Encryption of sensor data using the Lorentz attractor in embedded systems

The increasing threat of cyber-attacks and the need to protect embedded system data require the development of energy-efficient cryptographic methods. The subject matter of this article is the development of an energy-efficient data encryption method for embedded systems using chaotic systems, specifically the Lorenz system. The goal of this study was to create a data encryption method for embedded systems with limited computing resources. The tasks included developing an algorithm based on the properties of the chaotic Lorenz system, implementing it on microcontrollers and programmable logic circuits, and testing its performance under near-real operational conditions. The methods used involved leveraging the high sensitivity of chaotic systems to initial conditions, implementing the encryption algorithm in hardware, and evaluating key performance indicators, such as speed, power consumption, memory usage, and resistance to cryptographic attacks. The results showed that the proposed algorithm reduces memory and energy consumption by 37% and 10%, respectively, compared to conventional methods, providing an encryption speed of 120 milliseconds per kilobyte of data. Tests have confirmed that even minimal changes in the initial parameters of a chaotic system led to a change of up to 90% of the bits in the encrypted data, which increases the algorithm’s robustness. The proposed method is compatible with various types of data and shows versatility for information protection. The algorithm has demonstrated efficiency in processing text arrays and sensory data, making it suitable for use in smart cities, medical devices, and industrial networks. The key entropy value was 7.95 bits per byte, indicating high encryption reliability. In conclusion, the results obtained prove that the proposed method is promising for use in conditions of limited resources and can be integrated with modern information security technologies.