# Carl-Hauser -- Open Source Image Matching Algorithms Benchmarking Framework

## TL;DR

This paper introduces an open-source benchmarking framework for image matching algorithms, enabling security analysts to evaluate and compare algorithms on datasets of phishing and onion websites for improved classification and search tasks.

## Contribution

The paper presents a novel open-source framework for benchmarking image matching algorithms using real-world datasets of phishing and onion websites.

## Key findings

- Framework supports evaluation on diverse datasets
- Open-Data datasets facilitate reproducibility
- Enhances security analysts' ability to select effective algorithms

## Abstract

Security analysts need to classify, search and correlate numerous images. Automatic classification tools improve the efficiency of such tasks. Many Image-Matching algorithms are presented in the litterature. The present paper introduces and provides a Open-Source benchmarking and evaluation tool for these algorithms. Is this paper, the framework evaluates algorithms on illustrative datasets, which are constituted of phishing and onion websites. Datasets are provided as Open-Data.