Nonlinear Dynamics

, Volume 89, Issue 3, pp 1689–1704 | Cite as

Secure communication in wireless sensor networks based on chaos synchronization using adaptive sliding mode control

  • Behrouz Vaseghi
  • Mohammad Ali PourminaEmail author
  • Saleh Mobayen
Original Paper


Due to resource constraints in wireless sensor networks and the presence of unwanted conditions in communication systems and transmission channels, the suggestion of a robust method which provides battery lifetime increment and relative security is of vital importance. This paper considers the secure communication in wireless sensor networks based on new robust adaptive finite time chaos synchronization approach in the presence of noise and uncertainty. For this purpose, the modified Chua oscillators are added to the base station and sensor nodes to generate the chaotic signals. Chaotic signals are impregnated with the noise and uncertainty. At first, we apply the modified independent component analysis to separate the noise from the chaotic signals. Then, using the adaptive finite-time sliding mode controller, a control law and an adaptive parameter-tuning method is proposed to achieve the finite-time chaos synchronization under the noisy conditions and parametric uncertainties. Synchronization between the base station and each of the sensor nodes is realized by multiplying a selection matrix by the specified chaotic signal which is broadcasted by the base station to the sensor nodes. Simulation results are presented to show the effectiveness and applicability of the proposed technique.


Chaos synchronization Adaptive sliding mode control Secure communication Independent component analysis Wireless sensor networks 


