AIMC Topic: Deception

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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...
Communication Deception Diffusion Neural Networks, Computer
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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...
Artificial Intelligence Machine Learning Computers Neural Networks, Computer Deception
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Deceptive Online Content Detection Using Only Message Characteristics and a Machine Learning Trained Expert System.

Sensors (Basel, Switzerland) Oct 26, 2021
This paper considers the use of a post metadata-based approach to identifying intentionally deceptive online content. It presents the use of an inherently explainable artificial intelligence technique, which utilizes machine learning to train an expe...
Emotions Deception Artificial Intelligence Expert Systems Machine Learning
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Exponential synchronization of coupled neural networks under stochastic deception attacks.

Neural networks : the official journal of the International Neural Network Society Oct 23, 2021
In this paper, the issue of synchronization is investigated for coupled neural networks subject to stochastic deception attacks. Firstly, a general differential inequality with delayed impulses is given. Then, the established differential inequality ...
Deception Neural Networks, Computer Time Factors
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Machine learning based approach to exam cheating detection.

PloS one Aug 4, 2021
The COVID-19 pandemic has impelled the majority of schools and universities around the world to switch to remote teaching. One of the greatest challenges in online education is preserving the academic integrity of student assessments. The lack of dir...
Algorithms SARS-CoV-2 Educational Measurement Pandemics COVID-19 Lie Detection Deception Datasets as Topic Models, Theoretical Universities Humans Machine Learning Education, Distance Fraud
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Improved semi-supervised autoencoder for deception detection.

PloS one Oct 8, 2019
Existing algorithms of speech-based deception detection are severely restricted by the lack of sufficient number of labelled data. However, a large amount of easily available unlabelled data has not been utilized in reality. To solve this problem, th...
Lie Detection Deception Artificial Intelligence Algorithms Humans
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Self Multi-Head Attention-based Convolutional Neural Networks for fake news detection.

PloS one Sep 26, 2019
With the rapid development of the internet, social media has become an essential tool for getting information, and attracted a large number of people join the social media platforms because of its low cost, accessibility and amazing content. It great...
Models, Statistical Deception Social Media Neural Networks, Computer Data Analysis
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Predicting instructed simulation and dissimulation when screening for depressive symptoms.

European archives of psychiatry and clinical neuroscience Dec 12, 2018
The intentional distortion of test results presents a fundamental problem to self-report-based psychiatric assessment, such as screening for depressive symptoms. The first objective of the study was to clarify whether depressed patients like healthy ...
Humans Young Adult Adult Female Supervised Machine Learning Malingering Psychometrics Deception Male Predictive Value of Tests Depression
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Resting-state Functional Connectivity and Deception: Exploring Individualized Deceptive Propensity by Machine Learning.

Neuroscience Oct 28, 2018
Individuals show marked variability in determining to be honest or deceptive in daily life. A large number of studies have investigated the neural substrates of deception; however, the brain networks contributing to the individual differences in dece...
Games, Experimental Individuality Nerve Net Deception Brain Mapping Machine Learning Brain Humans Adult Female Young Adult Male Magnetic Resonance Imaging
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Functional neural networks of honesty and dishonesty in children: Evidence from graph theory analysis.

Scientific reports Sep 21, 2017
The present study examined how different brain regions interact with each other during spontaneous honest vs. dishonest communication. More specifically, we took a complex network approach based on the graph-theory to analyze neural response data whe...
Male Brain Nerve Net Deception Models, Neurological Child Female Humans Analysis of Variance Neural Networks, Computer
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