SoK: An Evaluation of the Secure End User Experience on the Dark Net through Systematic Literature Review
Abstract
:1. Introduction
- Users intend to conceal web browsing to circumvent internet-activity monitoring by local ISPs (Internet Service Providers) or law-enforcing government agencies. These users can include people from legitimate backgrounds such as journalists or whistle blowers [6,8]. However, these users can also include criminals who intentionally use these services to conceal their identities. It is challenging to provide selective anonymity without compromising on the anonymity network in the first place, making other legitimate users vulnerable to the system.
- Users seek encrypted communication with an immediate network, concealing logs of chat or instant messages being documented on a database. These users might need the protected network not only for anonymous communication but also for financial transactions.
- Users seek to publish controversial journalistic articles amid an oppressive regime. This is a specific user base as there have been several incidents where journalists and whistleblowers were targeted after their identities have been revealed https://carleton.ca/align/2019/illuminate-exploring-the-dark-web-a-cloak-for-journalists-and-their-sources/ (accessed on 1 December 2021).
- Provide a comprehensive overview of all themes and subjects explored so far in Dark Net research;
- Highlight the importance of the study of privacy and security in the Dark Net from the user’s perspective;
- Point out the gaps and less studied themes in Dark Net research.
2. Related Work
3. Methods
- RQ1: What is the current research landscape for the Dark Net from the privacy and security perception of user data?
- RQ2: What are the technical security and privacy vulnerabilities of the Dark Net detailed by prior studies, and what are the mitigation measures suggested? Are these mitigation measures successful in user-focused vulnerabilities over the Dark Net?
- RQ3: How are prior research studies comprehending the privacy and security concerns of the users? For example, are there any user studies conducted to understand users’ risk perception?
3.1. Database and Keyword-Based Search
3.2. Inclusion and Exclusion Criteria
3.3. Title and Abstract Screening
3.4. Thematic Analysis
3.5. User Study Analysis
4. Results
4.1. Thematic Analysis
4.1.1. Frameworks and Technological Solutions of Dark Net Privacy and Security
4.1.2. Network Analysis of the Dark Net
4.1.3. Attack Landscape
4.1.4. Dark Web Illegal Market
4.1.5. Theoretical Overviews of Dark Net Privacy and Security
4.1.6. Evaluation of Illegal Activities over Dark Net
4.1.7. Forum and Social Network Studies Evaluating Dark Net Data
4.1.8. Deanonymization of Dark Net Users
4.1.9. Ethical and Legal Implications of Dark Net Transactions
4.2. Analysis of User Studies
4.2.1. Study Method
4.2.2. Study Population
4.2.3. Recruitment Methods
4.2.4. Study Categories
5. Discussion and Implications
5.1. Focus on Technical Aspects
5.2. Future Direction towards User Studies
5.3. Attack Surfaces
5.4. More Emphasis on Dark Net and Legal Implications
6. Limitations and Future Work
7. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Theme | Open Codes |
---|---|
Frameworks and Technological Solutions of Dark Net Privacy and Security | Dark Net Monitoring, Framework Based on Hidden Markov Models, Automating Traffic Analysis for Securing Network, Solutions of User Deanonymization Problem using Artificial Intelligence, TOR Crawling, and Classification, Image Analysis, Bag of Visual Words, Topic Detection Model, Stochastic Analysis, Machine Learning to Predict Threats, Real-time Alert System, Profiling Dark Net Data, Probabilistic Model, Graph Modelling, Tor Ranking Algorithm, Online Processing Algorithm, Graph Mining, Probabilistic Pre-processing Model for Data Sanitization, Dark Net Application Suite Using Cryptography, Random Walk Algorithm, Agglomerative Clustering, Malicious Dedicated Hosts Detection, Data Mining, Modeling and Querying the Dark Web, Zeronet Crawling, Dark Net Design, Attack Resistant Network Embedding, Image Analysis, Greedy Embedding Algorithm, Freenet Routing, Smart Contracts, Bloom Filters |
Network Analysis of the Dark Net | Traffic Monitoring, Traffic Classification, Taxonomy of Dark Net Traffic, Tor Traffic Analysis, Traffic Misconfiguration, Port Scanning, P2P Network Routing, Hybrid Honeypot Architecture for Coverage of Large IPv6 Address Spaces, Network Monitoring using Topological Data Analysis, Network Telescopes, Passive Monitoring of Traffic, Probing Campaigns, Improper Traffic Analysis, Hierarchical Classifier of Dark Net Traffic, Freenet Routing, I2P Network |
