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Preprint Technical Note Version 1 Preserved in Portico This version is not peer-reviewed

Computational Intelligence Assisted Less-Expensive Privacy-Preserving Optimization in Audio-Video Content

Version 1 : Received: 10 April 2024 / Approved: 11 April 2024 / Online: 17 April 2024 (02:09:11 CEST)

How to cite: Parnianifard, A. Computational Intelligence Assisted Less-Expensive Privacy-Preserving Optimization in Audio-Video Content. Preprints 2024, 2024040807. https://doi.org/10.20944/preprints202404.0807.v1 Parnianifard, A. Computational Intelligence Assisted Less-Expensive Privacy-Preserving Optimization in Audio-Video Content. Preprints 2024, 2024040807. https://doi.org/10.20944/preprints202404.0807.v1

Abstract

This research study focuses on addressing practical optimization challenges in audio-visual content using advanced computational intelligence methods, with a specific emphasis on privacy-preserving issues. The research will be presented as a proposal and can be conducted based on the provided ideas. Computational intelligence encompasses various approaches, including evolutionary algorithms, learning methods, fuzzy systems, and neural networks, which have become essential tools for tackling complex engineering optimization problems due to computational expenses, dimensional complexities, and interdisciplinary integration. The research objectives include a thorough investigation of optimization challenges in audio-visual content, the delineation of problem characteristics, and the development of relevant methodologies based on these specifications. The main goals of the study, titled "Advanced Computational Intelligence Assisted Less-Expensive Privacy-Preserving Optimization," encompass the development of a metamodel-based learning algorithm integrated with evolutionary computation for privacy-preserving optimization, less-expensive signal watermarking optimization using hybrid metamodeling and evolutionary algorithms, and a closed-loop robust intelligent PID control system applied in real-time dynamic signal watermarking. Additional objectives may be defined as the research progresses and further background review is conducted.

Keywords

Computational Intelligence; Privacy-Preserving Optimization; Audio-Visual Content; Evolutionary Computation; Metamodel-Based Learning; Signal Watermarking

Subject

Engineering, Industrial and Manufacturing Engineering

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