Publications
2020
1.
Biswas, Rubel; Carofilis-Vasco, Andrés; Fidalgo, Eduardo; Jáñez-Martino, Francisco; Blanco-Medina, Pablo
Perceptual Hashing applied to Tor domains recognition Artículo de revista
En: arXiv preprint arXiv:2005.10090, 2020.
Resumen | Enlaces | BibTeX | Etiquetas: Cybersecurity, DCT, Deep Web, Image classification, TOR
@article{biswas_perceptual_2020-1,
title = {Perceptual Hashing applied to Tor domains recognition},
author = {Rubel Biswas and Andrés Carofilis-Vasco and Eduardo Fidalgo and Francisco Jáñez-Martino and Pablo Blanco-Medina},
url = {https://arxiv.org/abs/2005.10090},
year = {2020},
date = {2020-01-01},
urldate = {2020-01-01},
journal = {arXiv preprint arXiv:2005.10090},
abstract = {This paper introduces Frequency-Dominant Neighborhood Structure (F-DNS), a perceptual hashing method for automatically classifying Tor domains by their screenshots. F-DNS outperforms other methods, achieving better correlation coefficients, especially for rotated images. The method was tested on the Darknet Usage Service Images-2K (DUSI-2K) dataset and achieved an accuracy of 98.75%, surpassing other classification and hashing techniques.},
keywords = {Cybersecurity, DCT, Deep Web, Image classification, TOR},
pubstate = {published},
tppubtype = {article}
}
This paper introduces Frequency-Dominant Neighborhood Structure (F-DNS), a perceptual hashing method for automatically classifying Tor domains by their screenshots. F-DNS outperforms other methods, achieving better correlation coefficients, especially for rotated images. The method was tested on the Darknet Usage Service Images-2K (DUSI-2K) dataset and achieved an accuracy of 98.75%, surpassing other classification and hashing techniques.