Encryption is crucial for smart city sensor data: It protects the confidentiality of the data collected by a vast array of sensors embedded throughout the city, such as those monitoring traffic, environmental conditions, utilities, and public safety. This data often includes sensitive information that could compromise individual privacy or city operations if accessed by unauthorized parties.

In addition, encryption can also ensure the integrity of the data, preventing unauthorized alterations that could lead to misinformation or manipulation of smart city systems. This is particularly important as tampering with sensor data could have severe consequencunles, such as disrupting traffic flow, causing malfunctions in public services, or hampering emergency response efforts.

Stream ciphers are ideal for encrypting smart city sensor data due to their ability to efficiently handle real-time data processing with minimal latency and computational overhead. These ciphers encrypt data on-the-fly, making them perfect for the continuous data streams generated by smart city sensors. Unlike block ciphers, stream ciphers do not require fixed-size blocks or data padding, allowing them to seamlessly handle diverse data sizes and formats typical in a smart city environment. Another often underestimated advantage of stream ciphers is that they – unlike block ciphers – do not require a mode of operation (which entails additional computational overhead and may introduce its own security issues). This flexibility enables security across a network of heterogeneous devices, safeguarding the confidentiality and integrity of information vital for applications ranging from traffic management to environmental monitoring.

Our contributions in this work are:

• We realised software-implementations of the recently published Lightweight Stream Cipher DRACO (Hamann et al., 2022) in two different programing languages (C++ and Rust), targeted at microcontrollers.
• Based on these implementations we conducted experiments on different types of resource-constrained Arduino/Raspberry nodes with random as well as real-word smart city sensor data, yielding numerous results.

To the best of our knowledge, our work presents the first performance analysis of the DRACO stream cipher implemented in Rust and C++ on microcontrollers.

We conducted a multitude of experiments on three microcontrollers: ESP32, ESP8266, and Raspberry Pi Pico. The ESP32 and ESP8266 are Wi-Fi-enabled microcontrollers often used in smart cities for applications like smart street lighting, air quality monitoring, and smart parking, while the Raspberry Pi Pico is usually used for local control tasks and sensor data acquisition, often in combination with other devices like the ESP32 for IoT solutions.

Our experiments measure the runtime performance of our two DRACO implementations (one implemented in C++, one implemented in Rust) on these resource-constrained devices. We benchmarked the performance of these implementations on the different microcontrollers for random data of various sizes as well as for more than 700 real-world smart city sensor measurements of various types (e.g. temperature, power units, volume flow rate) from cooling systems (valves, pumps, refrigeration units).