Attack Landscape | Worm Tomography, DDOS Attacks detection, Malware Analysis, Phishing Study, Tor Attacks, Cyber Threat Prediction, Real-time Malware Activity Detection, Tor Threat Analysis, Enterprise Level Cyber Attacks, Ransomware, Fingerprinting Dark Net Traffic Logs to Detect Malware, Emerging Novel Attacks, Distributed Reflection Denial of Service Attack Detection, Cryptocurrency Attacks, Blockchain Privacy |
Dark Web Illegal Market | Single Vendor Marketplace Similarities, Dark Net Marketplace Vendor Accounts Linking, Identity Crime Prevention and Trading on Dark Net Marketplaces, Law enforcement Interventions Against Dark Net Market, Silkroad, Transactions in Cryptocurrency, Trust Logistics and Conflict Factors |
Theoretical Overviews of Dark Net Privacy and Security | Tor V3 Services, Tor Attacks, Tor Security, SOK on Illicit Markets, Dark Web Privacy, Cybercrime Ecosystem |
Evaluation of Illegal Activities Over Dark Net | Drug Trade, Identity Crime, Child Abuse, Criminal Activity |
Forum and Social Network Studies Evaluating Dark Net Data | Forum Analysis on Suicide, Dark Net Forums Data Analysis, Forum Study on Law Enforcement Interventions Against Dark Net Market, Representations of Drug Users’ Ways of Life, Sentiment Analysis, Authorship Attribution |
Deanonymization of Dark Net Users | User Deanonymization, Tor Deanonymization, Tor Identity location leaks, Deanonymization Techniques, Personally Identifiable Information Data Mining, Geolocation, Deanonymization of Users Through Bitcoin Transactions, Drug Trafficker Identification, Location Leak |
User Studies | User Behavior on Tor, Drug Cryptomarket Users, Silkroad Users, Internet Freedom, Revocable Anonymity to Abusive Users, TOR Community Motivations, Dark Web Perceptions of Students and Parents |
Ethical and Legal Implications of Dark Net Transactions | Legislative Limits, Tor Legal Issues, Chatbot, Slovenian Legal System, Legal Enforcement |
Category | Articles |
---|---|
Frameworks and Technological Solutions | 54 (27%) |
Network Analysis of the Dark Net | 49 (%) |
Attack Landscape | 30 (15%) |
Dark Web Illegal Market | 25 (%) |
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 (%) |
Deanonymization of Dark Net Users | 13 (%) |
User Studies | 9 (%) |
Ethical and Legal Implications of Dark Net Transactions | 7 (%) |
Year (20–) | 05 | 06 | 07 | 08 | 09 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Frameworks & Technological Solutions | 1 | - | - | 1 | - | 1 | 2 | 2 | 2 | 3 | 3 | 3 | 4 | 3 | 8 | 10 | 5 |
Network Analysis | - | 1 | - | 1 | - | 1 | - | 4 | 1 | 2 | 2 | 4 | 5 | 10 | 7 | 3 | 5 |
Attack Landscape | - | - | - | 3 | - | - | 1 | - | - | 3 | 2 | 2 | 2 | 4 | 3 | 5 | - |
Illegal Market | - | - | - | - | - | - | - | 1 | 1 | 1 | - | 1 | 2 | 4 | 7 | 5 | 3 |
Theoretical Overviews | - | - | - | - | 1 | - | 1 | - | 1 | - | 1 | 1 | 4 | 2 | 4 | 4 | 1 |
Illegal Activities | 1 | 1 | - | 2 | - | 5 | 3 | 5 | 1 | ||||||||
Forum Studies | - | - | - | - | - | 2 | - | 1 | 1 | - | - | 2 | 1 | 2 | 3 | 5 | - |
User Deanonymization | - | - | - | - | - | - | - | - | - | - | - | 1 | - | 3 | 2 | 5 | 1 |
Ethical & Legal Implications | - | - | - | - | - | - | - | - | - | - | 1 | 1 | 1 | 2 | 1 | 1 | - |
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Tazi, F.; Shrestha, S.; De La Cruz, J.; Das, S. SoK: An Evaluation of the Secure End User Experience on the Dark Net through Systematic Literature Review. J. Cybersecur. Priv. 2022, 2, 329-357. https://doi.org/10.3390/jcp2020018
Tazi F, Shrestha S, De La Cruz J, Das S. SoK: An Evaluation of the Secure End User Experience on the Dark Net through Systematic Literature Review. Journal of Cybersecurity and Privacy. 2022; 2(2):329-357. https://doi.org/10.3390/jcp2020018
Chicago/Turabian StyleTazi, Faiza, Sunny Shrestha, Junibel De La Cruz, and Sanchari Das. 2022. "SoK: An Evaluation of the Secure End User Experience on the Dark Net through Systematic Literature Review" Journal of Cybersecurity and Privacy 2, no. 2: 329-357. https://doi.org/10.3390/jcp2020018
APA StyleTazi, F., Shrestha, S., De La Cruz, J., & Das, S. (2022). SoK: An Evaluation of the Secure End User Experience on the Dark Net through Systematic Literature Review. Journal of Cybersecurity and Privacy, 2(2), 329-357. https://doi.org/10.3390/jcp2020018