Darknet Crawling and Data Analysis

Darknet Crawling and Data Analysis

Bachelor Thesis

Motivation
Darknet market places allow people to purchase illegal goods or illegal services like a botnet for DDoS attacks. The usage and the popularity of such market places is permanently increasing. Darknet research is still in its infancy. Our goal is to get a better understanding in this area. This challenge will be tackled in this thesis.
This market functions as a black market and offers the opportunity for users to remain anonymous. Marketplace operators use Tor hidden services to hide their identity. Sellers and buyers use Tor and BitCoin to trade anonymously.
However, every user of such a Darknet market has to be registered with a username which are visible to everyone within that marketplace. These names can be linked to offered products. Thus, it is possible to monitor the activity of users which can be related to each other. This can lead to new perceptions.

Ziel
This solution will help to understand the Darknet system better because new perceptions can be made. Relations between users after graph representation can lead to recognize criminal structures like organizations. Additionally, this solution could also function as an early warning system.

Vision
This problem is highly relevant because criminal organizations have found a way to trade illegal goods and services with minimal risk of getting caught. In addition to that, the usage of Darknet marketplaces is increasing.
However, everyone is able to register to those marketplaces and gets the ability to see a couple of activities of vendors, users and products. This introduces the opportunity to monitor those activities. This information can be used to build an early-warning-system for criminal activities.

Start: 27.06.2016

Ende: 26.12.2016

Betreuer:

  • Jörg Daubert

Forschungsgebiete: CRISP, CYSEC, Telecooperation, privacy-trust , – SSI – Area Secure Smart Infrastructures, – SPIN: Smart Protection in Infrastructures and Networks