Results 81 to 90 of about 1,097 (171)

Neural Network Ensemble Method for Deepfake Classification Using Golden Frame Selection

Big Data and Cognitive Computing
Deepfake technology poses significant threats in various domains, including politics, cybersecurity, and social media. This study uses the golden frame selection technique to present a neural network ensemble method for deepfake classification.
Khrystyna Lipianina-Honcharenko, Nazar Melnyk, Andriy Ivasechko, Mykola Telka, Oleg Illiashenko   +4 more
doaj   +1 more source

Robust Sequential DeepFake Detection

International Journal of Computer Vision
Since photorealistic faces can be readily generated by facial manipulation technologies nowadays, potential malicious abuse of these technologies has drawn great concerns. Numerous deepfake detection methods are thus proposed. However, existing methods only focus on detecting one-step facial manipulation.
Rui Shao 0001, Tianxing Wu 0002, Ziwei Liu 0002   +2 more
openaire   +2 more sources

Deepfake detection: critical review of state-of-the-art approaches and future perspectives

Discover Applied Sciences
In recent years, the advancement of technology, particularly in domains such as AI, machine learning, and deep learning, has fostered the development of novel tools for altering visual media, including images, audios, and videos.
B. C. Soundarya, H. L. Gururaj
doaj   +1 more source

Penerapan ResNeXt dan Long Short-Term Memory untuk Deteksi Video Deepfake

JISKA (Jurnal Informatika Sunan Kalijaga)
Deepfake is a form of facial manipulation in videos that utilizes artificial intelligence-based models to generate highly realistic visual content. The increasing spread of Deepfake has the potential to cause misinformation, manipulate public opinion ...
Chalifa Chazar, Firhan Hafiansyah, Milda Gustiana Husada, Uung Ungkawa, Rizka Milandga Milenio   +4 more
doaj   +1 more source

Real time detection of deepfakes using the efficient Swin attention network with global and local facial features

Discover Artificial Intelligence
The rapid advancement of deepfake generation techniques has exposed critical limitations in existing deepfake detection methods, particularly their inability to simultaneously achieve high detection accuracy and real-time efficiency across diverse ...
Muhammad Javed, Dezhi Han, Fida Hussain Dahri, Teerath Kumar, Jameel Ahmed Bhutto, Ashfaque Khowaja   +5 more
doaj   +1 more source

Human Performance in Deepfake Detection: A Systematic Review

Human Behavior and Emerging Technologies
Deepfakes refer to a wide range of computer-generated synthetic media, in which a person’s appearance or likeness is altered to resemble that of another.
Klaire Somoray, Dan J. Miller, Mary Holmes   +2 more
doaj   +1 more source

Ensemble-Based Biometric Verification: Defending Against Multi-Strategy Deepfake Image Generation

Computers
Deepfake images, synthetic images created using digital software, continue to present a serious threat to online platforms. This is especially relevant for biometric verification systems, as deepfakes that attempt to bypass such measures increase the ...
Hilary Zen, Rohan Wagh, Miguel Wanderley, Gustavo Bicalho, Rachel Park, Megan Sun, Rafael Palacios, Lucas Carvalho, Guilherme Rinaldo, Amar Gupta   +9 more
doaj   +1 more source

Detection of Deepfake Environmental Audio

2024 32nd European Signal Processing Conference (EUSIPCO)
With the ever-rising quality of deep generative models, it is increasingly important to be able to discern whether the audio data at hand have been recorded or synthesized. Although the detection of fake speech signals has been studied extensively, this is not the case for the detection of fake environmental audio.
Hafsa Ouajdi, Oussama Hadder, Modan Tailleur, Mathieu Lagrange, Laurie M. Heller   +4 more
openaire   +3 more sources

Speech DF Arena: A Leaderboard for Speech DeepFake Detection Models

IEEE Open Journal of Signal Processing
Parallel to the development of advanced deepfake audio generation, audio deepfake detection has also seen significant progress. However, a standardized and comprehensive benchmark is still missing. To address this, we introduce Speech DeepFake (DF) Arena,
Sandipana Dowerah, Atharva Kulkarni, Ajinkya Kulkarni, Hoan My Tran, Joonas Kalda, Artem Fedorchenko, Benoit Fauve, Damien Lolive, Tanel Alumae, Mathew Magimai.-Doss   +9 more
doaj   +1 more source

A Multifaceted Deepfake Prevention Framework Integrating Blockchain, Post-Quantum Cryptography, Hybrid Watermarking, Human Oversight, and Policy Governance

Computers
Deepfake technology, driven by advances in artificial intelligence (AI) and deep learning (DL), has become one of the foremost threats to digital trust and the authenticity of information.
Mohammad Alkhatib
doaj   +1 more source