Automated Research Integrity Analysis Platform
A unified AI-powered platform that integrates three independent forensic analysis systems to detect image manipulation, deepfakes, and paper mill activity in scientific publications — from pixel-level forgery maps to metadata anomaly detection.
ARIA brings together three independent research-grade forensic pipelines under one multi-user web interface. Each system addresses a distinct aspect of research integrity: image manipulation within papers, deepfake detection in figures, and paper mill identification through metadata patterns.
Researchers upload their scientific articles or figures, select the appropriate analysis system and modules, and receive rich visual results — activation maps, provenance graphs, anomaly scores, and natural-language forensic reports — in a single, downloadable ZIP package.
Pixel-level detection of copy-move, splicing and panel duplication artefacts in scientific figures
Multimodal LLM analysis generating natural-language descriptions of detected manipulation artefacts
Directed graph analysis tracing the origin and history of scientific figures across publications
Machine learning detection of paper mill patterns in metadata, embeddings and citation graphs
Each system runs in its own containerised environment and can be executed independently. Select the system that matches your analysis goal.
Detects image fabrication, copy-move forgeries, figure duplication and provenance inconsistencies in academic PDFs. Based on the sciint pipeline (Moreira et al., Nature Sci. Rep. 2022).
A three-stage pipeline combining deep-learning manipulation detection, multimodal LLM forensic reporting and pixel-level inconsistency mapping for scientific images.
Detects anomalies in scientific papers indicative of paper mill activity by extracting metadata, generating transformer embeddings and applying unsupervised anomaly detection.
Contact the administrator to request an account on the platform.
Upload your paper PDFs or images, select the forensic system, and choose analysis modules.
Start the pipeline with one click. Monitor real-time execution logs as each module completes.
Browse visual results in the interface and download a complete ZIP package of all outputs.
ARIA is a research platform operated at IFSP Campus Itapetininga in collaboration with RECOD/Unicamp. Access is restricted to researchers, students and institutional partners. To request an account, please contact the platform administrator.
The platform integrates three independent systems, each with its own academic attribution:
Hardware notice: The SciForensics pipeline (FakeScope stage) requires a GPU with ≥ 7 GB VRAM. Other systems run on CPU-only hardware.
To request access or discuss research collaborations, please contact the platform administrator directly by email. Include a brief description of your research context and intended use of the platform.