Results 161 to 170 of about 6,771 (199)

An integrated framework for proactive deepfake mitigation via attention-driven watermarking and blockchain-based authenticity verification. [PDF]

Sci Rep
Hajjej F, Hamid M, Alluhaidan AS.
europepmc   +1 more source

Decoding deception: state-of-the-art approaches to deep fake detection. [PDF]

Front Big Data
Hussain T, Reddy BT, Phanindra K, Terumalasetti S, Khan GA.   +4 more
europepmc   +1 more source

Explainable detection of machine generated music and early systematic evaluation. [PDF]

Sci Rep
Li Y, Sun Q, Li H, Specia L, Schuller BW.   +4 more
europepmc   +1 more source

Robust deepfake detector against deep image watermarking. [PDF]

PLoS One
Yu J, Liu X, Zan F, Peng Y.
europepmc   +1 more source

Generative AI-driven synthetic media risks in digital health: implications for telemedicine and teledentistry. [PDF]

Front Public Health
Jędrasiak K, Bijoch J.
europepmc   +1 more source

Prediction model for the dissemination of AI-generated deepfake videos in the intelligent entertainment paradigm. [PDF]

Sci Rep
Ma X, Wang J, Ji E, Wang Z.
europepmc   +1 more source

Detecting anti-forensic deepfakes with identity-aware multi-branch networks. [PDF]

Front Big Data
Zhu M, Long J.
europepmc   +1 more source

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Deepfake Detection

Proceedings of the 9th ACM International Workshop on Security and Privacy Analytics, 2023
This tutorial presents developments on the detection of Deepfakes, which are realistic images, audios and videos created using deep learning techniques. Deepfakes can be readily used for malicious purposes and pose a serious threat to privacy and security.
Md. Shohel Rana, Andrew H. Sung
openaire   +1 more source

A Survey on Speech Deepfake Detection

ACM Computing Surveys
The availability of smart devices leads to an exponential increase in multimedia content. However, advancements in deep learning have also enabled the creation of highly sophisticated Deepfake content, including speech Deepfakes, which pose a serious threat by generating realistic voices and spreading misinformation. To combat this, numerous challenges

exaly   +3 more sources

DeepFake-Adapter: Dual-Level Adapter for DeepFake Detection

International Journal of Computer Vision
IJCV 2025.
Rui Shao, Tianxing Wu, Liqiang Nie
exaly   +3 more sources