  1. 1.
    Ma, J., Li, F., Huang, L., Jin, W.-Y.: Complete synchronization, phase synchronization and parameters estimation in a realistic chaotic system. Commun. Nonlinear Sci. Numer. Simul. 16(9), 3770–3785 (2011)CrossRefzbMATHGoogle Scholar
  2. 2.
    Ma, J., Zhang, A.-H., Xia, Y.-F., Zhang, L.-P.: Optimize design of adaptive synchronization controllers and parameter observers in different hyperchaotic systems. Appl. Math. Comput. 215(9), 3318–3326 (2010)MathSciNetzbMATHGoogle Scholar
  3. 3.
    Mobayen, S., Tchier, F.: Synchronization of A Class of Uncertain Chaotic Systems with Lipschitz Nonlinearities Using State-Feedback Control Design: A Matrix Inequality Approach. Asian J. Control (2017). doi: 10.1002/asjc.1512 Google Scholar
  4. 4.
    Mobayen, S.: Finite-time stabilization of a class of chaotic systems with matched and unmatched uncertainties: An LMI approach. Complexity 21(5), 14–19 (2016)MathSciNetCrossRefGoogle Scholar
  5. 5.
    Mobayen, S., Tchier, F., Ragoub, L.: Design of an adaptive tracker for n-link rigid robotic manipulators based on super-twisting global nonlinear sliding mode control. Int. J. Syst. Sci. (2017). doi: 10.1080/00207721.2017.1299812 MathSciNetGoogle Scholar
  6. 6.
    Mobayen, S.: Finite-time robust-tracking and model-following controller for uncertain dynamical systems. J. Vib. Control 22(4), 1117–1127 (2016)MathSciNetCrossRefzbMATHGoogle Scholar
  7. 7.
    Mobayen, S.: Design of a robust tracker and disturbance attenuator for uncertain systems with time delays. Complexity 21(1), 340–348 (2015)MathSciNetCrossRefGoogle Scholar
  8. 8.
    Mobayen, S.: Fast terminal sliding mode controller design for nonlinear second-order systems with time-varying uncertainties. Complexity 21(2), 239–244 (2015)MathSciNetCrossRefGoogle Scholar
  9. 9.
    Mobayen, S., Tchier, F.: A novel robust adaptive second-order sliding mode tracking control technique for uncertain dynamical systems with matched and unmatched disturbances. Int. J. Control Autom. Syst. (2016). doi: 10.1007/s12555-015-0477-1 zbMATHGoogle Scholar
  10. 10.
    Mobayen, S., Tchier, F.: An LMI approach to adaptive robust tracker design for uncertain nonlinear systems with time-delays and input nonlinearities. Nonlinear Dyn. 85(3), 1965–1978 (2016)MathSciNetCrossRefzbMATHGoogle Scholar
  11. 11.
    Quyen, N.-X., VanYem, V., Duong, T.-Q.: Design and analysis of a spread-spectrum communication system with chaos based variation of both phase-coded carrier and spreading factor. IET Commun. 9(12), 1466–1473 (2015)CrossRefGoogle Scholar
  12. 12.
    Nijsure, Y., Kaddoum, G., Leung, H.: Cognitive chaotic UWB-MIMO radar based on nonparametric Bayesian technique. IEEE Trans. Aero Electron. Syst. 51(3), 2360–2378 (2015)CrossRefGoogle Scholar
  13. 13.
    Berber, S.-M.: Probability of error derivatives for binary and chaos-based CDMA systems in wide-band channels. IEEE Trans. Wirel. Commun. 13(10), 5596–5606 (2014)CrossRefGoogle Scholar
  14. 14.
    Li, C., Liu, Y., Xie, T., Chen, M.-Z.: Breaking a novel image encryption scheme based on improved hyperchaotic sequences. Nonlinear Dyn. 73(3), 2083–2089 (2013)MathSciNetCrossRefzbMATHGoogle Scholar
  15. 15.
    Li, C., Xie, T., Liu, Q., Cheng, G.: Cryptanalyzing image encryption using chaotic logistic map. Nonlinear Dyn. 78(2), 1545–1551 (2014)CrossRefGoogle Scholar
  16. 16.
    Lin, Z., Yu, S., Li, C.: L, J., Wang, Q.: Design and smartphone-based implementation of a chaotic video communication scheme via WAN remote transmission. Int. J. Bifurc Chaos 26(09), 1650158 (2016)CrossRefGoogle Scholar
  17. 17.
    Xie, E.-Y., Li, C., Yu, S.: L, J.: On the cryptanalysis of Fridrich’s chaotic image encryption scheme. Signal Process. 132, 150–154 (2017)CrossRefGoogle Scholar
  18. 18.
    Kajbaf, A., Akhaee, M.-A., Sheikhan, M.: Fast synchronization of non-identical chaotic modulation-based secure systems using amodified slidingmode controller. Chaos Soliton Fract. 84, 49–57 (2016)CrossRefzbMATHGoogle Scholar
  19. 19.
    Pecora, L.-M., Carroll, T.-L.: Synchronization in chaotic systems. Phys. Rev. Lett. 64(8), 821 (1990)MathSciNetCrossRefzbMATHGoogle Scholar
  20. 20.
    Herceg, M., Miličević, K., Matić, T.: Frequency-translated differential chaos shift keying for chaos-based communications. J. Franklin Inst. 353(13), 2966–2979 (2016)MathSciNetCrossRefzbMATHGoogle Scholar
  21. 21.
    Shu, X., Wang, H., Yang, X., Wang, J.: Chaotic modulations and performance analysis for digital underwater acoustic communications. Appl. Acoust. 105, 200–208 (2016)CrossRefGoogle Scholar
  22. 22.
    Aromataris, G., Annovazzi-Lodi, V.: Enhancing privacy of chaotic communications by double masking. IEEE J. Quantum. Electr. 49(11), 955–959 (2013)CrossRefGoogle Scholar
  23. 23.
