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Lattice Cryptalization and Cybersecurity: New Findings in Analyzing Cryptovalues Dynamics

In: Mathematical and Statistical Methods for Actuarial Sciences and Finance

Author

Listed:
  • Domenica Stefania Merenda

    (University “Mediterranea” of Reggio Calabria, Department of Law, Economics and Human Sciences and Decisions_Lab)

  • Massimiliano Ferrara

    (University “Mediterranea” of Reggio Calabria, Department of Law, Economics and Human Sciences and Decisions_Lab
    ICRIOS-The Invernizzi Centre for Research in Innovation, Organization, Strategy and Entrepreneurship Bocconi University, Department of Management and Technology)

Abstract

RSA-based scheme are the most popular asymmetric cryptosystems to date, being deployed in billions of security systems and applications. This RSA cryptosystem comprises of two important features that are needed for encryption process known as the public parameter and the modulus. Such constructions are extensively used in financial applications such as Bitcoins, where more than one key is required in order to authorize Bitcoin transactions. Many of the current state-of-the-art schemes are based on the RSA assumptions, however this may be-come insecure in the future, for example due to the possibility of quantum attacks. In this paper we propose a scheme based on recent theoretical advances in lattice-based cryptography. Over the last years lattice-based cryptography has received much attention as it is a very versatile tool in different fields. In this work we explore the implementations of cryptographic systems presenting geometric considerations for an application approach to the financial sector, in particular emphasizing the feasibility of the special algebraic structure of ideal lattice on the spread of “cryptocurrencies” (or “virtual currencies”), the best known of which is bitcoin.

Suggested Citation

  • Domenica Stefania Merenda & Massimiliano Ferrara, 2022. "Lattice Cryptalization and Cybersecurity: New Findings in Analyzing Cryptovalues Dynamics," Springer Books, in: Marco Corazza & Cira Perna & Claudio Pizzi & Marilena Sibillo (ed.), Mathematical and Statistical Methods for Actuarial Sciences and Finance, pages 353-358, Springer.
    • Handle: RePEc:spr:sprchp:978-3-030-99638-3_57
    DOI: 10.1007/978-3-030-99638-3_57
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