Statistical Simulation of the Information Warfare

Nakonechnyi, Oleksandr; Pashko, A. A.; Капустян, О. А.; Zinko, Taras; Shevchuk, Iuliia

doi:10.1109/atit49449.2019.9030599

Cited by 3 publications

(1 citation statement)

References 14 publications

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“…Another model by [8] employs mathematical and computer models to examine non-permanent information warfare, forecasting system developments and proposing control strategies. Contrastingly, [9] introduces a mathematical model based on nonlinear stochastic differential equations. It explores stability conditions and conducts statistical modeling using Wiener random processes, asserting both theoretical and practical implications.…”

Section: Related Workmentioning

confidence: 99%

Modeling Information Warfare in Scale-Free Networks: Analysis of Propagation and Counter-Propagation Dynamics

pandey,

Pandey,

Nazarov

2024

Preprint

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In an era where information's rapid dissemination profoundly impacts society, this study introduces a comprehensive model examining information warfare dynamics within a scale-free network. Emphasizing the propagation and counter-propagation processes, our model intricately captures interactions among network nodes and their attributed statuses. Constructing a scale-free network via the Barabasi-Albert model, we simulate an information dissemination environment, attributing nodes as Informed or Unversed to mirror the diversity within the network. The transmission probability, contingent on node attributes, governs the information propagation process, while a reinforcement mechanism factors in the higher susceptibility of Unversed nodes to reinfection. Introducing a counter-propagation process to recover infected nodes, recovery probabilities are tailored based on node literacy status, potentially enhancing intervention effectiveness. Extensive simulations scrutinize the dynamics of information warfare, investigating parameters like transmission and recovery probabilities, and network topology's influence on information spread and counter-propagation success. This study evaluates defender and attacker accuracy, unveiling varied strategy effectiveness. The accuracy of the defender, which measures the rate at which nodes recover and align with their actual literacy attributes, was found to be 66.7% in defender dominant state and accuracy of attacker was 81.9% in attacker dominant state. Our findings illuminate the intricate dynamics of information warfare, underscoring the pivotal role of literacy status and proposing strategies to bolster defender accuracy.

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Section: Related Workmentioning

confidence: 99%

Modeling Information Warfare in Scale-Free Networks: Analysis of Propagation and Counter-Propagation Dynamics

pandey,

Pandey,

Nazarov

2024

Preprint

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Detection of Propaganda in Information Warfare using Deep Learning

Pandey

Nazarov

2022

2022 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N)

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Mathematical and Computer Modeling of a Dynamic System for Effectively Combating Disinformation

Kereselidze

2024

Wseas Transactions on Systems

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The work investigated a mathematical and computer model of a dynamic system for effectively combating disinformation. In the compartmental model of false information dissemination in society, there are groups of citizens: - At risk, prone to the perception of misinformation; Adepts - those who accepted false information and with Immunity - those who rejected false information from the very beginning or future adepts. A barrier level for the number of adherents will be introduced as a measure of the information security of society. As a result of a computer experiment, the possibility of an uncontrolled growth in the number of adherents was identified, threatening the safety of society as a whole.

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Statistical Simulation of the Information Warfare

Cited by 3 publications

References 14 publications

Modeling Information Warfare in Scale-Free Networks: Analysis of Propagation and Counter-Propagation Dynamics

Modeling Information Warfare in Scale-Free Networks: Analysis of Propagation and Counter-Propagation Dynamics

Detection of Propaganda in Information Warfare using Deep Learning

Mathematical and Computer Modeling of a Dynamic System for Effectively Combating Disinformation

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