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In-sensor cryptographic signature generation to link a physical process and an immutable digital entity

Abstract

Data forgery and manipulation can undermine trust in areas ranging from science to journalism. Artificial intelligence will probably exacerbate this problem, degrading our ability to distinguish between artificially created data and real recordings (such as those taken with a video camera). Here we report a recording device technology that establishes a cryptographic link between a physical process (the act of recording) and an immutable digital entity (such as an entry in a public blockchain). Our approach relies on a monolithic cryptographic sensor that integrates a sensor device with a hashing unit (that continuously hashes pieces of recorded data) and a cryptographic signature unit (that signs the hashes using a public key encryption scheme). The system then uploads the signed hashes to a trusted public repository. We provide a proof-of-concept implementation with a voltage sensor for extracellular recording of cardiac myocyte field potentials that is fabricated using 180-nm complementary metal–oxide–semiconductor technology.

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Fig. 1: Overview of the system architecture.
Fig. 2: Details of the proof-of-concept implementation.

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Data availability

Links to the data uploaded to the Sokol blockchain during the proof-of-concept (PoC) implementation can be found in Supplementary Section 3. Other data that support the findings of this study (including the electrophysiological recordings) are available from the corresponding authors upon reasonable request.

References

  1. Rini, R. Deepfakes and the epistemic backstop. Philos. Impr. 20, 1–16 (2020).

    Google Scholar 

  2. Westerlund, M. The emergence of deepfake technology: a review. Technol. Innov. Manag. Rev. 9, 39–52 (2019).

    Article  Google Scholar 

  3. Ienca, M. On artificial intelligence and manipulation. Topoi 42, 833–842 (2023).

    Article  Google Scholar 

  4. Shumailov, I. et al. AI models collapse when trained on recursively generated data. Nature 631, 755–759 (2024).

    Article  Google Scholar 

  5. Naveh, A. & Tromer, E. PhotoProof: cryptographic image authentication for any set of permissible transformations. In 2016 IEEE Symposium on Security and Privacy (SP) 255–271 (IEEE, 2016).

  6. Sedlmeir, J., Rieger, A., Roth, T. & Fridgen, G. Battling disinformation with cryptography. Nat. Mach. Intell. 5, 1056–1057 (2023).

    Article  Google Scholar 

  7. C2PA technical specification. C2PA https://c2pa.org/specifications/specifications/2.0/specs/_attachments/C2PA_Specification.pdf (2024).

  8. Igarashi, T., Kazuhiko, T., Kobayashi, Y., Kuno, H. & Diehl, E. Photrace: a blockchain-based traceability system for photographs on the internet. In 2021 IEEE International Conference on Blockchain (Blockchain) 590–596 (IEEE, 2021).

  9. Garrison, C. & Sorensen, D. Apparatus for authenticated recording and method therefor. US patent 20030204736A1 (2003).

  10. Ghoreishizadeh, S. S. et al. A lightweight cryptographic system for implantable biosensors. In 2014 IEEE Biomedical Circuits and Systems Conference (BioCAS) Proceedings 472–475 (IEEE, 2014).

  11. Myers, C. C. Imaging systems with data encryption and embedding capabilities. US patent 20180097636A1 (2018).

  12. Shao, B. et al. Highly trustworthy in-sensor cryptography for image encryption and authentication. ACS Nano 17, 10291–10299 (2023).

    Article  Google Scholar 

  13. Suh, G.E. & Devadas, S. Physical unclonable functions for device authentication and secret key generation. In 2007 44th ACM/IEEE Design Automation Conference 9–14 (IEEE, 2007).

  14. Cardes, F., Baladari, N., Lee, J. & Hierlemann, A. A low-power opamp-less second-order delta-sigma modulator for bioelectrical signals in 0.18 µm CMOS. Sensors 21, 6456 (2021).

    Article  Google Scholar 

  15. Munjal, K. & Bhatia, R. A systematic review of homomorphic encryption and its contributions in healthcare industry. Complex Intell. Syst. 9, 3759–3786 (2023).

    Article  Google Scholar 

  16. Aad, I. in Trends in Data Protection and Encryption Technologies (eds Mulder, V. et al.) 25–30 (Springer Nature, 2023).

Download references

Acknowledgements

This research was supported by ETH Zurich (ETH Postdoctoral Fellowship to F.C.); the Swiss National Science Foundation (SNSF) through project no. 205320_188910 (to A.H.); the State Secretariat for Education, Research and Innovation (SBFI) through the SwissChips initiative (to A.H.); the Swiss National Science Foundation (SNSF) Eccellenza Grant (grant no. PCEFP3_187001 to F.F.); Projects in Life Sciences Grant (grant no. 310030_220209 to F.F.); and an SNSF Spark Grant (grant no. CRSK-3_220987 to F.F.). We thank N. Baladari (ETH Zurich and TU Delft) for help with analogue-to-digital converter (ADC) design, P. Rimpf (Cleanroom Facility Basel, ETH Zurich) for assistance with chip packaging and F.K. Gürkaynak and B. Muheim Bachl (Microelectronics Design Center, ETH Zurich) for valuable discussions.

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Authors and Affiliations

Authors

Contributions

F.C., S.B. and F.F. conceived the project. F.F. and A.H. supervised the project. F.F., F.C. and X.Y. developed the algorithm and implemented the software. F.C., X.Y., R.B. and V.V. built the prototype. F.C. and J.L. performed the experiments. Q.Y. and S.B. implemented the verification software in Solidity. A.R. performed the power, area and overhead estimation analysis. F.F. and F.C. wrote the paper. A.H., A.R. and S.B. edited the paper.

Corresponding authors

Correspondence to Fernando Cardes or Felix Franke.

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Competing interests

F.C., X.Y., R.B. and F.F. are inventors in a European patent application filed by ETH Zurich (application no. EP25164337.5). The patent application covers certain possible implementations of the monolithic cryptographic sensor discussed in the manuscript. The other authors declare no competing interests.

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Nature Electronics thanks Soumyajit Mandal and Fei Zhuge for their contribution to the peer review of this work.

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Supplementary Sections 1–4, Figs. 1 and 2 and Tables 1 and 2.

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Cardes, F., Bürgel, S., Yuan, X. et al. In-sensor cryptographic signature generation to link a physical process and an immutable digital entity. Nat Electron (2026). https://doi.org/10.1038/s41928-026-01593-5

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