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

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Author(s)

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

1. Syrian Virtual University, Damascus, Syria

2. Al-Sham Private University, Damascus, Syria

* Corresponding author.

DOI: https://doi.org/10.5815/ijmecs.2019.10.01

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

Abstract

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

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