Can it run PQC? Simulating embedded use cases to identify bottlenecks

The emergence of quantum computing poses a significant threat to traditional public-

key cryptosystems, making the rapid adoption of post-quantum cryptography (PQC)

essential for maintaining digital security. This transition is especially challenging for

the Internet of Things and embedded systems because they have limited computational

power, memory, and energy. Due to the vast design space of algorithms, platforms,

and network conditions, manual benchmarking is infeasible. Thus, this thesis presents

a novel, modular simulation framework for identifying PQC-induced bottlenecks in

embedded environments. By integrating structured use case descriptions with data-

driven performance models derived from hardware benchmarks, the framework enables

a systematic evaluation of multiple dimensions, including computation, memory usage,

energy consumption, and communication overhead. The tool’s functionality is evaluated

through case studies such as a TLS handshake, secure boot, and Over-the-Air update.

The results indicate that there is no universal PQC solution. Instead, the suitability of

an algorithm depends heavily on specific constraints, such as flash storage limits for

certain implementations or network-induced latency in low-bandwidth environments.

Evaluation against real hardware benchmarks confirms that the simulation accurately

captures performance trends and identifies critical trade-offs. The framework provides a

scalable, practical tool for designing future secure embedded systems.