RAT: Reference-Augmented Training for ASV Anti-Spoofing

We introduce a spoofing countermeasure architecture conditioned on speaker-reference recordings, but observe that it converges to a solution that effectively ignores the reference during inference. Surprisingly, training with a reference channel induces invariance that improves deepfake detection...

DeepFake Forensics AI: A Multi-Modal Detection and Blockchain-Anchored Evidence Management Platform

The proliferation of AI-generated synthetic media poses a critical threat to the integrity of digital evidence in legal and forensic contexts. Existing deepfake detection systems typically address a single modality and provide no mechanism for tamper-proof evidence preservation. We present DeepFa...

Brinker Introduces a Novel Approach to Deepfake Detection

WILMINGTON, Delaware, 29th April 2026, CyberNewswire...

ForensicFlow: A Tri-Modal Adaptive Network for Robust Deepfake Detection

Deepfakes generated by advanced GANs and autoencoders severely threaten information integrity and societal stability. Single-stream CNNs fail to capture multi-scale forgery artifacts across spatial, texture, and frequency domains, limiting robustness and generalization. We introduce the...

Decoupling Bias, Aligning Distributions: Synergistic Fairness Optimization for Deepfake Detection

Fairness is a core element in the trustworthy deployment of deepfake detection models, especially in the field of digital identity security. Biases in detection models toward different demographic groups, such as gender and race, may lead to systemic misjudgments, exacerbating the digital divide...

Enhanced Deep Learning DeepFake Detection Integrating Handcrafted Features

The rapid advancement of deepfake and face swap technologies has raised significant concerns in digital security, particularly in identity verification and onboarding processes. Conventional detection methods often struggle to generalize against sophisticated facial manipulations. This study...

Two Views, One Truth: Spectral and Self-Supervised Features Fusion for Robust Speech Deepfake Detection

Recent advances in synthetic speech have made audio deepfakes increasingly realistic, posing significant security risks. Existing detection methods that rely on a single modality, either raw waveform embeddings or spectral based features, are vulnerable to non spoof disturbances and often overfit...

Unmasking Synthetic Realities in Generative AI: a Comprehensive Review of Adversarially Robust Deepfake Detection Systems

The rapid advancement of Generative Artificial Intelligence has fueled deepfake proliferation-synthetic media encompassing fully generated content and subtly edited authentic material-posing challenges to digital security, misinformation mitigation, and identity preservation. This systematic revi...

Towards Trustworthy AI: Secure Deepfake Detection Using CNNs and Zero-Knowledge Proofs

In the era of synthetic media, deepfake manipulations pose a significant threat to information integrity. To address this challenge, we propose TrustDefender, a two-stage framework comprising i a lightweight convolutional neural network CNN that detects deepfake imagery in real-time extended...

LENS-DF: Deepfake Detection and Temporal Localization for Long-Form Noisy Speech

This study introduces LENS-DF, a novel and comprehensive recipe for training and evaluating audio deepfake detection and temporal localization under complicated and realistic audio conditions. The generation part of the recipe outputs audios from the input dataset with several critical...

Think Twice Before Adaptation: Improving Adaptability of DeepFake Detection Via Online Test-Time Adaptation

Whitepaper called Think Twice Before Adaptation: Improving Adaptability Of DeepFake Detection Via Online Test-Time Adaptation...

GitHub’s Deepfake Porn Crackdown Still Isn’t Working

Over a dozen programs used by creators of nonconsensual explicit images have evaded detection on the developer platform, WIRED has found...

Tackling AI threats. Advanced DFIR methods and tools for deepfake detection

TL; DR AI-generated documents, videos and more pose significant challenges for DFIR DFIR teams can harness innovative detection strategies and tooling Digital fingerprinting and watermarking, AI-powered and behavioural analyses Hardware-based forensics and image-specific forensic techniques...

Eliminating AI Deepfake Threats: Is Your Identity Security AI-Proof?

Artificial Intelligence AI has rapidly evolved from a futuristic concept to a potent weapon in the hands of bad actors. Today, AI-based attacks are not just theoretical threats—they're happening across industries and outpacing traditional defense mechanisms. The solution, however, is not...

Detecting Deepfake Picture Editing

"Markpainting" is a clever technique to watermark photos in such a way that makes it easier to detect ML-based manipulation: An image owner can modify their image in subtle ways which are not themselves very visible, but will sabotage any attempt to inpaint it by adding visible information...

Deepfakes or not: new GAN image stirs up questions about digital fakery

Subversive deepfakes that enter the party unannounced, do their thing, then slink off into the night without anybody noticing are where it’s at. Easily debunked clips of Donald Trump yelling THE NUKES ARE UP or something similarly ludicrous are not a major concern. We’ve already dug into why that...

Deepstar: An Open Source Deepfake Detection Toolkit

Deepfake as a technology has been recently since June 2016 seen in the wild and has caused concern with a lot of people. A recently released tool – Deepstar is now here to help you detect deepfake videos. Where does this come into picture from a security point of view? According to me, it directl...

Facebook, Microsoft Challenge Industry to Detect, Prevent ‘Deepfakes’

Facebook, Microsoft and a number of universities have joined forces to sponsor a contest promoting research and development to combat deepfakes, or videos altered through artificial intelligence AI to mislead viewers. The two tech giants—along with the Partnership on AI and academics from Cornell...