Because of their complex behaviour, simple mathematical and digital hardware representation, one-dimensional (1D) chaotic functions were the earliest choices of cryptologists for applying chaos theory to cryptography. It was discovered later that most of these functions suffer from orbits collapsing into a specific period, especially under finite precision realization and weakness because of their limited number of control parameter(s). This in turn exposed many security issues and was proven to be vulnerable to various types of attacks. This paper addresses the issue of limited number of control parameters by introducing a 1D chaotic function with five control parameters (in addition to the initial condition). Analysis of the function implies its chaotic properties in addition to its ability to generate a cryptographically secured random stream of numbers. To further elaborate on its robustness, a new image encryption algorithm incorporating the function as its random number generator is presented. Various analyses of the new scheme confirm it to be secure with good confusion-diffusion properties.

This paper suggests a novel one-dimensional (1D) map to address the limitations of traditional chaotic 1D maps. In contrast to traditional 1D maps, the proposed map has three control parameters a, $\mu$, and c, allowing it to exhibit chaotic behavior over a wide range of values. The dynamic behavior of the new 1D map was analyzed using well-known numerical methods, including the bifurcation diagram and Lyapunov exponent. Both tests showed their complex and diverse behavior. In addition, a novel image encryption scheme was devised using the new function as its pseudorandom number generator. Rigorous statistical testing was applied to the proposed encryption algorithm. The mean square error (MSE) and peak signal-to-noise ratio (PSNR) results, in addition to subjecting 28 images to number of pixels change rate (NPCR) and unified average changing intensity (UACI) tests demonstrated the robustness of the system. The results of this study demonstrate the effectiveness of the new 1D map for use in secure image cryptography applications, providing a more robust and secure alternative to traditional chaotic 1D maps.

One dimensional chaotic maps suffer from limited number of control parameters and converged periodicity, specially under finite precision implementation, making them unsuitable for hardware based ciphering systems. This paper first discusses the limited periodicity of 1D maps under fixed point precision, then, an image encryption algorithm based on DNA encoding and two specially configured binarized chaotic cores is presented. The function of both cores is to perform the confusion and diffusion stages of the image by generating pseudo random numbers with excellent cryptographic properties. DNA encoding adds an extra layer of security to the algorithm by converting both the image and chaotic stream to DNA sequences using specific DNA encoding rule. Initial values of both chaotic cores are image dependent based on a calculated hamming distance. These initial condition and the utilized DNA rules composes the overall secret key of the system with a total length of 336 bits. On the condition that all calculations involved in the scheme are based on binary integer arithmetic, all performed security analysis subjected to the scheme proved the system to withstand known attacks with excellent encryption properties.

The rise of telehealth in smart cities has introduced both opportunities and challenges, particularly in securing sensitive patient data and ensuring reliable authentication. This paper presents a chaos-based dynamic authentication scheme designed to address these challenges. Utilizing the inherent unpredictability and sensitivity of chaotic systems, the proposed method ensures robust protection against various attacks, including replay, brute-force, man-in-the-middle, collision, and parameter prediction. The scheme operates through a dynamic challenge–response mechanism using chaotic maps, which generate highly unpredictable authentication parameters. Simulations demonstrate the system’s strong resilience, minimal collision rate, and adaptability to diverse telehealth devices. By safeguarding sensitive telehealth data and promoting secure access control, this research provides a foundational framework for implementing secure authentication systems in smart cities. Future directions include real-world deployment and integration with advanced technologies like blockchain to further enhance security and scalability.

The severe climate changes due to global warming pushed the world to strive to reduce carbon emissions. And transitioning to renewable energy sources is essential for achieving sustainability and combating climate change. This study aims to minimize the carbon emissions for a proposed smart energy hub. This paper prioritizes the minimization of carbon emissions, considering the minimization of operational running costs, and the maximization of profit. In this paper, two optimization scenarios were studied to compare the results. In the first scenario, the minimization of carbon emissions was achieved. In the second scenario, the minimization of running costs and the maximization of profit from the hub assets were studied. The proposed model was designed in MATLAB. Then, the results were verified by CPLEX and validated by RTDS. The multi-objective model was presented to obtain the optimal operation. The mitigation of data uncertainty was achieved by applying the Kalman filter. In this work, a novel method was proposed for the estimation of the quarter-hour resolution data from the hourly ones via the Kalman filter rather than by applying the classic polynomial interpolation methods.