Modeling the interplay of information security and computing costs in embedded devices

Abstract

The article proposes a mathematical model that describes the interplay of information security and computing costs in embedded devices. Embedded systems, such as IoT devices, medical devices, and industrial controllers, operate under limited computing resources, which poses significant challenges to ensuring an adequate level of information security without overloading the system. The proposed model takes into account key parameters, including power consumption, processing time, memory size, and cryptographic protection level, which allows exploring the balance between security and resource consumption. The effectiveness of lightweight – PRESENT, SPECK, SIMON and standard cryptographic algorithms – Blowfish, AES were analyzed. The results of simulations performed in MATLAB and Python environments using libraries for cryptography testing demonstrate that lightweight algorithms provide significantly lower power consumption and processing time. This makes them an optimal choice for devices with limited resources. In particular, the SPECK and PRESENT algorithms showed the best results in terms of power consumption and speed, while AES, although providing a high level of security, is more resource-intensive. The practical significance of the developed model lies in its application for selecting optimal cryptographic solutions when designing energy-efficient embedded systems. The model can be integrated into design processes to optimize the security and performance of devices, which is especially important for IoT architectures, where energy conservation and data security are critical