Counteracting dynamical degradation of a class of digital chaotic systems via Unscented Kalman Filter and perturbation

Yuling Luo, Yunqi Liu, Junxiu Liu, Shunbin Tang, Jim Harkin, Yi Cao

Research output: Contribution to journalArticlepeer-review

33 Citations (Scopus)
136 Downloads (Pure)


Theoretically, any chaotic system or chaotic map has ideal complex dynamics. However, because of the finite precision of simulation software and digital devices during implementation, chaotic systems often undergo dynamical degradation, which hinders the further application of digital chaotic systems in many fields. Therefore in this paper, the method based on the perturbation and Unscented Kalman Filter (UKF) theory is designed to counteract the dynamical degradation of digital chaotic systems. Specifically, the UKF algorithm is employed to reinstate the original dynamic performance of the chaotic system, and then perturbation feedback technology is used to cause the chaotic system to obtain strong dynamic performance to resist attacks. The experimental and simulation results demonstrate that this method has good effect on improving the dynamic degradation of digital chaotic map. In addition, the corresponding pseudorandom number generator (PRNG) is constructed via this method, and its randomness is evaluated using the National Institute of Standards and Technology (NIST) SP800-22 and TestU01 test suites. By comparing with other schemes, it can be seen that this PRNG has better performance which illustrates the proposed scheme can be applied in the chaos-based cryptography and utilized in other potential applications.
Original languageEnglish
Article number556
Pages (from-to)49-66
Number of pages18
JournalInformation Sciences
Issue number2021
Early online date29 Dec 2020
Publication statusPublished (in print/issue) - 1 May 2021

Bibliographical note

Funding Information:
This research was supported by the National Natural Science Foundation of China under Grants 61801131 and 61661008, the funding of Overseas 100 Talents Program of Guangxi Higher Education, 2018 Guangxi One Thousand Young and Middle-Aged College and University Backbone Teachers Cultivation Program.

Publisher Copyright:
© 2020 Elsevier Inc.


  • Cryptography
  • Digital chaotic systems
  • Dynamical degradation
  • Pseudorandom number generator
  • Unscented Kalman Filter


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