MAster assignment
Using text analysis (NLTK etc.) to understand malicious practices on the dark web
TYPE : MASTER CS
Period: Start date: as soon as possible
Student: Unassigned
If you are interested please contact:
Objective:
The project aims to study and understand the effectiveness of the texts used by attackers/cybercriminals. Also, how language is important to frame a message and get success in their attacks. How effective is the language translator for criminals if they want to translate their native language text into English? The student should focus on the following strategies. More details can be discussed with the interested student(s).
- Crime scripts
- Business Models
- Communication tactics
- Persuasion Principles
- Attack Trees
Data Sources
- Darkweb Marketplaces
- APWG
- Victim Stories (LMIO)
- Other open/proprietary data sources
References:
- N. Ferry, T. Hackenheimer, F. Herrmann and A. Tourette, "Methodology of dark web monitoring," 2019 11th International Conference on Electronics, Computers and Artificial Intelligence (ECAI), Pitesti, Romania, 2019, pp. 1-7, doi: 10.1109/ECAI46879.2019.9042072.
- Alghamdi, H. and Selamat, A. (2022), "Techniques to detect terrorists/extremists on the dark web: a review", Data Technologies and Applications, Vol. 56 No. 4, pp. 461-482. https://doi.org/10.1108/DTA-07-2021-0177
- Murty, C.A.S., Rana, H., Verma, R., Pathak, R., Rughani, P.H. (2022). Building an AI/ML Based Classification Framework for Dark Web Text Data. In: Bashir, A.K., Fortino, G., Khanna, A., Gupta, D. (eds) Proceedings of International Conference on Computing and Communication Networks. Lecture Notes in Networks and Systems, vol 394. Springer, Singapore. https://doi.org/10.1007/978-981-19-0604-6_9
- Dalvi, A., Siddavatam, I., Jain, A., Moradiya, S., Kazi, F., Bhirud, S.G. (2022). ELEMENT: Text Extraction for the Dark Web. In: Bianchini, M., Piuri, V., Das, S., Shaw, R.N. (eds) Advanced Computing and Intelligent Technologies. Lecture Notes in Networks and Systems, vol 218. Springer, Singapore. https://doi.org/10.1007/978-981-16-2164-2_43