Skip to main content
SpringerLink
Log in

A Digital Forensic Readiness Cybercrime Semantic Trigger Process

  • Conference paper
  • First Online:
e-Infrastructure and e-Services for Developing Countries (AFRICOMM 2021)

  • 475 Accesses

Abstract

The recent wave of the global Covid-19 pandemic has led to a surge in text-based non-technical cybercrime attacks within the cyber ecosystem. Information about such cyber-attacks is often in unstructured text data and metadata, a rich source of evidence in a digital forensic investigation. However, such information is usually unavailable during a digital forensic investigation when dealing with the public cloud post-incident. Furthermore, digital investigators are challenged with extracting meaningful semantic content from the raw syntactic and unstructured data. It is partly due to the lack of a structured process for forensic data pre-processing when or if such information is identified. Thus, this study seeks to address the lack of a procedure or technique to extract semantic meaning from text data of a cybercrime attack that could be used as a digital forensic readiness semantics trigger in a cybercrime detection process. For the methodology to address the proposed approach, data science modelling and unsupervised machine learning are used to design a strategy. This method process extracts tokens of cybercrime text data, which are further used to develop an intelligent DFR semantic tool extractor based on natural language patterns from cybercrime text data. The proposed DFR cybercrime semantic trigger process when implemented could be used to create a digital forensic cybercrime language API for all digital forensic investigation systems or tools.

Supported by DigiForS Research Group.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Kulkarni, A., Chong, D., Batarseh, F.A.: Foundations of data imbalance and solutions for a data democracy. In: Batarseh, F.A., Yang, R. (eds.) Data Democracy, pp. 83–106. Academic Press (2020). https://doi.org/10.1016/B978-0-12-818366-3.00005-8

  2. Allen, T.T., Sui, Z., Akbari, K.: Exploratory text data analysis for quality hypothesis generation. Qual. Eng. 30(4), 701–712 (2018)

    Article  Google Scholar 

  3. Ami-Narh, J.T., Williams, P.A.: Digital forensics and the legal system: a dilemma of our times (2008)

    Google Scholar 

  4. Baror, S.O., Venter, H.S., Adeyemi, R.: A natural human language framework for digital forensic readiness in the public cloud. Aust. J. Forensic Sci. 53(5), 566–591 (2021)

    Article  Google Scholar 

  5. Baror, S.O., Ikuesan, R.A., Venter, H.S.: A defined digital forensic criteria for cybercrime reporting. In: International Conference on Cyber Warfare and Security, pp. 617–XVIII. Academic Conferences International Limited (2020)

    Google Scholar 

  6. Baror, S.O., Venter, H.: A taxonomy for cybercrime attack in the public cloud. In: International Conference on Cyber Warfare and Security, pp. 505–X. Academic Conferences International Limited (2019)

    Google Scholar 

  7. Bauder, R., Herland, M., Khoshgoftaar, T.: Evaluating model predictive performance: a medicare fraud detection case study, pp. 9–14 (2019). https://doi.org/10.1109/IRI.2019.00016

  8. Casey, E.: Digital evidence and computer crime: forensic science, computers, and the internet. Academic Press (2011)

    Google Scholar 

  9. Cekik, R., Uysal, A.K.: A novel filter feature selection method using rough set for short text data. Expert Syst. Appl. 160, 113691 (2020)

    Article  Google Scholar 

  10. Ferreira Cruz, A., Rocha, G., Lopes Cardoso, H.: Coreference resolution: toward end-to-end and cross-lingual systems. Information 11(2), 74 (2020)

    Article  Google Scholar 

  11. Hargreaves, C.J., Solomon, S.H.: Assessing the reliability of digital evidence from live investigations involving encryption. Ph.D thesis, Deportment of Informatics and Sensors, Cranfield University, UK (2009)

    Google Scholar 

  12. Hofmann, T.: Realms of meaning: an introduction to semantics. Routledge (2015)

    Google Scholar 

  13. Horsman, G.: The different types of reports produced in digital forensic investigations. Sci. Justice 61(5), 627–634 (2021). https://doi.org/10.1016/j.scijus.2021.06.009

    Article  Google Scholar 

  14. Huoranszki, F.: Common sense and the theory of human behaviour. Philos. Q. 52(209), 526–543 (2002)

    Article  Google Scholar 

  15. Ivan, I., Milodin, D., Sbora, C.: Non security–premise of cybercrime. Theor. Appl. Econ. 19(4), 59–78 (2012)

    Google Scholar 

  16. Jongejan, B., Dalianis, H.: Automatic training of lemmatization rules that handle morphological changes in pre-, in-and suffixes alike. In: Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP, pp. 145–153 (2009)

