Related Experiment Video
Updated: Feb 26, 2026
11:54
Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface
Published on: May 8, 2021
5.2K
Sampled-Data-Based Secure Synchronization Control of Delayed Coupled Fuzzy Inertial Neural Networks Under Deception
IEEE Transactions on Cybernetics
|February 24, 2026
Summary
This study introduces a fuzzy sampling data security controller to address deception attacks on delayed coupled fuzzy inertial neural networks (FINNs). The method ensures exponential synchronization for these networks despite adversarial interference.
Area of Science:
- Control Theory
- Artificial Intelligence
- Network Security
Background:
- Delayed coupled fuzzy inertial neural networks (FINNs) are susceptible to deception attacks.
- Ensuring network security and synchronization under adversarial conditions is crucial.
Purpose of the Study:
- To design a robust security control strategy for FINNs against deception attacks.
- To analyze the system's behavior under deceptive interference and guarantee exponential synchronization.
Main Methods:
- A fuzzy sampling data security controller was designed.
- Lyapunov functionals (LKFs) and inequality techniques were employed.
- Linear matrix inequalities (LMIs) were used to establish synchronization criteria.
Main Results:
- A theoretical framework for analyzing closed-loop system behavior under deception was formulated.
- Criteria for achieving exponential synchronization were successfully established.
- Numerical simulations confirmed the effectiveness of the proposed security control approach.
Conclusions:
- The developed security control method effectively mitigates deception attacks.
- Exponential synchronization of delayed coupled FINNs can be achieved even under adversarial conditions.
- The approach demonstrates practical applicability in securing intelligent networks.
Related Concept Videos
01:14Understanding Deception
200
Deception is a pervasive aspect of human communication. Empirical studies have shown that most individuals engage in some form of deceit on a daily basis, with approximately 20% of social exchanges involving deceptive elements. Lying follows a developmental trajectory, peaking during adolescence and declining with age, possibly due to the maturation of cognitive control and social accountability.Cognitive and Social Factors in Deception DetectionDespite its prevalence, accurately detecting...
200
01:18Aliasing
717
Accurate signal sampling and reconstruction are crucial in various signal-processing applications. A time-domain signal's spectrum can be revealed using its Fourier transform. When this signal is sampled at a specific frequency, it results in multiple scaled replicas of the original spectrum in the frequency domain. The spacing of these replicas is determined by the sampling frequency.
If the sampling frequency is below the Nyquist rate, these replicas overlap, preventing the original...
If the sampling frequency is below the Nyquist rate, these replicas overlap, preventing the original...
717
01:10Propagation of Uncertainty from Systematic Error
1.5K
The atomic mass of an element varies due to the relative ratio of its isotopes. A sample's relative proportion of oxygen isotopes influences its average atomic mass. For instance, if we were to measure the atomic mass of oxygen from a sample, the mass would be a weighted average of the isotopic masses of oxygen in that sample. Since a single sample is not likely to perfectly reflect the true atomic mass of oxygen for all the molecules of oxygen on Earth, the mass we obtain from this...
1.5K