Journals / Sakarya University Journal of Computer and Information Sciences / 2022 / Cilt: 5 Sayı: 1

Terrorism in Cyberspace : A Critical Review of Dark Web Studies under the Terrorism Landscape

Pages
1–21
Publication Date
2022-04-30
DOI
—
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Advanced artificial intelligence, image processing and classification by using machine learning, natural language processing methods, hash value analysis, and sock puppet techniques can be used to detect and predict terrorist incidents on the dark web.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Crime, terrorism, and other illegal activities are increasingly taking place in cyberspace.
📊
Key Findings & Data:Dark web studies are critical for designing successful counter-terrorism strategies.
💡
Conclusion & Impact:Advanced artificial intelligence, image processing and classification by using machine learning, natural language processing methods, hash value analysis, and sock puppet techniques can be used to detect and predict terrorist incidents on the dark web.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Terrorism · Cyberspace · Dark web

Abstract

Crime, terrorism, and other illegal activities are increasingly taking place in cyberspace. Crime in the dark web is one of the most serious challenges confronting governments around the world. Dark web makes it difficult to detect criminals and track activities, as it provides anonymity due to special tools such as TOR. Therefore, it has evolved into a platform that includes many illegal activities such as pornography, weapon trafficking, drug trafficking, fake documents, and more specially terrorism as in the context of this paper. Dark web studies are critical for designing successful counter-terrorism strategies. The aim of this research is to conduct a critical analysis of the literature and to demonstrate research efforts in dark web studies related to terrorism. According to result of study, the scientific studies related to terrorism activities have been minimally conducted and the scientific methods used in detecting and combating them in dark web should be varied. Advanced artificial intelligence, image processing and classification by using machine learning, natural language processing methods, hash value analysis, and sock puppet techniques can be used to detect and predict terrorist incidents on the dark web.

🔖

Cite This Article

SÖNMEZ, E., CODAL, K. S. (2022). Terrorism in Cyberspace : A Critical Review of Dark Web Studies under the Terrorism Landscape. Sakarya University Journal of Computer and Information Sciences, Cilt: 5 Sayı: 1, 1–21. https://ajindex.com/articles/946638

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (18)

  1. S. D. Keene, “Terrorism and the internet: a double-edged sword,” J. Money Laund. Control, vol. 14, no. 4, pp. 359–370, Oct. 2011, doi: 10.1108/13685201111173839
  2. J. R. C. Nurse and M. Bada, “The Group Element of Cybercrime: Types, Dynamics, and Criminal Operations,” Jan. 2019, doi: 10.1093/oxfordhb/9780198812746.013.36
  3. D. Bieda and L. Halawi, “Cyberspace: A Venue for Terrorism,” 2015. Accessed: May 28, 2021. [Online]. Available:
  4. G. Weimann, “Cyberterrorism How Real Is the Threat?,” 2004. Accessed: May 28, 2021. [Online]. Available: www.usip.org
  5. G. Weimann, “Going Darker ? The Challenge of Dark Net Terrorism,” 2015
  6. M. Chertoff and T. Simon, “The Impact of the Dark Web on Internet Governance and Cyber Security,” Glob. Comm. Internet Govrnance, no. 6, pp. 6–8, 2015, [Online]. Available:
  7. Statista, “Internet users in the world,” 2021. https://www.statista.com/statistics/617136/digital-population-worldwide/ (accessed Dec. 22, 2020)
  8. M. de Kunder, “The size of the World Wide Web (The Internet),” 2020. https://www.worldwidewebsize.com/ (accessed Dec. 21, 2020)
  9. G. Weimann, “Terrorist Migration to the Dark Web,” Perspect. Terror., vol. 10, no. 3, pp. 40–44, 2016
  10. M. Bergman, “The deep Web: Surfacing hidden value,” J. Electron., vol. 7, no. 1, 2001
  11. K. Finklea, “Dark Web,” Taylor and Francis Inc., Mar. 2017. doi: 10.1080/1057610X.2015.1119546
  12. E. Jardine, “The Dark Web Dilemma: Tor, Anonymity and Online Policing,” 2015. Accessed: Jan. 21, 2021. [Online]. Available:
  13. R. Dingledine, N. Mathewson, and P. Syverson, “Tor: The Second-Generation Onion Router,” 2004
  14. B. Berton, “The dark side of the web: ISIL ’ s one-stop shop ?,” no. June, pp. 1–2, 2015, doi: 10.2815/454889
  15. N. Tavabi, N. Bartley, A. Abeliuk, S. Soni, E. Ferrara, and K. Lerman, “Characterizing activity on the deep and dark web,” Web Conf. 2019 - Companion World Wide Web Conf. WWW 2019, pp. 206–213, 2019, doi: 10.1145/3308560.3316502
  16. D. Moore and T. Rid, “Cryptopolitik and the darknet,” Survival (Lond)., vol. 58, no. 1, pp. 7–38, Jan. 2016, doi: 10.1080/00396338.2016.1142085
  17. N. Malik, “Terror in the Dark,” London, 2018. [Online]. Available:
  18. S. Alayda, N. A. Almowaysher, F. Alserhani, and M. Humayun