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Logistic map-encrypted Chaotic Ranging code as a proposed alternative to GNSS PRN Pseudorange Code

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Abstrakty
EN
Pseudo-Random Noise (PRN) Gold code was selected for utilisation as the Global Navigation Satellite System (GNSS) pseudo-range measurement code sequence. Recent studies revealed a potential security vulnerability issue due to the Gold PRN code utilisation in a GNSS-related cyber-attack known as GNSS spoofing. Here a PRN code construction method based on chaotic-form logistic map is proposed as an alternative to the existing Gold code practice. Dubbed Chaotic Ranging Code (CRC), is a PRN code generation method that generates ranging code with orthogonal properties as good as, if not better, then those of the Gold PRN code, while assuming the encryption embedded in the proposed CRC code provides improved GNSS information security.
Twórcy
autor
  • University of Ljubljana, Ljubljana, Slovenia 
autor
  • University of Ljubljana, Ljubljana, Slovenia
Bibliografia
  • 1. Filić M.: Foundations of GNSS Spoofing Detection and Mitigation with Distributed GNSS SDR Receiver. TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation, Vol. 12, No. 4, doi:10.12716/1001.12.04.01, pp. 649-656, 2018
  • 2. GPS Directorate. (2013). Global Positioning Systems Directorate Systems Engineering and Integration Interface Specification IS-GPS-200J. Washington, DC. Available at: https://bit.ly/2R6MkSF
  • 3. HM Government Office for Science. (2018). Satellite-Derived Time and Position: A Study of Critical Dependencies. HM Government of the UK and NI. Available at: https://bit.ly/2E2STnd
  • 4. Huang, N E et al. (1998). The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis. Proc R Soc Lond, 454, 903-995. - doi:10.1098/rspa.1998.0193
  • 5. Kanso, A, Smaoui. (2009). Logistic chaotic maps for binary numbers generations. Ch, Sol and Fract, 40, 2557-2568. Available at: https://bit.ly/2RY2Xku - doi:10.1016/j.chaos.2007.10.049
  • 6. May, R M. (1976). Simple mathematical models with very complicated dynamics. Nature, 261, 459-467. - doi:10.1038/261459a0
  • 7. Mitra, A. (2007). On Pseudo-Random and Orthogonal Binary Spreading Sequences. Int J of Inf Tech, 4(2), 137-144.
  • 8. Pecora, L M, Carroll, T L. (2015). Synchronization of chaotic systems. Chaos, 25, 097611. doi: 10.1063/1.4917383 - doi:10.1063/1.4917383
  • 9. Petrovski, I, Tsujii, T. (2012). Digital Satellite Navigation and Geophysics: A Practical Guide with GNSS Signal Simulator and Receiver Laboratory. Cambridge University Press. Cambridge, UK. - doi:10.1017/CBO9780511659072
  • 10. Roeck, A. (2009). Quantifying Studies of (Pseudo) Random Number Generation for Cryptography (PhD thesis). L’Ecole Polytechnique. Palaiseau, France. Available at: https://bit.ly/2WRBEdv
  • 11. Tippenhauer, N O, Poepper, C, Rasmussen, K B, and Čapkun, S. (2011). On the Requirements for Successful GPS Spoofing Attacks. Proc of the 18 th ACM conference on Computer and communications security, 75-86. Chicago, IL. - doi:10.1145/2046707.2046719
  • 12. Yang, L, Xiao-Jun, T. (2012). A new pseudorandom number generator based on complex number chaotic equation.. Chyn Phys B, 21(9), 090506. - doi:10.1088/1674-1056/21/9/090506
  • 13. Yang, T. (2004). A survey of chaotic secure communication systems. Int J of Comp Cogn, 2(2), 81-130. Available at: https://bit.ly/2LiGImY
Uwagi
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).
Typ dokumentu
Bibliografia
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bwmeta1.element.baztech-bd8e84de-9a42-46e5-976b-a958d61c997e
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