most citedClassifying Suspicious Content in Tor Darknet

1 citations · 1 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2021

State of the Art: Face Recognition

Rubel Biswas, Pablo Blanco-Medina

Working with Child Sexual Exploitation Material (CSEM) in forensic applications might be benefited from the progress in automatic face recognition. However, discriminative parts of…

cs.CV2021

State of the Art: Image Hashing

Rubel Biswas, Pablo Blanco-Medina

Perceptual image hashing methods are often applied in various objectives, such as image retrieval, finding duplicate or near-duplicate images, and finding similar images from large…

cs.CV2020

Perceptual Hashing applied to Tor domains recognition

Rubel Biswas, Roberto A. Vasco-Carofilis, Eduardo Fidalgo Fernandez +2

The Tor darknet hosts different types of illegal content, which are monitored by cybersecurity agencies. However, manually classifying Tor content can be slow and error-prone. To s…

cs.CV20201 cited

Classifying Suspicious Content in Tor Darknet

Eduardo Fidalgo Fernandez, Roberto Andrés Vasco Carofilis, Francisco Jáñez Martino +1

One of the tasks of law enforcement agencies is to find evidence of criminal activity in the Darknet. However, visiting thousands of domains to locate visual information containing…

cs.CV2020

Classification of Industrial Control Systems screenshots using Transfer Learning

Pablo Blanco Medina, Eduardo Fidalgo Fernandez, Enrique Alegre +3

Industrial Control Systems depend heavily on security and monitoring protocols. Several tools are available for this purpose, which scout vulnerabilities and take screenshots from…