Honeypot-Based Data Collection for Dark Web Investigations Using the Tor Network


연구 분야: Strategies



학회: IFIP International Conference on Digital Forensics


초록

The Dark Web presents a challenging and complex environment where cyber criminals conduct illicit activities with high degrees of anonymity and privacy. This chapter describes a honeypot-based data collection approach for Dark Web browsing that incorporates honeypots on three isolated virtual machines, including production honeypots, an onion-website-based research honeypot (Honey Onion) offering illegal services and a log server that collects and securely stores the honeypot logs. Experiments conducted over 14 days collected more than 250 requests on the Honey Onion service and in excess of 28,000 chat records from the Dark Web forum. The log server also monitored Honey Onion traffic, providing details such as packet types, timestamps, network data, and HTTP requests. The data collection results provide valuable insights into Dark Web activities, including malicious, benign and uncategorized activities. The data analysis identified common user categories such as malicious actors, researchers and security professionals, and uncategorized actors. The experimental results demonstrate that honeypot-based data collection can advance Dark Web investigations as well as enable the development of effective cyber security strategies and efforts to combat cyber crime in the Dark Web.


Author Profile
Krishan Pal Singh

Malaviya National Institute of Technology Jaipur India

India
Author Profile
Emmanuel Pilli

Malaviya National Institute of Technology Jaipur India

India
Author Profile
Vijay Laxmi

Malaviya National Institute of Technology Jaipur India

India

📄 논문 정보

발행 연도 2025년
인용수 0
출판 국가 India
사이트 Springer
좋아요 수 0

연관 논문 목록 (165건)