4.7 Article

Zooming into chaos as a pathway for the creation of a fast, light and reliable cryptosystem

期刊

NONLINEAR DYNAMICS
卷 104, 期 1, 页码 753-764

出版社

SPRINGER
DOI: 10.1007/s11071-021-06280-y

关键词

Chaos; Ergodic theory; Chaos-based cryptography; Information theory

资金

  1. National Council for Scientific and Technological Development (CNPq) [155957/2018-0]
  2. Sao Paulo Research Foundation (FAPESP) [2020/03514-9]
  3. CNPq [307897/2018-4]
  4. FAPESP [16/18809-9]
  5. Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP) [16/18809-9] Funding Source: FAPESP

向作者/读者索取更多资源

This paper introduces a method for generating PRNs with low correlation using chaotic maps, enhancing the security of the cryptosystem with minimal computational cost. By applying transformations to chaotic trajectories, the entropy and Lyapunov exponents are significantly increased, leading to a fast, light, and reliable chaos-based cryptosystem.
Motivated by today's huge volume of data that needs to be handled in secrecy, there is a wish to develop not only fast and light but also reliably secure cryptosystems. Chaos allows for the creation of pseudo-random numbers (PRNs) by low-dimensional transformations that need to be applied only a small number of times. These two properties may translate into a chaos-based cryptosystem that is both fast (short running time) and light (little computational effort). What we propose here is an approach to generate PRNs-and consequently digital secret keys-that can serve as a seed for an enhanced chaos-based cryptosystem. We use low-dimensional chaotic maps to quickly generate PRNs that have little correlation, and then, we quickly (fast) enhance secrecy by several orders (reliability) with very little computational cost (light) by simply looking at the less significant digits of the initial chaotic trajectory. This paper demonstrates this idea with rigor, by showing that a transformation applied a small number of times to chaotic trajectories significantly increases its entropy and Lyapunov exponents, as a consequence of the smoothing out of the probability density towards a uniform distribution.

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