Local Chapter Münich, Germany Chapter
Coordinated byGermany ,
Status: Completed
Project Duration: 27 Feb 2023 - 17 Mar 2023
Open Source resources available from this project
Project background.
Deepfakes are artificial intelligence generated or manipulated multimedia content (images, videos) that depict real people doing or saying things they never did in reality. Due to the recent advancements in architectures like Generative Adversarial Networks (GANs), deepfake generation became considerably faster and at a lower cost, presenting a significant threat to information media, politics and cyber security through spreading false information, identity theft and manipulating public opinion. Hence the necessity of having effective deepfake detection mechanisms.
The problem.
Deepfake generators have been able to produce imitations almost undetectable through human inspection. Per se, deepfake detection is one of the notable challenges of digital forensics and media security. They can be used to:
– Spread false information and manipulate public opinion.
– Defame, harass or blackmail individuals.
– Damage the credibility of media information and undermine trust.
– Spread fake news, political propaganda, and manipulate elections.
An artificial intelligence (AI) solution can help identify deepfake images with accuracy and precision.
Project goals.
Project plan.
Week 1
Research previous work and Data Collection
Week 2
Exploratory Data Analysis
Week 3
Preprocessing and Augmentation
Week 4
Model Development
Week 5
Model Training
Week 6
Model Analysis and Interpretation
Learning outcomes.
Deep Learning, GAN, CNN, team work, project management.
