Identification of illegal forum activities inside the Dark Net

Hussein Alnabulsi; MD Rafiqul Islam

doi:10.1109/iCMLDE.2018.00015

Identification of illegal forum activities inside the Dark Net

Hussein Alnabulsi, MD Rafiqul Islam

Research output: Book chapter/Published conference paper › Conference paper › peer-review

16 Citations (Scopus)

Abstract

Cybercriminal activities in the dark web can be considered one of the critical problems for societies around the world. It is possible that cybercriminals are using the Internet for criminal activities such as: trading and buying drugs, pedophilia, hiring hitmen, forgery, piracy and terrorism. In this paper, we are high-lighting the illegal activities happening on the dark side of the Internet, in particular the dark web forums. We used the Onion Router to check the web contents that users of dark web forums are posting and discussing. This paper also examines the most common activities in the illicit subjects that users are chatting about in the dark web forums. We performed affect analysis on the dark web forums, which is useful for measuring the presence of illicit subjects such as drugs, violence, forgery and piracy. The results show that there are similarities in the subjects between the dark web forums

Original language	English
Title of host publication	2018 International Conference on Machine Learning and Data Engineering (iCMLDE)
Editors	Phill Kyu Rhee, Md Rezaul Bashar
Place of Publication	Piscataway, NJ, USA
Publisher	IEEE
Pages	22-29
Number of pages	8
ISBN (Print)	9781728104041
DOIs	https://doi.org/10.1109/iCMLDE.2018.00015
Publication status	Published - 17 Jan 2019
Event	2nd International Conference on Machine Learning and Data Engineering: iCMLDE 2018 - Western Sydney University (Parramatta campus), Sydney, Australia Duration: 03 Dec 2018 → 07 Dec 2018 http://www.2018.icmlde.net.au/ https://ieeexplore.ieee.org/xpl/conhome/8613698/proceeding (proceedings)

Conference

Conference	2nd International Conference on Machine Learning and Data Engineering
Country/Territory	Australia
City	Sydney
Period	03/12/18 → 07/12/18
Internet address	http://www.2018.icmlde.net.au/ https://ieeexplore.ieee.org/xpl/conhome/8613698/proceeding (proceedings)

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1109/iCMLDE.2018.00015

Cite this

@inproceedings{0d35fa5d2666449aa2a9a7033a1ce326,

title = "Identification of illegal forum activities inside the Dark Net",

abstract = "Cybercriminal activities in the dark web can be considered one of the critical problems for societies around the world. It is possible that cybercriminals are using the Internet for criminal activities such as: trading and buying drugs, pedophilia, hiring hitmen, forgery, piracy and terrorism. In this paper, we are high-lighting the illegal activities happening on the dark side of the Internet, in particular the dark web forums. We used the Onion Router to check the web contents that users of dark web forums are posting and discussing. This paper also examines the most common activities in the illicit subjects that users are chatting about in the dark web forums. We performed affect analysis on the dark web forums, which is useful for measuring the presence of illicit subjects such as drugs, violence, forgery and piracy. The results show that there are similarities in the subjects between the dark web forums",

keywords = "Dark web, Deep web, Surface web, Illegal forums, Tor",

author = "Hussein Alnabulsi and Islam, {MD Rafiqul}",

year = "2019",

month = jan,

day = "17",

doi = "10.1109/iCMLDE.2018.00015",

language = "English",

isbn = "9781728104041 ",

pages = "22--29",

editor = "{Kyu Rhee}, Phill and Bashar, {Md Rezaul}",

booktitle = "2018 International Conference on Machine Learning and Data Engineering (iCMLDE)",

publisher = "IEEE",

note = "2nd International Conference on Machine Learning and Data Engineering : iCMLDE 2018 ; Conference date: 03-12-2018 Through 07-12-2018",

url = "http://www.2018.icmlde.net.au/, https://ieeexplore.ieee.org/xpl/conhome/8613698/proceeding",

}

Alnabulsi, H & Islam, MDR 2019, Identification of illegal forum activities inside the Dark Net. in P Kyu Rhee & MR Bashar (eds), 2018 International Conference on Machine Learning and Data Engineering (iCMLDE). IEEE, Piscataway, NJ, USA, pp. 22-29, 2nd International Conference on Machine Learning and Data Engineering, Sydney, New South Wales, Australia, 03/12/18. https://doi.org/10.1109/iCMLDE.2018.00015

TY - GEN

T1 - Identification of illegal forum activities inside the Dark Net

AU - Alnabulsi, Hussein

AU - Islam, MD Rafiqul

PY - 2019/1/17

Y1 - 2019/1/17

N2 - Cybercriminal activities in the dark web can be considered one of the critical problems for societies around the world. It is possible that cybercriminals are using the Internet for criminal activities such as: trading and buying drugs, pedophilia, hiring hitmen, forgery, piracy and terrorism. In this paper, we are high-lighting the illegal activities happening on the dark side of the Internet, in particular the dark web forums. We used the Onion Router to check the web contents that users of dark web forums are posting and discussing. This paper also examines the most common activities in the illicit subjects that users are chatting about in the dark web forums. We performed affect analysis on the dark web forums, which is useful for measuring the presence of illicit subjects such as drugs, violence, forgery and piracy. The results show that there are similarities in the subjects between the dark web forums

AB - Cybercriminal activities in the dark web can be considered one of the critical problems for societies around the world. It is possible that cybercriminals are using the Internet for criminal activities such as: trading and buying drugs, pedophilia, hiring hitmen, forgery, piracy and terrorism. In this paper, we are high-lighting the illegal activities happening on the dark side of the Internet, in particular the dark web forums. We used the Onion Router to check the web contents that users of dark web forums are posting and discussing. This paper also examines the most common activities in the illicit subjects that users are chatting about in the dark web forums. We performed affect analysis on the dark web forums, which is useful for measuring the presence of illicit subjects such as drugs, violence, forgery and piracy. The results show that there are similarities in the subjects between the dark web forums

KW - Dark web

KW - Deep web

KW - Surface web

KW - Illegal forums

KW - Tor

U2 - 10.1109/iCMLDE.2018.00015

DO - 10.1109/iCMLDE.2018.00015

M3 - Conference paper

SN - 9781728104041

SP - 22

EP - 29

BT - 2018 International Conference on Machine Learning and Data Engineering (iCMLDE)

A2 - Kyu Rhee, Phill

A2 - Bashar, Md Rezaul

PB - IEEE

CY - Piscataway, NJ, USA

T2 - 2nd International Conference on Machine Learning and Data Engineering

Y2 - 3 December 2018 through 7 December 2018

ER -

Identification of illegal forum activities inside the Dark Net

Abstract

Conference

UN SDGs

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