Performance-Security Tradeoff of Multi-Dimensional Chaotic Maps for Resource-Constrained Environments

In today’s interconnected world, resource-limited devices are crucial across various sectors but face significant security challenges due to limited computational resources. Ensuring the security of these devices is crucial to protect against unauthorized access, data breaches, and other cyber threats. Traditional cryptographic approaches may lead to performance bottlenecks and excessive energy consumption, rendering them unsuitable for practical deployment in these devices. To address this, lightweight encryption algorithms are essential to balance security and efficiency. This study explores encryption methods tailored for these devices, using chaos theory principles to develop novel techniques. This study utilizes multidimensional chaotic maps (1D, 2D, 3D, 4D) to generate encryption keys and secure data transmission. This research analyzes security and performance to find a balance between them as dimension increases. This study finds that end-to-end time and memory consumption rise with higher dimensions, enhancing security through uniform pixel distribution in encrypted images, increased key sensitivity, resistance to differential attacks, decreased peak signal-to-noise ratio, and lower pixel correlation. Although entropy and contrast values do not significantly improve, higher values are observed. The research findings indicate that higher dimensions enhance both security and performance, providing insights for optimizing lightweight encryption schemes to meet specific application needs. Through rigorous experimentation, we conclude that the optimal dimension can be selected based on application requirements, effectively balancing security and performance.