Digital watermarking as an adversarial attack on medical image analysis with deep learning


Abstract

Summary:

The paper discusses the use of digital watermarking as a potential adversarial attack on medical image analysis with deep learning, highlighting the risks posed by the massive use of watermarks for security reasons.
Categories

Categories

  • Cognitive function and memory: The paper discusses the use of Deep Neural Networks (DNNs) in medical image analysis, which involves cognitive function and memory.
  • Education and learning: The paper contributes to the field of education and learning by proposing a new category of adversarial attacks named watermarking attacks.
  • Phototherapy: The paper discusses digital watermarking, a form of phototherapy, as a potential adversarial attack on medical image analysis with deep learning.
Authors

Author(s)

KD Apostolidis, GA Papakostas
Publication Date

Publication Year:

2022
Citations

Number of Citations:

12