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Strong Known Related-Key Attacks and the Security of ECDSA

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Network and System Security (NSS 2019)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 11928))

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Abstract

The classical related-key attack (RKA) model fails to capture some real world systems that introduce related secret keys by design. In some blockchain applications, public keys are generated in a way that the corresponding secret keys are additively related. The difference between two secret keys are known to some third parties. In this paper, we propose the Strong Known Related-Key Attack (Strong KRKA) model to capture this scenario.

ECDSA has long been considered to be inferior to Schnorr signature in terms of security, in sprite of its popularity in the standardization and real world usage. In this paper we show that Schnorr signature is not secure in the Strong KRKA model. In contrast, the security of ECDSA in the Strong KRKA model can be reduced to the unforgeability of ECDSA under chosen message attack. This theoretical result gives a different view of the relative security level of ECDSA and Schnorr, since ECDSA was developed in 1992.

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Notes

  1. 1.

    https://bitcointalk.org/index.php?topic=5965.0.

  2. 2.

    CryptoNote v 2.0 Whitepaper. https://cryptonote.org/whitepaper.pdf.

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Acknowledgment

This project is partially supported by the grant of the University of Hong Kong (Project No. 201901159007), and the CRF grant (CityU: C1008-16G) of the Government of HKSAR, Hong Kong.

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Authors and Affiliations

  1. The University of Hong Kong, Pok Fu Lam, Hong Kong

    Tsz Hon Yuen & Siu-Ming Yiu

Authors
  1. Tsz Hon Yuen
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  2. Siu-Ming Yiu
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Correspondence to Tsz Hon Yuen .

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Editors and Affiliations

  1. Monash University, Clayton, VIC, Australia

    Joseph K. Liu

  2. Fujian Normal University, Fuzhou, China

    Xinyi Huang

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Yuen, T.H., Yiu, SM. (2019). Strong Known Related-Key Attacks and the Security of ECDSA. In: Liu, J., Huang, X. (eds) Network and System Security. NSS 2019. Lecture Notes in Computer Science(), vol 11928. Springer, Cham. https://doi.org/10.1007/978-3-030-36938-5_8

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  • DOI: https://doi.org/10.1007/978-3-030-36938-5_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-36937-8

  • Online ISBN: 978-3-030-36938-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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