Mining the Dark Web: A Novel Approach for Placing a Dark Website under Investigation

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Bassel Alkhatib 1,2,* Randa S. Basheer 1

1. Syrian Virtual University, Damascus, Syria

2. Al-Sham Private University, Damascus, Syria

* Corresponding author.


Received: 15 Jul. 2019 / Revised: 16 Aug. 2019 / Accepted: 11 Sep. 2019 / Published: 8 Oct. 2019

Index Terms

Dark Web, Dark Web Market, Data Mining, Dark Web Mining, Data Pre-Processing


In the last two decades, illicit activities have dramatically increased on the Dark Web. Every year, Dark Web witnesses establishing new markets, in which administrators, vendors, and consumers aim to illegal acquisition and consumption. On the other hand, this rapid growth makes it quite difficult for law and security agencies to detect and investigate all those activities with manual analyses. In this paper, we introduce our approach of utilizing data mining techniques to produce useful patterns from a dark web market contents. We start from a brief description of the methodology on which the research stands, then we present the system modules that perform three basic missions: crawling and extracting the entire market data, data pre-processing, and data mining. The data mining methods include generating Association Rules from products’ titles, and from the generated rules, we infer conceptual compositions vendors use when promoting their products. Clustering is the second mining aspect, where the system clusters vendors and products. From the generated clusters, we discuss the common characteristics among clustered objects, find the Top Vendors, and analyze products promoted by the latter, in addition to the most viewed and sold items on the market. Overall, this approach helps in placing a dark website under investigation.

Cite This Paper

Bassel Alkhatib, Randa S. Basheer, " Mining the Dark Web: A Novel Approach for Placing a Dark Website under Investigation", International Journal of Modern Education and Computer Science(IJMECS), Vol.11, No.10, pp. 1-13, 2019. DOI:10.5815/ijmecs.2019.10.01


[1]B. Hawkins, "Under The Ocean of the Internet - The Deep Web," 15 5 2016. [Online]. Available: [Accessed 13 December 2018].
[2]M. S. L. S. W. L. Andres Baravalle, "Mining the Dark Web: Drugs and Fake Ids," in Data Mining Workshops (ICDMW), 2016 IEEE 16th International Conference, Barcelona, Spain, 2016.
[3]J. A. F. A. R. W. Monica J. Barratt, "Safer Scoring? Cryptomarkets, Social Supply and Drug Market Violence," International Journal of Drug Policy, vol. 35, pp. 24-31, 2016.
[4]A. D. ,. E. M. ,. E. N. ,. V. P. ,. J. S. ,. P. S. John Robertson, Darkweb Cyber Threat Intelligence Mining, Cambridge: Cambridge University Press, 2017.
[5]O. B. M. N. S. Quan Le, "Deep Learning at the Shallow End: Malware Classification for Non-Domain Experts," Digital Investigation, vol. 26, pp. S118-S126, 2018.
[6]G. M. M. M. Alessandro Celestini, "Tor Marketplaces Exploratory Data Analysis: The Drugs Case," in International Conference on Global Security, Safety, and Sustainability, 2017.
[7]M. A. E. N. P. S. Ericsson Marin, "Community Finding of Malware and Exploit Vendors on Darkweb Marketplaces," in In 2018 1st International Conference on Data Intelligence and Security (ICDIS), 2018.
[8]F. C. B. B. Paolo Spagnoletti, "An Investigation on the Generative Mechanisms of Dark Net Markets," in Proceedings of the 13th Pre-ICIS Workshop on Information Security and Privacy, 2018.
[9]D. L. N. A. S. A. M. P. M. S. Ben R. Lane, "The Dark Side Of The Net: Event Analysis Of Systemic Teamwork (East) Applied To Illicit Trading On A Darknet Market," in Proceedings of the Human Factors and Ergonomics Society 2018 Annual Meeting, 2018.
[10]I. Ladegaard, "Crime Displacement in Digital Drug Markets," International Journal of Drug Policy, vol. 63, p. 113–121, 2019.
[11]D. R. M. M. L. S. Q. R. Julian Broséus, "A Geographical Analysis of Trafficking on a Popular Darknet Market," Forensic science international, vol. 277, pp. 88-102, 2017.
[12]H. P. Petar Ristoski, "Semantic Web in data mining and knowledge discovery: A comprehensive survey," Web Semantics: Science, Services and Agents on the World Wide Web, vol. 36, pp. 1-22, 2016.
[13]P. R. A. S. P. S. Praveen Kumari, "Web Mining - Concept, Classification and Major Research Issues: A Review," Asian J. Adv. Basic Sci, vol. 4, no. 2, pp. 41-44, 11 May 2016.
[14]L. H. P. P. C. Pritam C. Gaigole, "Preprocessing Techniques in Text Categorization," in National Conference on Innovative Paradigms in Engineering & Technology (NCIPET-2013), 2013.
[15]J. I. N. S. Vijayarani, "Preprocessing Techniques for Text Mining - An Overview," International Journal of Computer Science & Communication Networks, vol. 5, no. 1, pp. 7-16, 2015.
[16]S. K. I. A. K. M. A. A. Rida Hafeez, "Does Preprocessing Really Impact Automatically Generated Taxonomy," in 2017 13th International Conference on Emerging Technologies (ICET), 2017.
[17]J. T. P. Surbhi K. Solanki, "A Survey on Association Rule Mining," in 2015 Fifth International Conference on Advanced Computing & Communication Technologies, 2015.
[18]J. T. P. Surbhi K. Solanki, "A Survey on Association Rule Mining," in 2015 Fifth International Conference on Advanced Computing & Communication Technologies, 2015.
[19]T. Vishal, "Cluster Analysis for Market Segmentation," 3 February 2015. [Online]. Available: [Accessed 9 March 2019].
[20]N. P. M. P. Jasmine Irani, "Clustering Techniques and the Similarity Measures used in Clustering: A Survey," International Journal of Computer Applications, vol. 134, no. 7, pp. 9-14, January 2016.
[21]R. B. Bassel AlKhatib, "Crawling the Dark Web: A Conceptual Perspective, Challenges and Implementation," Journal of Digital Information Management (JDIM), vol. 17, no. 2, pp. 51-60, April 2019.
[22]"Davies-Bouldin Criterion Clustering Evaluation Object - MATLAB - MathWorks Benelux," [Online]. Available: [Accessed 19 April 2019].