    Filali, R.L., Benrejeb, M., Borne, P.: On observer-based secure communication design using discrete-time hyperchaotic systems. Commun. Nonlinear Sci. Numer. Simul. 19(5), 1424–1432 (2014)MathSciNetCrossRefGoogle Scholar
  24. 24.
    Wang, X.-Y., Gu, S.-X.: New chaotic encryption algorithm based on chaotic sequence and plain text. IET Inform. Secur. 8(3), 213–216 (2014)CrossRefGoogle Scholar
  25. 25.
    Soriano-Snchez, A.-G., Posadas-Castillo, C., Platas-Garza, M.-A., Diaz-Romero, D.-A.: Performance improvement of chaotic encryption via energy and frequency location criteria. Math. Comput. Simul. 112, 14–27 (2015)MathSciNetCrossRefGoogle Scholar
  26. 26.
    Khelifa, M.A., Boukabou, A.: Design of an intelligent prediction-based neural network controller for multi-scroll chaotic systems. Appl. Intell. 45(3), 793–807 (2016)CrossRefGoogle Scholar
  27. 27.
    Chien, T.-H., Chen, Y.-C.: Combination of Observer/Kalman Filter identification and digital redesign of observer-based tracker for stochastic chaotic systems. In: 2016 International Symposium on Computer, Consumer and Control (IS3C), pp. 103–107 IEEE (2016)Google Scholar
  28. 28.
    Vaidyanathan, S., Idowu, B.-A., Azar, A.-T.: Backstepping controller design for the global chaos synchronization of Sprotts jerk systems. In: Chaos Modeling and Control Systems Design, pp. 39–58. Springer International Publishing (2015)Google Scholar
  29. 29.
    Xu, L., Ge, S.-S.: Set-stabilization of discrete chaotic systems via impulsive control. Appl. Math. Lett. 53, 52–62 (2016)MathSciNetCrossRefzbMATHGoogle Scholar
  30. 30.
    Jun, M., Qing-Yun, W., Wu-Yin, J., Ya-Feng, X.: Control chaos in Hindmarsh–Rose neuron by using intermittent feedback with one variable. Chin. Phys. Lett. 2510), 3582 (2008)Google Scholar
  31. 31.
    Li, Y., Li, C.: Complete synchronization of delayed chaotic neural networks by intermittent control with two switches in a control period. Neurocomputing 173, 1341–1347 (2016)CrossRefGoogle Scholar
  32. 32.
    Zheng, S.: Multi-switching combination synchronization of three different chaotic systems via nonlinear control. Optik-Int. J. Light Electron Opt. 127(21), 10247–10258 (2016)CrossRefGoogle Scholar
  33. 33.
    Chekan, J.-A., Nojoumian, M.-A., Merat, K., Salarieh, H.: Chaos control in lateral oscillations of spinning disk via linear optimal control of discrete systems. J. Vib. Control 23(1), 103–110 (2017)MathSciNetCrossRefGoogle Scholar
  34. 34.
    Mobayen, S., Tchier, F.: Composite nonlinear feedback control technique for master/slave synchronization of nonlinear systems. Nonlinear Dyn. 87(3), 1731–1747 (2017)CrossRefGoogle Scholar
  35. 35.
    Handa, H., Sharma, B.-B.: Novel adaptive feedback synchronization scheme for a class of chaotic systems with and without parametric uncertainty Chaos Soliton Fract. 86, 50–63 (2017)Google Scholar
  36. 36.
    Mobayen, S.: Design of LMI based global sliding mode controller for uncertain nonlinear systems with application to Genesio’s chaotic system. Complexity 21(1), 94–98 (2015)MathSciNetCrossRefGoogle Scholar
  37. 37.
    Mobayen, S.: An LMI-based robust controller design using global nonlinear sliding surfaces and application to chaotic systems. Nonlinear Dyn. 79(2), 1075–1084 (2015)MathSciNetCrossRefzbMATHGoogle Scholar
  38. 38.
    Mobayen, S., Baleanu, D., Tchier, F.: Second-order fast terminal sliding mode control design based on LMI for a class of non-linear uncertain systems and its application to chaotic systems. J Vib Control (2016). doi: 10.1177/1077546315623887 Google Scholar
  39. 39.
    Ouassaid, M., Maaroufi, M., Cherkaoui, M.: Observerbased nonlinear control of power system using sliding mode control strategy. Electr. Power Syst. Res. 84, 135143 (2012)CrossRefGoogle Scholar
  40. 40.
    Hsu, C.-F., Lee, B.-K.: FPGA-based adaptive PID control of a DC motor driver via sliding-mode approach. Expert Syst. Appl. 38, 1186611872 (2011)Google Scholar
  41. 41.
    Sun, T., Pei, H., Pan, Y., Zhou, H., Zhang, C.: Neural network-based sliding mode adaptive control for robot manipulators. Neurocomputing 74, 23772384 (2011)Google Scholar
  42. 42.
    Zhu, F., Xu, J., Chen, M.: The combination of high-gain sliding mode observers used as receivers in secure communication. IEEE Trans. Circ. Syst. I: Regul. Pap. 59(11), 2702–2712 (2012)Google Scholar
  43. 43.
    Mobayen, S., Javadi, S.: Disturbance observer and finite-time tracker design of disturbed third-order non holonomic systems using terminal sliding mode. J. Vib. Control 23(2), 181–189 (2017)MathSciNetCrossRefGoogle Scholar
  44. 44.
    Mobayen, S.: An LMI-based robust tracker for uncertain linear systems with multiple time-varying delays using optimal composite nonlinear feedback technique. Nonlinear Dyn. 80, 917–927 (2015)MathSciNetCrossRefzbMATHGoogle Scholar
  45. 45.
