35 citations · 82 across the 12 of their papers we have counts for
12 papers
AdaptPrompt: Parameter-Efficient Adaptation of VLMs for Generalizable Deepfake Detection
Yichen Jiang, Mohammed Talha Alam, Sohail Ahmed Khan +2
Detectors of AI-generated images tend to inherit the biases of the data they are trained on: models fitted to GAN imagery learn to treat GAN-specific artifacts as the very definiti…
CLIPping the Deception: Adapting Vision-Language Models for Universal Deepfake Detection
Sohail Ahmed Khan, Duc-Tien Dang-Nguyen
The recent advancements in Generative Adversarial Networks (GANs) and the emergence of Diffusion models have significantly streamlined the production of highly realistic and widely…
Online Multimedia Verification with Computational Tools and OSINT: Russia-Ukraine Conflict Case Studies
Sohail Ahmed Khan, Jan Gunnar Furuly, Henrik Brattli Vold +2
This paper investigates the use of computational tools and Open-Source Intelligence (OSINT) techniques for verifying online multimedia content, with a specific focus on real-world…
Detecting Out-of-Context Image-Caption Pairs in News: A Counter-Intuitive Method
Eivind Moholdt, Sohail Ahmed Khan, Duc-Tien Dang-Nguyen
The growth of misinformation and re-contextualized media in social media and news leads to an increasing need for fact-checking methods. Concurrently, the advancement in generative…
Deepfake Detection: A Comparative Analysis
Sohail Ahmed Khan, Duc-Tien Dang-Nguyen
This paper present a comprehensive comparative analysis of supervised and self-supervised models for deepfake detection. We evaluate eight supervised deep learning architectures an…
Grand Challenge On Detecting Cheapfakes
Duc-Tien Dang-Nguyen, Sohail Ahmed Khan, Cise Midoglu +3
Cheapfake is a recently coined term that encompasses non-AI ("cheap") manipulations of multimedia content. Cheapfakes are known to be more prevalent than deepfakes. Cheapfake media…
Hybrid Transformer Network for Deepfake Detection
Sohail Ahmed Khan, Duc-Tien Dang-Nguyen
Deepfake media is becoming widespread nowadays because of the easily available tools and mobile apps which can generate realistic looking deepfake videos/images without requiring a…
ACM Multimedia Grand Challenge on Detecting Cheapfakes
Shivangi Aneja, Cise Midoglu, Duc-Tien Dang-Nguyen +5
Cheapfake is a recently coined term that encompasses non-AI (``cheap'') manipulations of multimedia content. Cheapfakes are known to be more prevalent than deepfakes. Cheapfake med…
Video Transformer for Deepfake Detection with Incremental Learning
Sohail A. Khan, Hang Dai
Face forgery by deepfake is widely spread over the internet and this raises severe societal concerns. In this paper, we propose a novel video transformer with incremental learning…
Adversarially robust deepfake media detection using fused convolutional neural network predictions
Sohail Ahmed Khan, Alessandro Artusi, Hang Dai
Deepfakes are synthetically generated images, videos or audios, which fraudsters use to manipulate legitimate information. Current deepfake detection systems struggle against unsee…
Phishing Attacks and Websites Classification Using Machine Learning and Multiple Datasets (A Comparative Analysis)
Sohail Ahmed Khan, Wasiq Khan, Abir Hussain
Phishing attacks are the most common type of cyber-attacks used to obtain sensitive information and have been affecting individuals as well as organisations across the globe. Vario…
Analysing the impact of global demographic characteristics over the COVID-19 spread using class rule mining and pattern matching
Wasiq Khan, Abir Hussain, Sohail Ahmed Khan +3
Since the coronavirus disease (COVID-19) outbreak in December 2019, studies have been addressing diverse aspects in relation to COVID-19 and Variant of Concern 202012/01 (VOC 20201…