Examining and Exposing the Darknet

This thesis consists of two studies; the first study is “Diving into the Darknet” and the second is “Exposing the Darknet on Mobile Devices”. The Darknet is a network of hidden sites and services which are built based on anonymity. In “Diving into the Darknet”, we applied different data science methods to establish the relationships between the data in the data set. This data set has information related to seller, drug types, and transactions. Additionally, we used Tableau to visualize the data set. For the second study, we took a digital forensics perspective of the Darknet. Orfox and Orbot, a Browser Bundle which is used to access the Darknet through mobile devices, were installed on a Galaxy Note 5 with Android 6.0.1. After the investigation, some theories of past studies were disproved by our method combined with E3: DS, a mobile digital forensics software package by Paraben. We believe that the combination of information from a user’s point of view and a technical perspective of digital forensics would bring the Darknet to light. Through this thesis, we hope that knowledge about the Darknet will be revealed and better understood

Using Tableau to Visualize Darknet Data

This presentation was given during the Georgia Southern University College of Engineering and Information Technology Research Symposium

Diving Into the Darknet: Using Tableau to Shed Some Light On Data Analysis

With the law enforcement closure of Silk Road, an increasing number of crypto-markets surfaced at a rapid rate. Taking an interest in this kind of market, multiple studies were conducted using different techniques and tools to collect the data. This data ranged from the kind of drugs being traded, how long the seller was active and the number of transactions a seller conducted. Visualization has always been an effective process that helps the reader, planner, and decision maker to see and recognize the information much faster than reading a table or sorting through pages of information. Tableau is one of the most modern statistical and visualization software packages available. Combining Tableau visualization capabilities and analyzing prior collected data, this study presents findings that illustrate the effectiveness of data visualization

Exposing The Tor Failures On Mobile Devices Using Paraben’s E3:Ds Technology

Privacy and anonymity tools on electronic devices are increasingly commonplace. These tools provide challenges for digital investigators especially when trying to track down and uncover illegal activity such as the use of the “Darknet”, an illegal online service trading market which is hidden from the normal internet users and is often difficult to detect with digital forensic tools, especially if the user uses privacy and anonymity “protection” on their devices. However, digital forensic tools continue to evolve with the ability to detect internet usage, even those supposedly hidden by such privacy tools. These tools present privacy concerns to users. This work seeks to examine the extent that the Tor Browser Bundle protects a user’s privacy. Using a mobile digital forensics software by Paraben, E3:DS, we extract the mobile device’s data, a Samsung Galaxy Note 5 using the Android 6.0.1 operating system. While past research has claimed that using Tor protects user privacy, analysis of the data revealed we were able to extract the websites visited via Tor and extracted search terms from common shopping and social media websites. Implications from this research are three-fold: first, the study shows that E3:DS can reveal internet activity even while running applications that are supposed to provide privacy and anonymity; second, user’s activities are not fully protected when using the Tor Browsing Bundle to surf the internet; and, finally, there are weaknesses in the Tor Bundle that Tor developers need to address in their software to support their privacy claims