AIMC Topic: Deception

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Detecting deception with artificial intelligence: promises and perils.

Trends in cognitive sciences Apr 21, 2024
Rapid advancements in artificial intelligence (AI) have driven interest in its potential application for lie detection. Unfortunately, the current approaches have primarily focused on technical aspects at the expense of a solid methodological and the...
Humans Artificial Intelligence Lie Detection Deception
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Role play with large language models.

Nature Nov 8, 2023
As dialogue agents become increasingly human-like in their performance, we must develop effective ways to describe their behaviour in high-level terms without falling into the trap of anthropomorphism. Here we foreground the concept of role play. Cas...
Humans Deception Natural Language Processing Terminology as Topic Self-Assessment Imitative Behavior
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Deception detection with machine learning: A systematic review and statistical analysis.

PloS one Feb 9, 2023
Several studies applying Machine Learning to deception detection have been published in the last decade. A rich and complex set of settings, approaches, theories, and results is now available. Therefore, one may find it difficult to identify trends, ...
Neural Networks, Computer Machine Learning Research Design Deception Publications
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Protecting world leaders against deep fakes using facial, gestural, and vocal mannerisms.

Proceedings of the National Academy of Sciences of the United States of America Nov 23, 2022
Since their emergence a few years ago, artificial intelligence (AI)-synthesized media-so-called deep fakes-have dramatically increased in quality, sophistication, and ease of generation. Deep fakes have been weaponized for use in nonconsensual pornog...
Artificial Intelligence Gestures Deception
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Recursive Minimum-Variance Filter Design for State-Saturated Complex Networks With Uncertain Coupling Strengths Subject to Deception Attacks.

IEEE transactions on cybernetics Sep 19, 2022
In this article, the recursive filtering problem is investigated for state-saturated complex networks (CNs) subject to uncertain coupling strengths (UCSs) and deception attacks. The measurement signals transmitted via the communication network may su...
Neural Networks, Computer Computer Simulation Time Factors Deception
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IAT faking indices revisited: Aspects of replicability and differential validity.

Behavior research methods Apr 19, 2022
Research demonstrates that IATs are fakeable. Several indices [either slowing down or speeding up, and increasing errors or reducing errors in congruent and incongruent blocks; Combined Task Slowing (CTS); Ratio 150-10000] have been developed to dete...
Humans Machine Learning Deception
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Leveraging Computational Intelligence Techniques for Defensive Deception: A Review, Recent Advances, Open Problems and Future Directions.

Sensors (Basel, Switzerland) Mar 11, 2022
With information systems worldwide being attacked daily, analogies from traditional warfare are apt, and deception tactics have historically proven effective as both a strategy and a technique for Defense. Defensive Deception includes thinking like a...
Artificial Intelligence Machine Learning Algorithms Deception
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Event-Triggered Output Feedback Synchronization of Master-Slave Neural Networks Under Deception Attacks.

IEEE transactions on neural networks and learning systems Feb 28, 2022
The problem of event-triggered synchronization of master-slave neural networks is investigated in this article. It is assumed that both communication channels from the sensor to controller and from controller to actuator are subject to stochastic dec...
Neural Networks, Computer Feedback Communication Deception Markov Chains
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Event-triggered H/passive synchronization for Markov jumping reaction-diffusion neural networks under deception attacks.

ISA transactions Dec 30, 2021
The issue of H/passive master-slave synchronization for Markov jumping neural networks with reaction-diffusion terms is investigated in this paper via an event-triggered control scheme under deception attacks. To lighten the burden of limited communi...
Neural Networks, Computer Communication Deception Diffusion
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Deepfake Detection Using the Rate of Change between Frames Based on Computer Vision.

Sensors (Basel, Switzerland) Nov 5, 2021
Recently, artificial intelligence has been successfully used in fields, such as computer vision, voice, and big data analysis. However, various problems, such as security, privacy, and ethics, also occur owing to the development of artificial intelli...
Neural Networks, Computer Artificial Intelligence Machine Learning Computers Deception
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