Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Distributed Loads: Problem Solving01:21

Distributed Loads: Problem Solving

1.3K
Beams are structural elements commonly employed in engineering applications requiring different load-carrying capacities. The first step in analyzing a beam under a distributed load is to simplify the problem by dividing the load into smaller regions, which allows one to consider each region separately and calculate the magnitude of the equivalent resultant load acting on each portion of the beam. The magnitude of the equivalent resultant load for each region can be determined by calculating...
1.3K
Propagation of Uncertainty from Random Error00:59

Propagation of Uncertainty from Random Error

1.9K
An experiment often consists of more than a single step. In this case, measurements at each step give rise to uncertainty. Because the measurements occur in successive steps, the uncertainty in one step necessarily contributes to that in the subsequent step. As we perform statistical analysis on these types of experiments, we must learn to account for the propagation of uncertainty from one step to the next. The propagation of uncertainty depends on the type of arithmetic operation performed on...
1.9K
Propagation of Uncertainty from Systematic Error01:10

Propagation of Uncertainty from Systematic Error

1.4K
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...
1.4K
BIBO stability of continuous and discrete -time systems01:24

BIBO stability of continuous and discrete -time systems

1.1K
System stability is a fundamental concept in signal processing, often assessed using convolution. For a system to be considered bounded-input bounded-output (BIBO) stable, any bounded input signal must produce a bounded output signal. A bounded input signal is one where the modulus does not exceed a certain constant at any point in time.
To determine the BIBO stability, the convolution integral is utilized when a bounded continuous-time input is applied to a Linear Time-Invariant (LTI) system....
1.1K
Distribution Reliability and Automation01:25

Distribution Reliability and Automation

678
Distribution reliability in electrical power systems is critical for ensuring an uninterrupted power supply to consumers at minimal cost. According to IEEE Standard Terms, reliability is the probability that a device will function without failure over a specified time period or amount of usage. For electric power distribution, this translates to maintaining continuous power supply and addressing customer concerns over power outages. Several indices, as defined by IEEE Standard 1366-2012, are...
678
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

333
Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
333

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Exploring the role of specialized pro-resolving mediators, fatty acid oxidation markers and transporters in Gestational Diabetes Mellitus (GDM) placentae.

Placenta·2025
Same author

Profibrotic monocyte-derived alveolar macrophages as a biomarker and therapeutic target in systemic sclerosis-associated interstitial lung disease.

bioRxiv : the preprint server for biology·2025
Same author

Fatty acid metabolism in the placentae of gestational diabetes mellitus.

Prostaglandins, leukotrienes, and essential fatty acids·2025
Same author

Longitudinal assessment of maternal micronutrients (folate and vitamin B<sub>12</sub>) and homocysteine levels in women who develop gestational diabetes mellitus.

European journal of clinical nutrition·2025
Same author

Evaluating the feasibility of prehospital point-of-care EEG: The prehospital implementation of rapid EEG (PHIRE) study.

Journal of the American College of Emergency Physicians open·2024
Same author

Distributed Discrete-time Exponential Sliding Mode Consensus Protocol for Discrete Multi-Agent System Comprise of Multiple Robotic Arms.

ISA transactions·2024
Same journal

Stackelberg differential game-based fuzzy adaptive hierarchical optimal control for a nonlinear system with unknown dynamics.

ISA transactions·2026
Same journal

Composite fault-tolerant predictive control strategy for PMSM demagnetization faults.

ISA transactions·2026
Same journal

Bias-compensated Q-learning for optimal tracking control under denial-of-service attacks.

ISA transactions·2026
Same journal

Motion prediction for leader manipulator of teleoperation system with large time delay based on inverse optimal control.

ISA transactions·2026
Same journal

Neural network parameter identification-based prescribed-time adaptive control for morphing glide aircraft.

ISA transactions·2026
Same journal

Nonlinear system-guided continuous-time generalization for cross-aircraft engine state monitoring.

ISA transactions·2026
See all related articles

Related Experiment Video

Updated: Apr 27, 2026

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
05:30

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

1.3K

False data injection attack resilient distributed exponential sliding mode consensus protocol for discrete

Nikita Joshi1, Axaykumar Mehta1

  • 1Electrical & Computer Science Engineering Department, Institute of Infrastructure, Technology, Research And Management, Ahmedabad, Gujarat, 380026, India.

ISA Transactions
|April 25, 2026
PubMed
Summary
This summary is machine-generated.

This study introduces a novel False Data Injection (FDI) attack resilient protocol for discrete multi-agent systems. The new method enhances cyber-physical security by detecting and tolerating FDI attacks on communication weights, ensuring system stability.

Keywords:
ConsensusCyber-physical attackDiscrete multi-agent systemsDiscrete-time sliding mode controlFalse data injection attackUnknown input observer

Related Experiment Videos

Last Updated: Apr 27, 2026

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
05:30

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

1.3K

Area of Science:

  • Control Systems Engineering
  • Cyber-Physical Systems Security
  • Robotics

Background:

  • Discrete Multi-Agent Systems (DMASs) are vulnerable to False Data Injection (FDI) attacks targeting communication links.
  • Existing resilient consensus theories primarily focus on sensor or actuator attacks, leaving communication weight vulnerabilities underexplored.
  • Ensuring robust consensus in DMASs under cyber-physical attacks is critical for reliable operation.

Purpose of the Study:

  • To propose a novel False Data Injection (FDI) attack resilient Distributed Exponential Sliding Mode Consensus (DESMC) protocol for DMASs.
  • To extend resilient consensus theory by explicitly modeling FDI attacks on communication weights.
  • To enhance the cyber-physical security of DMASs against sophisticated communication-based attacks.

Main Methods:

  • A distributed Unknown Input Observer (UIO) was developed to detect FDI attacks on communication links.
  • A switching mechanism was implemented, transitioning between sliding surfaces for normal and FDI-attack conditions based on UIO residuals.
  • An adaptive sliding surface within the DESMC protocol was derived to tolerate FDI attack effects and maintain consensus stability.
  • Lyapunov functions were used to derive conditions for global consensus stability.

Main Results:

  • The proposed DESMC protocol guarantees finite-time convergence and ultra-tight O(T^3) quasi-sliding bands.
  • The protocol autonomously reconfigures consensus dynamics, isolating malicious influence without controller redesign.
  • Simulation and experimental validation on 2-DOF robotic manipulators confirmed reliable consensus, rapid recovery, and robustness against FDI attacks.
  • The protocol demonstrated reduced control effort while preserving global stability under attack.

Conclusions:

  • The developed FDI resilient DESMC protocol effectively enhances the cyber-physical security of DMASs.
  • The switching surface strategy ensures reliable consensus and rapid recovery from FDI attacks.
  • The proposed approach offers a robust and adaptable solution for secure consensus in networked systems.