Deepfakes: dangers, development, and detection

Artificial Intelligence (AI), and in particular Deep Learning, have made huge advances in recent years. One of the most spectacular aspects of AI is the ability to create original content as well as manipulate existing content, for reasons that may be benign or less so.

Deepfakes mix the identity information of one individual with the expressions of another to create an artificially generated face. Deepfakes are media – images, videos, or sound clips – that have been manipulated by deep learning algorithms. Their goal is to alter the identity or perceived actions of the people depicted on the manipulated media – showing people doing or saying things they never did.

Criminals and fraudsters can use this for a wide variety of activities, such as:

  • Scamming relatives of the victim for money or personal data
  • Scamming business associates by requesting specific business-oriented actions;
  • Blackmail
  • Damaging the reputation of the victim
  • Manipulating public opinion,
  • Spreading propaganda by showing public figures in compromised situations;
  • And more

Detecting deepfakes has also become more challenging with the increase in the sophistication level of the deep learning machinery employed. The less sophisticated the deepfake, the easier it is to detect them; however this situation is changing dramatically. In fact, better deepfakes may have almost no errors. Currently, the newest approaches to deepfake detection employ deep learning neural networks to differentiate between real and deepfaked images.

To learn more about deepfakes, what they are, and what is currently being done to improve their detection, check out our TOOLS section for more detailed and interactive information.

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