Skip to main content
SpringerLink
Log in
Book cover

Machine Learning for Authorship Attribution and Cyber Forensics pp 23–36Cite as

Messaging Forensics In Perspective

  • Chapter
  • First Online:

  • 445 Accesses

Abstract

This chapter presents the central theme and a big picture of the methods and technologies covered in this book (see Fig. 2.2). For the readers to comprehend presented security and forensics issues, and associated solutions, the content is organized as components of a forensics analysis framework. The framework is employed to analyze online messages by integrating machine learning algorithms, natural language processing techniques, and social networking analysis techniques in order to help cybercrime investigation.

This is a preview of subscription content, 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   139.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   179.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   179.99
Price excludes VAT (USA)
  • Durable hardcover 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

Learn about institutional subscriptions

Notes

  1. 1.

    http://www.whitehousedrugpolicy.gov

References

  1. New Report on the State of Phishing Attacks from Wombat Security Shows Significant Increases Year over Year (2016)

    Google Scholar 

  2. (APWG), Phishing Activity Trends Report: Unifying the Global Response To Cybercrime (2017). [Online]. https://docs.apwg.org/reports/apwg_trends_report_q4_2016.pdf

  3. A. Abbasi, H. Chen, J.F. Nunamaker, Stylometric identification in electronic markets: scalability and robustness. J. Manag. Inf. Syst. 25(1), 49–78 (2008)

    Google Scholar 

  4. H. Chen et al., Crime data mining: an overview and case studies, in Proceedings of the 2003 Annual National Conference on Digital Government Research (2003), pp. 1–5

    Google Scholar 

  5. R.C. der Hulst, Introduction to Social Network Analysis (SNA) as an investigative tool. Trends Organ Crime 12(2), 101–121 (2009)

    Google Scholar 

  6. First Amendment And The Media ‘Encyclopedia of Communication and Information’ (2002). [Online]. https://www.encyclopedia.com/media/encyclopedias-almanacs-transcripts-and-maps/first-amendment-and-media

  7. K.C. Darrell Etherington, Large DDoS attacks cause outages at Twitter, Spotify, and other sites (2016). [Online]. https://techcrunch.com/2016/10/21/many-sites-including-twitter-and-spotify-suffering-outage/

  8. M.E. Whitman, H.J. Mattord, Principles of Information Security (Cengage Learning, 2011)

    Google Scholar 

  9. Oregon Woman Loses $400,000 to Nigerian E-Mail Scam (2008). [Online]. http://www.foxnews.com/story/2008/11/17/oregon-woman-loses-400000-to-nigerian-e-mail-scam.html

  10. Scam Victim Stories, Scammer’s Exposed (2017). [Online]. https://scammer419.wordpress.com/scam-victim-stories/

  11. N. Chou, R. Ledesma, Y. Teraguchi, J.C. Mitchell et al., Client-side defense against web-based identity theft, in NDSS (2004)

    Google Scholar 

  12. C.E.H. Chua, J. Wareham, Fighting internet auction fraud: an assessment and proposal. Computer (Long. Beach. Calif) 37(10), 31–37 (2004)

    Google Scholar 

  13. G.-F. Teng, M.-S. Lai, J.-B. Ma, Y. Li, E-mail authorship mining based on SVM for computer forensic, in Proceedings of 2004 International Conference on Machine Learning and Cybernetics, vol. 2 (2004), pp. 1204–1207

    Google Scholar 

  14. Forensic ToolKit. [Online]. https://accessdata.com/products-services/forensic-toolkit-ftk. Accessed 5 May 2020

  15. Encase. [Online]. http://www.guidancesoftware.com/. Accessed 5 May 2020

  16. Data Warehousing—Coplink*/BorderSafe/RISC. [Online]. https://eller.arizona.edu/departments-research/centers-labs/artificial-intelligence/research/previous/coplink. Accessed 5 May 2020

  17. Paraben’s E3: EMX. [Online]. https://www.paraben.com/products/e3-emx. Accessed 5 May 2020

  18. S.J. Stolfo, S. Hershkop, Email mining toolkit supporting law enforcement forensic analyses, in Proceedings of the 2005 National Conference on Digital Government Research (2005), pp. 221–222

    Google Scholar 

  19. S. Argamon, M. Šarić, S.S. Stein, Style mining of electronic messages for multiple authorship discrimination: first results, in Proceedings of the Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (2003), pp. 475–480

    Google Scholar 

  20. M. Koppel, J. Schler, S. Argamon, Computational methods in authorship attribution. J. Am. Soc. Inf. Sci. Technol. 60(1), 9–26 (2009)

    Google Scholar 

  21. H. Baayen, H. Van Halteren, F. Tweedie, Outside the cave of shadows: using syntactic annotation to enhance authorship attribution. Liter. Linguist. Comput. 11(3), 121–132 (1996)

