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Data Mining Instant Messaging Communications to Perform Author Identification for Cybercrime Investigations

  • Conference paper
Digital Forensics and Cyber Crime (ICDF2C 2009)

Abstract

Instant messaging is a form of computer-mediated communication (CMC) with unique characteristics that reflect a realistic presentation of an author’s online stylistic characteristics. Instant messaging communications use virtual identities, which hinder social accountability and facilitate IM-related cybercrimes. Criminals often use virtual identities to hide their true identity and may also supply false information on their virtual identities. This paper presents an IM authorship analysis framework and feature set taxonomy for use in cyber forensics and cybercrime investigations. We explore authorship identification of IM messages to discover the parameters with the highest accuracy for determining the identity of a cyber criminal.

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References

  1. Abbasi, A., Chen, H.: Applying Authorship Analysis to Extremist-Group Web Forum Messages. IEEE Intelligent Systems 20(5), 67–75 (2005)

    Article  Google Scholar 

  2. Abbasi, A., Chen, H.: Visualizing Authorship for Identification. Proceedings of the Intelligence and Security Informatics. In: IEEE International Conference on Intelligence and Security Informatics (2006)

    Google Scholar 

  3. Abbasi, A., Chen, H.: Writeprints: A Stylometric Approach to Identify-Level Identification and Similarity Detection in Cyberspace. ACM Transactions on Information Systems 26(2) (2008)

    Google Scholar 

  4. Argamon, S., Saric, M., Stein, S.S.: Style mining of electronic messages for multiple authorship discrimination: First results. In: Proceedings of the 9th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (2003)

    Google Scholar 

  5. BioPassword.: Authentication Solutions Through Keystroke Dynamics (2006)

    Google Scholar 

  6. Baayen, R.H., van Halteren, H., Tweedie, F.: Outside the Cave of Shadows: Using Syntactic Annotation to Enhance Authorship Attribution. Literary and Linguistic Computing 11(3) (1996)

    Google Scholar 

  7. Chaski, C.E.: Who’s At The Keyboard? Authorship Attribution in Digital Evidence Investigations. International Journal of Digital Evidence 4(1) (2005)

    Google Scholar 

  8. de Vel, O., Anderson, A., Corney, M., Mohay, G.: Multi-Topic E-mail Authorship Attribution Forensics. In: ACM Conference on Computer Security - Workshop on Data Mining for Security Applications, Philadelphia, PA, USA (2001)

    Google Scholar 

  9. de Vel, O., Anderson, A., Corney, M., Mohay, G.: Mining E-mail Content for Author Identification Forensics. SIGMOD Record Web Edition 30(4) (2001)

    Google Scholar 

  10. de Vel, O.: Mining E-mail Authorship. In: KDD 2000 Workshop on Text Mining, Boston, Massachusetts, USA, pp. 21–27 (2000)

    Google Scholar 

  11. Graham, N., Hirst, G., Marthi, B.: Segmenting documents by stylistic character. Natural Language Engineering 11(4), 397–415 (2005)

    Article  Google Scholar 

  12. Gray, A., Sallis, P., Macdonnel, S.: Software forensics: Extended authorship analysis techniques to computer programs. In: Proceedings of the 3rd Biannual Conference on the International Association of Forensic Linguists (1997)

    Google Scholar 

  13. Holmes, D.I.: Authorship Attribution. Computers and the Humanities 28(2) (1994)

    Google Scholar 

  14. Kucukyilmaz, T., Cambazoglu, B.B., Aykanat, C., Can, F.: Chat mining: predicting user and message attributes in computer-mediated communication. Information Processing & Management 44(4), 1448–1466 (2008)

    Article  Google Scholar 

  15. Love, H.: Attributing authorship: an introduction. Cambridge University Press, Cambridge (2002)

    Book  Google Scholar 

  16. Li, J., Zheng, R., Chen, H.: From fingerprint to writeprint. Commun. ACM 49(4), 76–82 (2006)

    Article  Google Scholar 

  17. McQuail, D.: McQuail’s Mass Communication Theory, 5th edn. SAGE Publications, London (2005)

    Google Scholar 

  18. Moores, T., Dhillon, G.: Software Piracy: A View from Hong Kong. Communications of the ACM 43(12), 88–93 (2000)

    Article  Google Scholar 

  19. Mendenhall, T.C.: The Characteristic Curves of Composition. Science 11(11), 237–249 (1887)

    Article  Google Scholar 

  20. Mostellar, F., Wallace, D.: Inference and Disputed Authorship: The Federalis. Addison-Wesley, Reading (1964)

    Google Scholar 

  21. Revett, K.: Behavioral Biometrics: A Remote Access Approach. John Wiley & Sons, Ltd., Chichester (2008)

    Book  Google Scholar 

  22. Rudman, J.: The state of authorship attribution studies: some problems and solutions. Computers and the Humanities 31(4) (1998)

    Google Scholar 

  23. Teng, G., Lai, M., Ma, J., Li, Y.: E-mail Authorship Mining Based on SVM for Computer Forensic. In: Proceedings of the Third International Conference on Machine Learning and Cybernetics, Shanghai (2004)

    Google Scholar 

  24. Zheng, R., Li, J., Chen, H., Huang, Z.: A Framework for Authorship Identification of Online Messages: Writing-Style Features and Classification Techniques. Journal of the American Society for Information Science and Technology 57(3), 378–393 (2006)

    Article  Google Scholar 

  25. Zheng, R., Qin, Y., Huang, Z., Chen, H.: Authorship Analysis in Cybercrime Investigation. In: Chen, H., Miranda, R., Zeng, D.D., Demchak, C.C., Schroeder, J., Madhusudan, T. (eds.) ISI 2003. LNCS, vol. 2665, pp. 59–73. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

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© 2010 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering

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Orebaugh, A., Allnutt, D.J. (2010). Data Mining Instant Messaging Communications to Perform Author Identification for Cybercrime Investigations. In: Goel, S. (eds) Digital Forensics and Cyber Crime. ICDF2C 2009. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 31. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11534-9_10

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  • DOI: https://doi.org/10.1007/978-3-642-11534-9_10

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-11533-2

  • Online ISBN: 978-3-642-11534-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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