The course Deepfakes and Disinformation: Identification and Prevention using AI offers specialised training in the analysis, detection and prevention of content manipulated using artificial intelligence. Through a technical and ethical approach, participants will understand how deepfakes, how the digital disinformation and which tools based on Forensic AI exist to verify the authenticity of audiovisual content. In addition, the following will be addressed technology and cybersecurity strategies aimed at safeguarding the integrity of information and strengthening trust in digital media.
Cross-cutting
AI Academy
8 am
Deepfakes and disinformation: identification and prevention using AI
AI Academy
8 am
Introduction
Objectives
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Understanding the technical and conceptual principles behind the deepfakes and its relationship with the digital disinformation.
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To analyse the ethical, social and communicative impact of the summary content.
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Finding out about the main ones techniques and algorithms for detecting deepfakes AI-based.
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Apply forensic methods for the verification of manipulated images, audio and video.
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Design prevention, authentication and early warning strategies in the face of media manipulation.
Table of Contents
TEACHING UNIT 1: THE BASICS OF DEEPFAKES AND MISINFORMATION
1. Definition and distinction between deepfakes and cheapfakes
2. Technical principles behind the creation of deepfakes
3. The digital disinformation ecosystem
4. The evolution of voice and image synthesis technology
TEACHING UNIT 2. FORENSIC ANALYSIS FOR THE IDENTIFICATION OF SYNTHETIC CONTENT
1. Visual and auditory techniques for detecting anomalies in deepfakes
2. Introduction to the analysis of metadata in audio and video files
3. AI algorithms for the automated detection of deepfakes
4. Identification of facial and vocal manipulation patterns
5. Forensic analysis tools for verifying the authenticity of media
TEACHING UNIT 3: TECHNOLOGICAL AND SAFETY STRATEGIES FOR PREVENTION
1. Methods for identity verification and digital content authentication
2. Use of digital watermarks and cryptographic signatures to ensure media integrity
3. AI in the development of fact-checking platforms
4. Early warning and real-time detection systems on online platforms
5. Self-regulation on social media and technological responsibility
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