Paul Eckloff was a US Secret Service Agent for 23 years. Today we discuss how deep fake videos increase security risks. Topics include: artificial intelligence risks in cyber, new ways to reduce risk of deep fakes, how are deep fakes made, how are deep fake videos made, how are audio deep fakes made, and how is ai making it harder to detect deep fakes.
Catch Video Episode with Sample Deep Fakes here: https://youtu.be/1yFFK6uHt0I?si=qP9F1_uIZ7q6qGSS
Takeaways
- Sample deepfakes are played. Can you tell? Over 85% of those tested could not.
- Deepfake technology, created using techniques like GANs, diffusion models, and VAEs, can convincingly substitute one person's face or voice with another's.
- The advancement of deepfake technology poses risks such as impersonating executives, enhancing social engineering campaigns, avoiding detection in malware, and conducting reconnaissance for future attacks.
- The widespread availability and low cost of deepfake technology make it accessible to both legitimate businesses and threat actors, increasing the threat surface for organizations.
- The potential for deepfakes to manipulate and deceive individuals, especially children, is a grave concern.
Chapters
- 00:00 Introduction to Deepfake Technology and its Impact
- 03:27 The Challenges of Detecting Deepfakes
- 08:04 The Erosion of Trust: Seeing is No Longer Believing
- 11:31 The Advancement of Deepfake Technology
- 26:53 The Malicious Uses of Deepfake Technology
- 36:17 The Risks of Deepfake Technology
- 37:42 Consequences of Deepfakes
- 40:38 Limitations of Deepfake Detec
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