Deepfakes generation and detection: State-of-the-art, open challenges, countermeasures, and way forward

M Masood, M Nawaz, KM Malik, A Javed, A Irtaza… - Applied …, 2023‏ - Springer
Easy access to audio-visual content on social media, combined with the availability of
modern tools such as Tensorflow or Keras, and open-source trained models, along with …

Machine learning in digital forensics: a systematic literature review

T Nayerifard, H Amintoosi, AG Bafghi… - arxiv preprint arxiv …, 2023‏ - arxiv.org
Development and exploitation of technology have led to the further expansion and
complexity of digital crimes. On the other hand, the growing volume of data and …

Deep fake video detection using transfer learning approach

S Suratkar, F Kazi - Arabian Journal for Science and Engineering, 2023‏ - Springer
The usage of the internet as a fast medium for spreading fake news reinforces the
requirement of computational utensils in order to fight for it. Fake videos also called deep …

Deepfakes: evolution and trends

R Gil, J Virgili-Gomà, JM López-Gil, R García - Soft Computing, 2023‏ - Springer
This study conducts research on deepfakes technology evolution and trends based on a
bibliometric analysis of the articles published on this topic along with six research questions …

STB-VMM: Swin transformer based video motion magnification

R Lado-Roigé, MA Pérez - Knowledge-Based Systems, 2023‏ - Elsevier
The goal of video motion magnification techniques is to magnify small motions in a video to
reveal previously invisible or unseen movement. Its uses extend from bio-medical …

Datasets, clues and state-of-the-arts for multimedia forensics: An extensive review

A Yadav, DK Vishwakarma - Expert Systems with Applications, 2024‏ - Elsevier
With the large chunks of social media data being created daily and the parallel rise of
realistic multimedia tampering methods, detecting and localising tampering in images and …

Rethinking data infrastructure and its ethical implications in the face of automated digital content generation

MJ Israel, A Amer - AI and Ethics, 2023‏ - Springer
Recent AI developments have made it possible for AI to auto-generate content—text, image,
and sound. Highly realistic auto-generated content raises the question of whether one can …

A CNN-based misleading video detection model

X Li, X **ao, J Li, C Hu, J Yao, S Li - Scientific Reports, 2022‏ - nature.com
Videos, especially short videos, have become an increasingly important source of
information in these years. However, many videos spread on video sharing platforms are …

Deepfake video detection by combining convolutional neural network (cnn) and recurrent neural network (rnn)

Y Al-Dhabi, S Zhang - 2021 IEEE international conference on …, 2021‏ - ieeexplore.ieee.org
Nowadays, people are facing an emerging problem called deepfake videos. These videos
were created using deep learning technology. Some are created just for fun, while others …

SRTNet: a spatial and residual based two-stream neural network for deepfakes detection

D Zhang, W Zhu, X Ding, G Yang, F Li, Z Deng… - Multimedia Tools and …, 2023‏ - Springer
With the rapid development of Internet technology, the Internet is full of false information, and
Deepfakes, as a kind of visual forgery content, brings the greatest impact to people. The …