## 4 Results
### Thematic Analysis  
#### 4.1.1 Frameworks and Technological Solutions of Dark Net Privacy and Security  
Over a quarter of the papers 54 (27%) aimed to design and introduce technology-based solution as well as frameworks to enhance the privacy and security of the Dark Net [31; 32; 33; 34; 35; 36; 37; 38; 39; 40; 41; 42; 43; 44; 45; 46; 47; 48; 49; 50; 51; 52; 53; 54; 55; 56; 57; 58; 59; 60; 61; 62; 63; 64; 65; 66; 67; 68; 69; 70; 71; 72; 73; 74; 75; 76; 77]. The research was based on several types of technological solutions \begin{table}
\begin{tabular}{c c} \hline \hline
**Category** & **Articles** \\ \hline Frameworks and Technological Solutions & 54 (27\%) \\ Network Analysis of the Dark Net & 49 (24.5\%) \\ Attack Landscape & 30 (15\%) \\ Dark Web Illegal Market & 25 (12.5\%) \\ Theoretical Overviews of Dark Net Privacy \& Security & 20 (10\%) \\ Evaluation of Illegal Activities Over Dark Net & 18 (9\%) \\ Forum and Social Network Studies Evaluating Dark Net Data & 17 (8.5\%) \\ Deanonymization of Dark Net Users & 13 (6.5\%) \\ User Studies & 9 (4.5\%) \\ Ethical and Legal Implications of Dark Net Transactions & 7 (3.5\%) \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Thematic overview of the papers collected and analyzed based on the codebook and themes generated. Note that the total of the percentages is over 100 since the categories are not mutually exclusive. \begin{table}
\begin{tabular}{c c c c c c c c c c c c c c c c} \hline \hline
**Year (20-)** & **05** & **06** & **07** & **08** & **09** & **10** & **11** & **12** & **13** & **14** & **15** & **16** & **17** & **18** & **19** & **20** & **21** \\ \hline Frameworks \& \& & & & & & & & & & & & & & & & \\ Technological Solutions & 1 & - & - & 1 & - & 1 & 2 & 2 & 2 & 3 & 3 & 3 & 4 & 3 & 8 & 10 & 5 \\ \hline Network Analysis & - & 1 & - & 1 & - & 1 & - & 4 & 1 & 2 & 2 & 4 & 5 & 10 & 7 & 3 & 5 \\ \hline Attack Landscape & - & - & - & 3 & - & - & 1 & - & - & 3 & 2 & 2 & 2 & 4 & 3 & 5 & - \\ \hline Illegal Market & - & - & - & - & - & - & - & 1 & 1 & 1 & - & 1 & 2 & 4 & 7 & 5 & 3 \\ \hline Theoretical Overviews & - & - & - & - & 1 & - & 1 & - & 1 & - & 1 & 1 & 4 & 2 & 4 & 4 & 1 \\ \hline Illegal Activities & & & & & & & & & & 1 & 1 & - & 2 & - & 5 & 3 & 5 & 1 \\ \hline Forum Studies & - & - & - & - & - & 2 & - & 1 & 1 & - & - & 2 & 1 & 2 & 3 & 5 & - \\ \hline User Deanonymization & - & - & - & - & - & - & - & - & - & - & 1 & - & 3 & 2 & 5 & 1 \\ \hline Ethical \& Legal Implications & - & - & - & - & - & - & - & - & 1 & 1 & 1 & 2 & 1 & 1 & - \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Summary of the timeline of the papers by themes. All papers were published after the year 2005.  
proposed by the authors to enhance the privacy and security of the Dark Net, including artificial intelligence approaches, data mining, network-based solutions, encryption, as well as statistical approaches as shown in Figure 2. Many of the papers use these technical solutions, the most prominent of which is combining network-based solutions with artificial intelligence methods. One such study, \"ToRank: Identifying the most influential suspicious domains in the Tor network\", develops a new algorithm for classifying the onion domains into normal and suspicious activities, then ranking these domains and identifying the influential ones. Through their study, [PERSON] et al. also extended the version of the \"Dark Net Usage Text Addresses\" dataset up to 10,367 manually labeled hidden services in the Tor network [58]. [PERSON] et al. attempt to classify images uploaded to the Tor network using artificial intelligence methods in a different approach. These methods include semantic attention key point filtering, which is a model introduced in this paper to eliminate non-significant features which do not belong to the main object of interest in the image at the pixel level [38]. Figure 3 shows a detailed timeline of publications of papers related to the theme of frameworks and technological solutions for Dark Net privacy and security.