    Google Scholar 

  17. Jurafsky, D., Martin, J.H.: Speech and language processing (draft). Chapter A: Hidden Markov Models (Draft of 11 Sep. 2018). Retrieved 19 March 2019 (2018)

    Google Scholar 

  18. Kebande, V.R., Karie, N.M., Ikuesan, R.A., Venter, H.S.: Ontology-driven perspective of CFRaaS. Wiley Interdiscip. Rev. Forensic Sci. 2(5), e1372 (2020)

    Article  Google Scholar 

  19. Lagrasse, M., Singh, A., Munkhondya, H., Ikuesan, A., Venter, H.: Digital forensic readiness framework for software-defined networks using a trigger-based collection mechanism. In: Proceedings of the 15th International Conference on Cyber Warfare and Security, ICCWS, pp. 296–305 (2020)

    Google Scholar 

  20. Ma, L., Zhang, Y.: Using word2vec to process big text data. In: 2015 IEEE International Conference on Big Data (Big Data), pp. 2895–2897. IEEE (2015)

    Google Scholar 

  21. McClelland, D., Marturana, F.: A digital forensics triage methodology based on feature manipulation techniques. In: 2014 IEEE International Conference on Communications Workshops (ICC), pp. 676–681. IEEE (2014)

    Google Scholar 

  22. Omeleze, S., Venter, H.S.: Testing the harmonised digital forensic investigation process model-using an android mobile phone. In: 2013 Information Security for South Africa, pp. 1–8. IEEE (2013)

    Google Scholar 

  23. Plisson, J., Lavrac, N., Mladenic, D., et al.: A rule based approach to word lemmatization. In: Proceedings of IS. vol. 3, pp. 83–86 (2004)

    Google Scholar 

  24. Popel, M., Žabokrtský, Z.: TectoMT: modular NLP framework. In: Loftsson, H., Rögnvaldsson, E., Helgadóttir, S. (eds.) NLP 2010. LNCS (LNAI), vol. 6233, pp. 293–304. Springer, Heidelberg (2010). https://doi.org/10.1007/978-3-642-14770-8_33

    Chapter  Google Scholar 

  25. Riemer, N.: Introducing Semantics. Cambridge University Press, Cambridge (2010)

    Book  Google Scholar 

  26. Sinatra, R., Dowd, C.A.: Using syntactic and semantic clues to learn vocabulary. J. Read. 35(3), 224–229 (1991)

    Google Scholar 

  27. Strawson, P.: Subject and Predicate in Logic and Grammar. Routledge (2017). https://doi.org/10.4324/9781315242132

  28. Valjarević, A., Venter, H., Petrović, R.: ISO/IEC 27043:2015–role and application. In: 2016 24th Telecommunications Forum (TELFOR), pp. 1–4. IEEE (2016)

    Google Scholar 

  29. Zawoad, S., Dutta, A.K., Hasan, R.: Towards building forensics enabled cloud through secure logging-as-a-service. IEEE Trans. Dependable Secure Comput. 13(2), 148–162 (2016). https://doi.org/10.1109/TDSC.2015.2482484

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Computer Science, University of Pretoria, Hillcrest, South Africa

    Stacey O. Baror & Hein S. Venter

  2. IT Department Science and Technology Division, Community College, Doha, Qatar

    Richard Adeyemi Ikuesan

Authors
  1. Stacey O. Baror
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hein S. Venter
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Richard Adeyemi Ikuesan
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Stacey O. Baror .

Editor information

Editors and Affiliations

  1. State University of Zanzibar, Zanzibar, Tanzania

    Yahya H. Sheikh

  2. State University of Zanzibar, Zanzibar, Tanzania

    Idris A. Rai

  3. State University of Zanzibar, Zanzibar, Tanzania

    Abubakar D. Bakar

Rights and permissions

Reprints and permissions

Copyright information

© 2022 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Baror, S.O., Venter, H.S., Ikuesan, R.A. (2022). A Digital Forensic Readiness Cybercrime Semantic Trigger Process. In: Sheikh, Y.H., Rai, I.A., Bakar, A.D. (eds) e-Infrastructure and e-Services for Developing Countries. AFRICOMM 2021. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 443. Springer, Cham. https://doi.org/10.1007/978-3-031-06374-9_21

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-06374-9_21

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-06373-2

  • Online ISBN: 978-3-031-06374-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation