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AI-Based Metaheuristics for Information Security and Digital Media

 
Edition number: 1
Publisher: Chapman and Hall
Date of Publication:
 
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Short description:

This book examines the latest developments in AI-based metaheuristics algorithms with applications in information security for digital media. It highlights the importance of several security parameters, their analysis, and validations for different practical applications.

Long description:

This book examines the latest developments in Artificial Intelligence (AI)-based metaheuristics algorithms with applications in information security for digital media. It highlights the importance of several security parameters, their analysis, and validations for different practical applications. Drawing on multidisciplinary research including computer vision, machine learning, artificial intelligence, and modified/newly developed metaheuristics algorithms, it will enhance information security for society. It includes state-of-the-art research with illustrations and exercises throughout.


Table of Contents:

Preface. About the Editors. Contributors. 1 Use of artificial intelligence and blockchain technologies in detecting and curbing fake news in journalism. 2 Blockchain technology
-based fake news detection: Applications and future research directions. 3 Deep learning
-based intelligent systems for audio abuse prediction: A survey. 4 A comprehensive review of toxicity analysis using deep learning techniques. 5 Literature review on zero
-knowledge proof and its applications. 6 Machine learning
-based algorithmic comparison for fake news identification. 7 A comprehensive review of classical and deep learning
-based time series models. 8 Use of technologies in media and communication: Interventions of artificial intelligence in mitigating fake news on social media. 9 Robust color image watermarking using IWT and ensemble model with PCA
-based statistical feature reduction. Index.