Adaptive Event-Triggered Synchronization of Uncertain Fractional Order Neural Networks with Double Deception Attacks and Time-Varying Delay

Abstract

This paper investigates the problem of adaptive event-triggered synchronization for uncertain FNNs subject to double deception attacks and time-varying delay. During network transmission, a practical deception attack phenomenon in FNNs should be considered; that is, we investigated the situation in which the attack occurs via both communication channels, from S-C and from C-A simultaneously, rather than considering only one, as in many papers; and the double attacks are described by high-level Markov processes rather than simple random variables. To further reduce network load, an advanced AETS with an adaptive threshold coefficient was first used in FNNs to deal with deception attacks. Moreover, given the engineering background, uncertain parameters and time-varying delay were also considered, and a feedback control scheme was adopted. Based on the above, a unique closed-loop synchronization error system was constructed. Sufficient conditions that guarantee the stability of the closed-loop system are ensured by the Lyapunov-Krasovskii functional method. Finally, a numerical example is presented to verify the effectiveness of the proposed method.

Research on information security of urban traffic control system based on tripartite evolutionary game

“…However, it is complicated and difficult to construct accurate system mechanism model and attack model, which makes its application in real environment limited. Shen Z et al [9] proposed a new Resilient and Memory Event-Triggered Scheme (RMETS), which can well balance the security performance required by the system and limited network resources when an attack occurs.…”

Finite-Time Stochastic Stability Analysis of Permanent Magnet Synchronous Motors with Noise Perturbation

“…As a typical nonlinear dynamical system, it is sensitive to initial conditions, parameter variables and environmental noise, and has become a common concept, enabling us to understand rich dynamic behavior. Over the past few decades, chaos control and synchronization have been intensively studied in various fields, including information processing, salt-water oscillators, semiconductor lasers, biological systems, chemical reactions and power electronics [ 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 ].…”

Finite-Time Pinning Synchronization Control for T-S Fuzzy Discrete Complex Networks with Time-Varying Delays via Adaptive Event-Triggered Approach

“…As a significant collective behavior in complex networks, synchronization shows practical significance in a coupled circuit system [14], communication networks [15], genetic networks [16] and industrial internet of things [17] and has become a hot topic of special concern in recent years [18][19][20][21]. For example, the asymptotic synchronization criteria for DCNs were derived under the periodic sampling signals in [19] and the exponential synchronization problem is discussed via topology matrices in [20].…”