    Google Scholar 

  22. J.F. Burrows, Word-patterns and story-shapes: the statistical analysis of narrative style. Liter. Linguist. Comput. 2(2), 61–70 (1987)

    Google Scholar 

  23. F. Mosteller, D.L. Wallace, Applied Bayesian and Classical Inference: The Case of the Federalist Papers (Springer Science & Business Media, 2012)

    Google Scholar 

  24. J.F. Burrows, ‘An ocean where each kind...’: statistical analysis and some major determinants of literary style. Comput. Hum. 23(4–5), 309–321 (1989)

    Google Scholar 

  25. R.S. Forsyth, D.I. Holmes, Feature-finding for test classification. Liter. Linguist. Comput. 11(4), 163–174 (1996)

    Article  Google Scholar 

  26. O. De Vel, Mining e-mail authorship, in Proc. Workshop on Text Mining, ACM International Conference on Knowledge Discovery and Data Mining (KDD’2000) (2000)

    Google Scholar 

  27. R. Zheng, J. Li, H. Chen, Z. Huang, A framework for authorship identification of online messages: writing-style features and classification techniques. J. Am. Soc. Inf. Sci. Technol. 57(3), 378–393 (2006)

    Article  Google Scholar 

  28. F. Iqbal, R. Hadjidj, B.C.M. Fung, M. Debbabi, A novel approach of mining write-prints for authorship attribution in e-mail forensics. Digit. Investig. 5, S42–S51 (2008)

    Article  Google Scholar 

  29. O. De Vel, A. Anderson, M. Corney, G. Mohay, Mining e-mail content for author identification forensics. ACM SIGMOD Rec. 30(4), 55–64 (2001)

    Article  Google Scholar 

  30. F. Inc, fastText: library for efficient text classification and representation learning (2016)

    Google Scholar 

  31. A. Vaswani et al., Attention is all you need. Adv. Neural Inf. Proces. Syst., 5998–6008 (2017)

    Google Scholar 

  32. P.J. Liu et al., Generating wikipedia by summarizing long sequences, in arXiv Prepr. arXiv1801.10198 (2018)

    Google Scholar 

  33. J. Schroeder, J. Xu, H. Chen, M. Chau, Automated criminal link analysis based on domain knowledge. J. Am. Soc. Inf. Sci. Technol. 58(6), 842–855 (2007)

    Google Scholar 

  34. J. Allan, J. Carbonell, G. Doddington, J. Yamron, Y. Yang et al., Topic detection and tracking pilot study: final report, in Proceedings of the DARPA Broadcast News Transcription and Understanding Workshop, vol. 1998 (1998), pp. 194–218

    Google Scholar 

  35. R. Barzilay, N. Elhadad, Inferring strategies for sentence ordering in multidocument news summarization. J. Artif. Intell. Res. 17, 35–55 (2002)

    MATH  Google Scholar 

  36. R. Barzilay, K.R. McKeown, Sentence fusion for multidocument news summarization. Comput. Linguist. 31(3), 297–328 (2005)

    MATH  Google Scholar 

  37. D. Das, A.F.T. Martins, A survey on automatic text summarization. Liter. Surv. Lang. Stat. II Course C. 4, 192–195 (2007)

    Google Scholar 

  38. M. White, T. Korelsky, C. Cardie, V. Ng, D. Pierce, K. Wagstaff, Multidocument summarization via information extraction, in Proceedings of the First International Conference on Human Language Technology Research (2001), pp. 1–7

    Google Scholar 

  39. N. Chinchor, Overview of MUC-7, in Seventh Message Understanding Conference (MUC-7): Proceedings of a Conference Held in Fairfax, Virginia, April 29–May 1, 1998 (1998)

    Google Scholar 

  40. E. Minkov, R.C. Wang, W.W. Cohen, Extracting personal names from email: applying named entity recognition to informal text, in Proceedings of the Conference on Human Language Technology and Empirical Methods in Natural Language Processing (2005), pp. 443–450

    Google Scholar 

  41. G. Wang, H. Chen, H. Atabakhsh, Automatically detecting deceptive criminal identities. Commun. ACM 47(3), 70–76 (2004)

    Google Scholar 

  42. V.R. Carvalho, W.W. Cohen, Learning to extract signature and reply lines from email, in Proceedings of the Conference on Email and Anti-Spam, vol. 2004 (2004)

    Google Scholar 

  43. H. Chen, W. Chung, J. Qin, E. Reid, M. Sageman, G. Weimann, Uncovering the dark Web: a case study of Jihad on the Web. J. Am. Soc. Inf. Sci. Technol. 59(8), 1347–1359 (2008)

    Google Scholar 

  44. A. Pons-Porrata, R. Berlanga-Llavori, J. Ruiz-Shulcloper, Topic discovery based on text mining techniques. Inf. Process. Manag. 43(3), 752–768 (2007)

