Evaluation framework for deepfake speech detection: a comparative study of state-of-the-art deepfake speech detectors
Abstract The proliferation of deepfake speech poses a significant threat to cybersecurity, from manipulating political speeches and impersonating public figures to spoofing voice biometric systems. The increasing sophistication of adversaries increases the necessity of deploying adaptive detection m...
Saved in:
| Main Authors: | Anton Firc, Kamil Malinka, Petr Hanáček |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2025-08-01
|
| Series: | Cybersecurity |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s42400-024-00346-1 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Explainability-driven adversarial robustness assessment for generalized deepfake detectors
by: Lorenzo Cirillo, et al.
Published: (2025-08-01) -
Partial Fake Speech Attacks in the Real World Using Deepfake Audio
by: Abdulazeez Alali, et al.
Published: (2025-02-01) -
Robust deepfake detection method based on siamese network
by: LIN Shanhe
Published: (2024-04-01) -
Deepfake Media Forensics: Status and Future Challenges
by: Irene Amerini, et al.
Published: (2025-02-01) -
ENHANCING EXPLAINABILITY IN DEEPFAKE DETECTION WITH GRAPH ATTENTION NETWORKS
by: Aleksandr S. Pikul, et al.
Published: (2025-05-01)