    Mobayen, S.: Fast terminal sliding mode tracking of non-holonomic systems with exponential decay rate. IET Control Theory A 9(8), 1294–1301 (2015)MathSciNetCrossRefGoogle Scholar
  46. 46.
    Mobayen, S.: Design of LMI-based sliding mode controller with an exponential policy for a class of underactuated systems. Complexity 21(5), 117–124 (2016)MathSciNetCrossRefGoogle Scholar
  47. 47.
    Golestani, M., Mobayen, S., Tchier, F.: Adaptive finite-time tracking control of uncertain non-linear n-order systems with unmatched uncertainties. IET Control Theory Appl. 10(14), 1675–1683 (2016)MathSciNetCrossRefGoogle Scholar
  48. 48.
    Mobayen, S., Tchier, F.: Design of an adaptive chattering avoidance global sliding mode tracker for uncertain non-linear time-varying systems. Trans. Inst. Measur. Control (2016). doi: 10.1177/0142331216644046 zbMATHGoogle Scholar
  49. 49.
    Mobayen, S., Baleanu, D.: Stability analysis and controller design for the performance improvement of disturbed nonlinear systems using adaptive global sliding mode control approach. Nonlinear Dyn. 83(3), 1557–1565 (2016)MathSciNetCrossRefzbMATHGoogle Scholar
  50. 50.
    Mobayen, S., Tchier, F.: A new LMI-based robust finite-time sliding mode control strategy for a class of uncertain nonlinear systems. Kybernetika 51(6), 1035–1048 (2015)MathSciNetzbMATHGoogle Scholar
  51. 51.
    Mobayen, S.: A novel global sliding mode control based on exponential reaching law for a class of underactuated systems with external disturbances. J. Comput. Nonlinear Dyn. 11(2), 021011 (2016)CrossRefGoogle Scholar
  52. 52.
    Mobayen, S.: An adaptive fast terminal sliding mode control combined with global sliding mode scheme for tracking control of uncertain nonlinear third-order systems. Nonlinear Dyn. 82(1–2), 599–610 (2015)MathSciNetCrossRefzbMATHGoogle Scholar
  53. 53.
    Mobayen, S., Baleanu, D.: Linear matrix inequalities design approach for robust stabilization of uncertain nonlinear systems with perturbation based on optimally-tuned global sliding mode control. J. Vib. Control 23(8), 1285–1295 (2017)Google Scholar
  54. 54.
    Mobayen, S.: An adaptive chattering-free PID sliding mode control based on dynamic sliding manifolds for a class of uncertain nonlinear systems. Nonlinear Dyn. 82(1–2), 53–60 (2015)MathSciNetCrossRefzbMATHGoogle Scholar
  55. 55.
    Mobayen, S.: Finite-time tracking control of chained-form nonholonomic systems with external disturbances based on recursive terminal sliding mode method. Nonlinear Dyn. 80(1–2), 669–683 (2015)MathSciNetCrossRefzbMATHGoogle Scholar
  56. 56.
    Zabi, G., Peyrard, F., Kachouri, A., Fournier-Prunaret, D., Samet, M.: Efficient and secure chaotic S-box for wireless sensor network. Secur. Commun. Netw. 9(8), 1294–1301 (2014)Google Scholar
  57. 57.
    Al.-Mashhadi, H.-M., Abdul.-Wahab, H.-B., Hassan, R.-F.: Data security protocol for wireless sensor network using chaotic map. Int. J. Comput. Sci. Inf. Secur. 13(8), 80 (2015)Google Scholar
  58. 58.
    Dutta, R., Gupta, S.: Das, M.-K.:Energy-aware chaotic communication in wireless sensor network. Appl. Mech. Mater. 367, 536–540 (2013)CrossRefGoogle Scholar
  59. 59.
    Jin, L., Zhang, Y., Li, L.: One-to-many chaotic synchronization with application in wireless sensor network. IEEE Commun. Lett. 17(9), 1782–1785 (2013)CrossRefGoogle Scholar
  60. 60.
    De la Hoz, M.-Z., Acho, L., Vidal, Y.: A modified Chuachaotic oscillator and its application to secure communications. Appl. Math. Comput. 247, 712–722 (2014)MathSciNetzbMATHGoogle Scholar
  61. 61.
    Moulay, E., Peruquetti, W.: Finite time stability and stabi lization of a class of continuous systems. J. Math. Anal. Appl. 323, 1430–1443 (2006)MathSciNetCrossRefGoogle Scholar
  62. 62.
    Cardoso, J.-F, Antoine, S.: Blind beamforming for non-Gaussian signals. In: IEE Proceedings F (Radar and Signal Processing) IET Digital Library, vol. 140(6), pp. 362–370 (1993)Google Scholar
  63. 63.
    Hyvrinen, A., Karhunen, J., Oja, E.: Independent Component Analysis, vol. 46. Wiley, New York (2004)Google Scholar
  64. 64.
    Fallahi, K., Raoufi, R., Khoshbin, H.: An application of Chen system for secure chaotic communication based on extended Kalman filter and multi-shift cipher algorithm. Commun. Nonlinear Sci. Numer. Simul. 13(4), 763–781 (2008)MathSciNetCrossRefzbMATHGoogle Scholar
  65. 65.
    Ma, J., Wu, X., Chu, R., Zhang, L.: Selection of multi-scroll attractors in Jerk circuits and their verification using Pspice. Nonlinear Dyn. 76(4), 1951–1962 (2014)CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2017

Authors and Affiliations

  1. 1.Department of Electrical and Computer Engineering, Science and Research BranchIslamic Azad UniversityTehranIran
  2. 2.Department of Electrical EngineeringUniversity of ZanjanZanjanIran

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