    MATH  Google Scholar 

  45. F. Sebastiani, Machine learning in automated text categorization. ACM Comput. Surv. 34(1), 1–47 (2002)

    Google Scholar 

  46. N. Pendar, Toward spotting the pedophile telling victim from predator in text chats, in International Conference on Semantic Computing, 2007. ICSC 2007 (2007), pp. 235–241

    Google Scholar 

  47. E. Elnahrawy, Log-based chat room monitoring using text categorization: a comparative study, in The International Conference on Information and Knowledge Sharing, US Virgin Islands (2002)

    Google Scholar 

  48. H. Dong, S. Cheung Hui, Y. He, Structural analysis of chat messages for topic detection. Online Inf. Rev. 30(5), 496–516 (2006)

    Google Scholar 

  49. T. Kolenda, L.K. Hansen, J. Larsen, Signal detection using ICA: application to chat room topic spotting, in Third Int. Conf. Indep. Compon. Anal. Blind Source Sep. (2001), no. 1, pp. 540–545

    Google Scholar 

  50. Ö. Özyurt, C. Köse, Chat mining: automatically determination of chat conversations’ topic in Turkish text based chat mediums. Expert Syst. Appl. 37(12), 8705–8710 (2010)

    Google Scholar 

  51. Y. Zhang, N. Zincir-Heywood, E. Milios, Narrative text classification for automatic key phrase extraction in web document corpora, in Proceedings of the 7th Annual ACM International Workshop on Web Information and Data Management (2005), pp. 51–58

    Google Scholar 

  52. R. Xiong, J. Donath, PeopleGarden: creating data portraits for users, in Proceedings of the 12th Annual ACM Symposium on User Interface Software and Technology (1999), pp. 37–44

    Google Scholar 

  53. J. Bengel, S. Gauch, E. Mittur, R. Vijayaraghavan, Chattrack: chat room topic detection using classification, in International Conference on Intelligence and Security Informatics (2004), pp. 266–277

    Google Scholar 

  54. G. Salton, M.J. McGill, Introduction to modern information retrieval (1986)

    Google Scholar 

  55. H. Chen, W. Chung, J.J. Xu, G. Wang, Y. Qin, M. Chau, Crime data mining: a general framework and some examples. Computer (Long. Beach. Calif). 37(4), 50–56 (2004)

    Google Scholar 

  56. Y. Xiang, M. Chau, H. Atabakhsh, H. Chen, Visualizing criminal relationships: comparison of a hyperbolic tree and a hierarchical list. Decis. Support. Syst. 41(1), 69–83 (2005)

    Article  Google Scholar 

  57. E. Frank, M.A. Hall, I.H. Witten, The WEKA Workbench. Online Appendix for “Data Mining: Practical Machine Learning Tools and Techniques” (Morgan Kaufmann, 2016)

    Google Scholar 

  58. I.H. Witten, E. Frank, M.A. Hall, C.J. Pal, Data Mining: Practical Machine Learning Tools and Techniques (Morgan Kaufmann, 2016)

    Google Scholar 

  59. E. Frank, S. Kramer, Ensembles of nested dichotomies for multi-class problems, in Proceedings of the Twenty-First International Conference on Machine Learning (2004), p. 39

    Google Scholar 

  60. J.R. Quinlan, Induction of decision trees. Mach. Learn. 1(1), 81–106 (1986)

    Google Scholar 

  61. M.D. Buhmann, Radial Basis Functions: Theory and Implementations, vol 12 (Cambridge University Press, 2003)

    Google Scholar 

  62. S.E. Robertson, K.S. Jones, Relevance weighting of search terms. J. Am. Soc. Inf. Sci. 27(3), 129–146 (1976)

    Google Scholar 

  63. J. Pearl, Bayesian networks: a model of self-activated memory for evidential reasoning, in Proceedings of the 7th Conference of the Cognitive Science Society, 1985 (1985), pp. 329–334

    Google Scholar 

  64. N. Kitaev, D. Klein, Constituency parsing with a self-attentive encoder, in arXiv Prepr. arXiv1805.01052 (2018)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Zayed University, Abu Dhabi, United Arab Emirates

    Farkhund Iqbal

  2. School of Engineering & Computer Science, Concordia University, Montreal, QC, Canada

    Mourad Debbabi

  3. School of Information Studies, McGill University, Montreal, QC, Canada

    Benjamin C. M. Fung

Authors
  1. Farkhund Iqbal
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Mourad Debbabi
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Benjamin C. M. Fung
    View author publications

    You can also search for this author in PubMed Google Scholar

Rights and permissions

Reprints and permissions

Copyright information

© 2020 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Iqbal, F., Debbabi, M., Fung, B.C.M. (2020). Messaging Forensics In Perspective. In: Machine Learning for Authorship Attribution and Cyber Forensics. International Series on Computer Entertainment and Media Technology. Springer, Cham. https://doi.org/10.1007/978-3-030-61675-5_2

Download citation

Publish with us

Policies and ethics

Search

Navigation