ai-eldorado/ML-KEM-SideChannel-Traces

ML-KEM Side Channel Traces

Dataset Description

This dataset contains power traces captured from the Post-Quantum Cryptography (PQC) ML-KEM implementation of the PQM4[1] library (commit: a24bb4b), running on an STM32 Nucleo-L4R5ZI development board equipped with an ARM Cortex-M4 processor.

The traces were collected using a Rohde & Schwarz RTC1002 100 MHz digital oscilloscope. The purpose of this dataset is to evaluate the ML-KEM implementation for side-channel leakage using the Test Vector Leakage Assessment (TVLA) methodology[2].

To perform the analysis, power traces were collected from two groups representing different operating conditions. The first group, referred to as the FIXED group, consists of traces from 1,000 decapsulation operations performed using the same secret key and ciphertext. The second group, referred to as the RANDOM group, consists of traces from 1,000 decapsulation operations performed using the same secret key while varying the ciphertext.

The trace collection was restricted to a specific function involved in message decoding of the decapsulation procedure: DecodeMessage (poly_tomsg()).

The experiments were performed using the ML-KEM-768 parameter set (k = 3).

Dataset Structure

Format: CSV Size: 2x1000 traces (FIXED and RANDOM sets), with more than 158k samples each

Usage

This dataset can be used for:

• Side-channel attack evaluation
• Machine learning-based leakage analysis
• Benchmarking SCA methodologies

License

cc-by-4.0

Citation

If you use this dataset, please cite:

@inproceedings{moia2026implattacks, title={Implementation Attacks on ML-KEM: Analysis, Practical Assessment, and Recommendations}, author={Moia, Vitor Hugo Galhardo and Novaes, Kevin Pires and Rossetto, Vinicius de Paula}, booktitle={Simp{'o}sio Brasileiro de Seguran{\c{c}}a da Informa{\c{c}}{~a}o e de Sistemas Computacionais (SBSeg)}, year={2026}, organization={SBC} }

Acknowledgment

This work has been totally funded by the project PQC Optimization for Critical Infrastructures supported by Centro Integrado de Segurança em Sistemas Avançados (CISSA), with financial resources from the PPI IoT/Manufatura 4.0 of the MCTI grant number 08/2-24, signed with EMBRAPII.

References

[1] Kannwischer, M. J., Rijneveld, J., Schwabe, P., and Stoffelen, K. (2019). Pqm4: Post- quantum crypto library for the arm cortex-m4. Available at: https://github.com/mupq/pqm4. Accessed: July. 12, 2026;

[2] Gilbert Goodwill, B. J., Jaffe, J., Rohatgi, P., et al. (2011). A testing methodology for side-channel resistance validation. In NIST non-invasive attack testing workshop, volume 7, pages 115–136.