June 18

Webinar takeaways: Deepfakes – Gefahren und Herausforderungen


My key takeaways

  • the fragmentation of the media landscape made deepfakes relevant
  • deepfakes still need a lot of training material
    • no data, no deep fake
  • voice is still an issue (delay, monotonie), but AI technology is developing fast
    • attackers may just find someone with a similar voice then trying to generate the voice artificially
  • the BSI has an eye on the development as well since ~1/2 year
  • "I swear I’m not a cat" 😀
  • most awareness trainings focus on the tools of the attackers, missing the strategy behind it
    • the effect of a deepfake depends on the context aka strategy
  • psycholocial associations help attacker to not need to fake every detail
    • WYSIATI – "what you see is all there is"
  • if we concentrate on details and are sceptic, we still have 94% probability to detect deep fakes
  • mulitmedia forensic exists since more then 20 years, eg statistical differences in images
  • FB challenge 2020: active image or video manipulation eg in the context of an attack and the automated detection rate drops to ~0%
  • fakeporn is a different technology then real time face reenactment
  • every silver bullet, like different lighting effects in both eyes of a person, will be attacked by a new technology: a cat and mouse game
  • manual detection is not a scaleable option
  • alternatives: detect the original video source or PKI for media ressources
  • driver of technological development: media companies for entertainment production
    • the dark side will adopt these developments
  • top details to spot deep fakes today
    • movements
    • voice
    • teeth
    • length variations of the neck
    • eyes (reflections, colors)


additional links


deepfake, german, social engineering

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