Impulsive Neural Networks Towards Image Protection
Inspired by security applications in the Industrial Internet of Things (IIoT), this chapter focuses on the usage of impulsive neural network synchronization technique for intelligent image protection against illegal swiping and abuse. A class of nonlinear interconnected neural networks with transmission delay and random impulse effect is first introduced. In order to make network protocols more flexible, a randomized broadcast impulsive coupling scheme is integrated into the protocol design. Impulsive synchronization criteria are then derived for the chaotic neural networks in presence of nonlinear protocol and random broadcast impulse, with the impulse effect discussed. Illustrative examples are provided to verify the developed impulsive synchronization results and to show its potential application in image encryption and decryption.
- 2.A. R. Sadeghi, C. Wachsmann, and M. Waidner, “Security and privacy challenges in Industrial Internet of Things,” in 52nd ACM/EDAC/IEEE Design Automation Conf., 2015, pp. 1–6.Google Scholar
- 3.G. R. Chen and X. N. Dong, “From Chaos to Order: Methodologies, Perspectives and Applications,” Singapore: World Scientific, 1998.Google Scholar
- 8.W. Lu and T. Chen, “Synchronization of coupled connected neural networks with delays,” IEEE Trans. Circuits Syst. I, vol. 54, no. 6, pp. 1317–1326, 2004.Google Scholar
- 19.M. Stern, H. Sompolinsky, and L. F. Abbott, “Dynamics of random neural networks with bistable units,” Phy. Rev. E, vol. 90, no. 062710, pp. 1–7, 2014.Google Scholar
- 24.A. Mosebach and J. Lunze, “A deterministic gossiping algorithm for the synchronization of multi-agent systems,” in 5th IFAC Workshop on Distributed Estimation and Control in Netw. Syst., 2015, pp. 1–7.Google Scholar
- 31.J. P. Hespanha and A. S. Morse, “Stability of switched systems with average dwell-time,” in 38th IEEE conf. decision contr., 1999, pp. 2655–2660.Google Scholar