Publications

@article{matilla_color_2018,

title = {Color SIFT descriptors to categorize illegal activities in images of onion domains},

author = {David Matilla and Víctor González-Castro and Laura Fernández-Robles and Eduardo Fidalgo and Wesam Al-Nabki},

url = {https://scholar.google.es/citations?view_op=view_citation&hl=en&user=4jZgNVkAAAAJ&cstart=20&pagesize=80&sortby=title&citation_for_view=4jZgNVkAAAAJ:RHpTSmoSYBkC},

year  = {2018},

date = {2018-01-01},

urldate = {2018-01-01},

journal = {Actas de las XXXIX Jornadas de Automática, Badajoz, 5-7 de Septiembre de 2018},

abstract = {This paper explores identifying illegal domains on the Tor darknet based on their visual content. After crawling 500 hidden services and categorizing their images into five illegal categories, a classifier was trained using the Bag of Visual Words (BoVW) model with SIFT descriptors. Since SIFT only works with grayscale images, color-SIFT variants (HSV-SIFT, RGB-SIFT) were tested. The results show that color-SIFT descriptors, particularly HSV-SIFT, outperform traditional SIFT, achieving an accuracy of 59.44%, compared to SIFT's 57.52%.},

note = {Publisher: Universidad de Extremadura},

keywords = {Dark Web, Image classification, TOR},

pubstate = {published},

tppubtype = {article}

}

@article{joshi_extractive_2018,

title = {Extractive Text Summarization in Dark Web: A Preliminary Study},

author = {Akanksha Joshi and Eduardo Fidalgo and Enrique Alegre and Wesam Al-Nabki},

url = {https://scholar.google.es/citations?view_op=view_citation&hl=es&user=yATJZvcAAAAJ&cstart=20&pagesize=80&sortby=title&citation_for_view=yATJZvcAAAAJ:iH-uZ7U-co4C},

year  = {2018},

date = {2018-01-01},

urldate = {2018-01-01},

journal = {International Conference of Applications of Intelligent Systems},

abstract = {This paper explores automatic text summarization applied to illegal content extracted from onion websites on the Tor network. The goals include evaluating the feasibility of summarizing such content, comparing summarization methods, and introducing a new dataset called "OWIDSumm," which contains manually curated summaries for 60 documents related to illicit services.},

keywords = {Dark Web, Text classification, TOR Network},

pubstate = {published},

tppubtype = {article}

}