtexts) of our technique passed standard security tests and is therefore highly immune against different attacks.