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

Understanding Deception01:14

Understanding Deception

12
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...
12
Masking and Demasking Agents01:19

Masking and Demasking Agents

2.7K
EDTA titrations may necessitate masking and demasking agents to temporarily protect a particular metal ion in a mixture from the EDTA reaction. These agents facilitate the sequential analysis of the metal ions by forming stable complexes with some—but not all—metal ions during certain steps.
There are many masking agents, such as cyanide, fluoride, triethanolamine, thiourea, and 2,3-bis(sulfanyl)propan-1-ol (formerly 2,3-dimercapto-1-propanol), with the masking agent chosen based on...
2.7K
Non-equilibrium in the Cell01:16

Non-equilibrium in the Cell

4.9K
An important concept in studying metabolism and energy is that of chemical equilibrium. Most chemical reactions are reversible. They can proceed in both directions, releasing energy into their environment in one direction, and absorbing it from the environment in the other direction. The same is true for the chemical reactions involved in cell metabolism, such as the breaking down and building up of proteins into and from individual amino acids, respectively. Reactants within a closed system...
4.9K
Strategies of Self-Presentation II: Self-Verification01:17

Strategies of Self-Presentation II: Self-Verification

8
Self-verification is a fundamental psychological drive wherein individuals seek affirmation of their self-concept from others, striving for consistency between their internal self-view and external perceptions. This drive operates even when the self-concept is negative, influencing interpersonal behavior and feedback preferences in complex and often counterintuitive ways. Unlike the self-enhancement motive, which seeks positive evaluations, self-verification prioritizes coherence and...
8
Ampere-Maxwell's Law: Problem-Solving01:17

Ampere-Maxwell's Law: Problem-Solving

801
A parallel-plate capacitor with capacitance C, whose plates have area A and separation distance d, is connected to a resistor R and a battery of voltage V. The current starts to flow at t = 0. What is the displacement current between the capacitor plates at time t? From the properties of the capacitor, what is the corresponding real current?
To solve the problem, we can use the equations from the analysis of an RC circuit and Maxwell's version of Ampère's law.
For the first part of...
801
Strategies for Assessing and Addressing Confounding01:25

Strategies for Assessing and Addressing Confounding

168
Confounding is a critical issue in epidemiological studies, often leading to misleading conclusions about associations between exposures and outcomes. It occurs when the relationship between the exposure and the outcome is mixed with the effects of other factors that influence the outcome. Given that, addressing confounding is of high importance for drawing accurate inferences in research.
Confounding can be addressed at both the design phase of a study and through analytical methods after data...
168

You might also read

Related Articles

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

Sort by
Same author

Artificial intelligence for fall detection in older adults: A comprehensive survey of machine learning, deep learning approaches, and future directions.

Ageing research reviews·2025
Same author

Quantum inspired qubit qutrit neural networks for real time financial forecasting.

Scientific reports·2025
Same author

A novel ensemble ARIMA-LSTM approach for evaluating COVID-19 cases and future outbreak preparedness.

Health care science·2024
Same author

Personalized cancer vaccine design using AI-powered technologies.

Frontiers in immunology·2024
Same author

Artificial Intelligence-Based Anomaly Detection Technology over Encrypted Traffic: A Systematic Literature Review.

Sensors (Basel, Switzerland)·2024
Same author

Advancing genome editing with artificial intelligence: opportunities, challenges, and future directions.

Frontiers in bioengineering and biotechnology·2024

Related Experiment Video

Updated: Sep 29, 2025

Author Spotlight: Development of an Automated Camera-Based System for Real-Time Blast Overpressure Monitoring and TBI Risk Assessment in Military Training
06:20

Author Spotlight: Development of an Automated Camera-Based System for Real-Time Blast Overpressure Monitoring and TBI Risk Assessment in Military Training

Published on: December 6, 2024

3.0K

Leveraging Computational Intelligence Techniques for Defensive Deception: A Review, Recent Advances, Open Problems

Pilla Vaishno Mohan1, Shriniket Dixit1, Amogh Gyaneshwar1

  • 1School of Computer Science and Engineering, Vellore Institute of Technology (VIT), Vellore 632014, India.

Sensors (Basel, Switzerland)
|March 26, 2022
PubMed
Summary

Defensive deception uses artificial intelligence to counter cyberattacks by creating uncertainty for adversaries. This survey explores deep learning and machine learning for advanced deception frameworks to enhance cybersecurity defenses.

Keywords:
computational intelligencedeep learningdefensive deceptionhoneypotsmachine-learningmoving target defense

More Related Videos

An Experimental Analysis of Children's Ability to Provide a False Report about a Crime
07:36

An Experimental Analysis of Children's Ability to Provide a False Report about a Crime

Published on: May 3, 2016

8.6K

Related Experiment Videos

Last Updated: Sep 29, 2025

Author Spotlight: Development of an Automated Camera-Based System for Real-Time Blast Overpressure Monitoring and TBI Risk Assessment in Military Training
06:20

Author Spotlight: Development of an Automated Camera-Based System for Real-Time Blast Overpressure Monitoring and TBI Risk Assessment in Military Training

Published on: December 6, 2024

3.0K
An Experimental Analysis of Children's Ability to Provide a False Report about a Crime
07:36

An Experimental Analysis of Children's Ability to Provide a False Report about a Crime

Published on: May 3, 2016

8.6K

Area of Science:

  • Cybersecurity
  • Artificial Intelligence
  • Information Warfare

Background:

  • Information systems face daily global attacks, necessitating advanced defense strategies.
  • Defensive deception, inspired by warfare, aims to counter cyber threats by introducing uncertainty.
  • Existing deception tactics include honeypots, honeytokens, and moving target defense.

Purpose of the Study:

  • To provide a comprehensive survey of defensive deception tactics utilizing artificial intelligence.
  • To highlight the need for a quantitative framework for deploying advanced deception technologies.
  • To analyze the application of deep learning and machine learning in defensive deception.

Main Methods:

  • Review and analysis of existing literature on defensive deception.
  • Focus on the integration of computational intelligence, specifically deep learning and machine learning.
  • Identification of insights, lessons, and limitations from prior research.

Main Results:

  • Computational intelligence offers tools for advanced deception frameworks.
  • Deep learning and machine learning are key strategies for implementing defensive deception.
  • Prior work provides valuable insights but also reveals limitations in current approaches.

Conclusions:

  • There is a critical need for a comprehensive framework for advanced deception technologies.
  • Future research should address identified gaps in defensive deception strategies.
  • AI-powered defensive deception holds significant potential for enhancing cybersecurity.