Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Perceptual Hashing applied to Tor domains recognition   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 support this task, we introduce Frequency-Dominant
Neighborhood Structure (F-DNS), a new perceptual hashing method for
automatically classifying domains by their screenshots. First, we evaluated
F-DNS using images subject to various content preserving operations. We
compared them with their original images, achieving better correlation
coefficients than other state-of-the-art methods, especially in the case of
rotation. Then, we applied F-DNS to categorize Tor domains using the Darknet
Usage Service Images-2K (DUSI-2K), a dataset with screenshots of active Tor
service domains. Finally, we measured the performance of F-DNS against an image
classification approach and a state-of-the-art hashing method. Our proposal
obtained 98.75% accuracy in Tor images, surpassing all other methods compared.

16
The categories of this paper are: stat
2
The categories of this paper are: math
0
The categories of this paper are: hep-ph
34
The categories of this paper are: chem-ph
31
The categories of this paper are: ao-sci
33
The categories of this paper are: plasm-ph
7
The categories of this paper are: hep-th
35
The categories of this paper are: mtrl-th
37
The categories of this paper are: supr-con
10
The categories of this paper are: q-bio
25
The categories of this paper are: patt-sol
4
The categories of this paper are: cond-mat
28
The categories of this paper are: alg-geom
13
The categories of this paper are: quant-ph
20
The categories of this paper are: acc-phys
8
The categories of this paper are: hep-ex