---
license: mit
language:
- en
- ru
tags:
- data-leakage
- distribution shift
- multimodal
- membership inference attack
---
# FiMMIA: scaling semantic perturbation-based membership inference across modalities
This repository contains an implementation of **F**i**MMIA** - a modular **F**ramework for **M**ultimodal **M**embership **I**nference **A**ttacks (FiMMIA)

## Description
The system is the first collection of models and pipelines for membership inference attacks against multimodal large language models, built initially with a priority for the Russian language, and extendable to any other language or dataset. 
Pipeline supports different modalities: **Video**, Audio and Image. In our experiments, we focus on [MERA datasets](https://github.com/MERA-Evaluation/MERA), however, the model can be used to other languages. 

We support models for **Video** (this), [Image](https://huggingface.co/ai-forever/FiMMIA-Image) and [Audio](https://huggingface.co/ai-forever/FiMMIA-Audio) modalities.

Training and inference code can be obtained [here](https://github.com/ai-forever/data_leakage_detect).