# Energy Consumption Framework and Analysis of Post-Quantum Key-Generation on Embedded Devices
## 2 Related Literature
### Energy Efficiency in PQC  
This section reviews studies on the energy efficiency of post-quantum cryptography (PQC) algorithms, especially within Transport Layer Security (TLS) and resource-constrained devices. [PERSON] et al. [36] analysed the integration of quantum-resistant cryptography into TLS. Their benchmarking quantified computational and data transfer overheads, revealing the feasibility of PQC in web communication, though some algorithms increased the overall network traffic due to larger key sizes and overheads. Notably, the lattice-based techniques showed comparable results to classical methods, suggesting deployment of PQC is practical with the careful selection of algorithms (e.g., NIST standardisation efforts).  
[PERSON] et al. [37] also examined PQC integration into TLS, specifically focusing on constrained environments (similarly to this study) and highlighting the inherent challenges. This pre-NIST standardisation work indicated potential additional PQC overheads (latency, computation, traffic) that vary with security level, compared to low-power classical cryptographic methods.  
[PERSON] et al. [12], also pre-NIST but evaluating many of its candidates, verified the resource utilisation of a complete TLS 1.3 implementation, and provided a valuable point of reference when validating the results of this paper. They found that PQC could be implemented in resource-limited settings, the with lattice-based Kyber showing favourable performance. However, some other algorithms were less energy-efficient than the classical alternatives, emphasising the importance of appropriate algorithm selection during implementation.  
[PERSON] et al. [38] specifically examined the energy costs of PQC Key Exchange Mechanisms (KEMs) in TLS-based low-power IoT devices. Their findings reinforced the significant energy cost variations among PQC techniques, reiterating the importance of selecting appropriate algorithms to minimise power consumption, based on both security needs and environmental constraints.  
Finally, [PERSON] et al. [39]'s analysis of PQC energy efficiency in mobile and large-scale environments showed performance variations based on vastly different architectures, but again highlighted the energy efficiency of lattice-based techniques. They concluded that algorithm selection should depend on specific requirements and platform characteristics, noting the increased significance of energy costs at scale and the impact on battery life in portable applications.  
In summary, these studies collectively demonstrated the feasibility of integrating PQC in low-power devices, but consistently emphasised the need for careful algorithm and parameter selection. This is particularly the case in resource-constrained environments, to manage trade-offs in computation, memory, data transfer, and energy. Lattice-based techniques often appear efficient, aligning with early NIST selections. However, non-PQC algorithms may remain a valid choice when the implementation platform does not support post-quantum cryptography or where confidentiality or integrity are not deemed to be critical concerns and the platform can be de-prioritised based on risk.  
The following section details the methodology for researching the energy efficiency of key generation algorithms on the target hardware platform.