Trustworthy Media Verification Through AI Forensics & C2PA Provenance
Coach Name
Juan Juan
EU Organization
Truebees Srl (Italy)
Members
- Giulia Boato
- Daniele Miorandi
- Andrea Montibeller
- Luisa Verdoliva
US Organization
Purdue University – VIPER Lab (USA)
Members
- Edward Delp
Project Overview
DeepShield addresses one of the most urgent digital challenges of our time: ensuring the authenticity of images in an era dominated by deepfakes, AI-generated content, and rapid social-media dissemination.
Modern generative models produce hyper-realistic images that become even harder to detect once they are compressed, resized, or filtered by platforms such as Facebook, X, and Telegram. DeepShield responds to this problem with a hybrid approach that combines:
- AI-based deepfake detection resilient to social-media laundering,
- C2PA-compliant provenance verification,
- A unified trust scoring engine, and
- Open datasets + benchmarking tools that strengthen transparency and reproducibility.
Through a strong EU–US collaboration, the project produced new datasets, algorithms, open-source tools, and platform-ready verification workflows that empower journalists,
Methods and approaches
Robust Deepfake Detection Surviving Social-Media Degradation
DeepShield developed Cantaloupe, a custom deepfake detector based on a modified ResNet50 with prototype learning.
It was trained on 160,000 images and tested on 100,000 images—both pristine and social-network-processed—and consistently exceeded 85% accuracy and recall across all classes and platforms.
C2PA Provenance Pipeline + Rule-Based Trustworthiness Scoring
The team implemented a full C2PA validation workflow to evaluate:
- authenticity of manifests,
- signature validity,
- tampering evidence,
- generative AI origins, and
- multi-manifest history.
A transparent scoring engine translates these signals into a human-interpretable trust score, integrated into the Truebees platform.
Key Achievements
DeepShield Dataset: 100,000 images (50k diffusion, 30k GAN, 20k real), including 30,000 images shared through Facebook, X, Telegram, providing unmatched real-world conditions.
Cantaloupe detector: Accuracy & recall ≥ 0.85 across all generators and sharing modes.
C2PA verification + scoring engine: 100% coverage on test dataset; fine-grained validity classification.
Unified verification workflow integrated in the Truebees platform (AI + provenance → combined trust score).
Open Benchmarking Library: Five state-of-the-art deepfake detectors with reproducible pipelines.
ITASpoof dataset: 1M+ real & synthetic Italian voice samples (under embargo).
62 structured interviews with journalists, users, analysts, and stakeholders.
19 LinkedIn posts, 23,502 impressions, and 10 dissemination events reaching 705 people.
Impact & Results
Scientific Impact
DeepShield produced:
- Two peer-reviewed publications (ACM IH&MMSec 2025; Deepfake Forensics Workshop 2025).
- Three open datasets/libraries (DeepShield, ITASpoof, Deepfake Detectors Library).
- Novel contributions to cross-platform robustness, compression-aware detection, and multimodal forensics.
Societal Impact
The project strengthens public trust by:
- equipping journalists, citizens, and institutions with transparent verification tools;
- supporting media literacy around synthetic content;
- aligning with EU AI Act, Digital Services Act, and global provenance standards.
Economic & Industrial Impact
DeepShield provides validated components that can be integrated into:
- newsrooms,
- forensic labs,
- online platforms,
- enterprise safety systems.
The dataset and open-source library reduce R&D costs for industry.
A new early-stage researcher position was created through the programme.
EU–US Collaboration
The partnership with Purdue University delivered:
- joint datasets (image + speech),
- joint publication (IEEE Security & Privacy Magazine submission),
- a 5-month visiting-researcher exchange,
- a full-team scientific meeting in Volterra.
The collaboration will continue with new papers and research directions.
Publications and Open-Source Contributions
- DeepShield Dataset (100k images): Zenodo link provided in report.
- Open Benchmarking Library: GitHub – 5 deepfake detectors with reproducible pipelines.
- ITASpoof speech dataset (to be released after embargo).
- Two scientific publications + one joint submission to IEEE Security & Privacy Magazine.
- C2PA provenance verification pipeline and scoring engine.
- Demonstrations, dashboards, datasets, and architecture documentation.
Future directions