A Stylometric Investigation Tool for Authorship Attribution in E-Mail Forensics

  • Sridhar Neralla
  • D. Lalitha Bhaskari
  • P. S. Avadhani
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 249)


E-Mail forensics is one of the several cyber forensics approaches for identifying the cyber crimes that are happened through e-mails. This paper focuses on stylometric approach for finding accurate author of an e-mail. Stylometry is used to identify unique writing styles of an author; we used parameter minimization approach to reduce the overhead. In this paper we introduced java-based Stylometric Investigation Tool that is based on minimum number of parameters for stylometric approach.


Authorship Cyber Crimes E-Mail Forensics Stylometry 


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  1. 1.
    Ramachandran, A., Feamster, N.: Understanding the network-level behavior of spammers. In: Proceedings of Sigcomm (2006)Google Scholar
  2. 2.
    Kantchelian, A., Ma, J., Huang, L., Afroz, S., Joseph, A.D., Tygar, J.D.: Robust Detection of Comment Spam Using Entropy Rate. In: Proceedings of the 5th ACM Workshop on Security and Artificial Intelligence (2012)Google Scholar
  3. 3.
    Neralla, S., Lalitha Bhaskari, D., Avadhani, P.S.: Inverted Pyramid Approach for E-mail forensics using heterogeneous forensics tools. CSI Communications, 20–22 (July 2013)Google Scholar
  4. 4.
    Schatz, B., Mohay, G., Clark, A.: A correlation method for establishing provenance of timestamps in digital evidence. Digital Investigation 3, 98–107 (2006)CrossRefGoogle Scholar
  5. 5.
    Weil, M.C.: Dynamic Time & Date Stamp Analysis. International Journal of Digital Evidence (2002)Google Scholar
  6. 6.
    Khmelev, D., Tweedie, W.: Using Markov Chains for Identification of Writer. Literary and Linguistic Computing 16(4), 299–307 (2001)CrossRefGoogle Scholar
  7. 7.
    Tweedie, F.J., Singh, S., Holmes, D.I.: Neural Network Applications in Stylometry. The Federalist Papers. Computers and the Humanities 39(1), 1–10 (1996)CrossRefGoogle Scholar
  8. 8.
    Chandrasekaran, R., Manimannan, G.: Use of Generalized Regression Neural Network in Authorship Attribution. International Journal of Computer Applications (0975 – 8887) 62(4) (January 2013)Google Scholar
  9. 9.
    Gill, P.S., Swartz, T.B.: Stylometric analyses using Dirichlet process mixture models. Journal of Statistical Planning and Inference 141, 3665–3674 (2011)MathSciNetCrossRefMATHGoogle Scholar
  10. 10.
    Anderson, A., Corney, M., de Vel, O., Mohay, G.: Identifying the Authors of Suspect E-mail. Communications of the ACM (2001)Google Scholar
  11. 11.
    Clark, J.H., Hannon, C.J.: A classifier system for author recognition using synonym-based features. In: Gelbukh, A., Kuri Morales, Á.F. (eds.) MICAI 2007. LNCS (LNAI), vol. 4827, pp. 839–849. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  12. 12.
    Abbasi, A., Chen, H.: Writeprints: a stylometric approach to identity level identification and similarity detection in cyberspace. ACM Transactions on Information Systems 26(2) (March 2008)Google Scholar
  13. 13.
    de Vel, O., Anderson, A., Corney, M., Mohay, G.: Mining E-mail Content for Author Identification Forensics. News Letter ACM SIGMOD Record 30(4), 55–64 (2001)CrossRefGoogle Scholar
  14. 14.
    Koppel, M., Schler, J.: Exploiting Stylistic Idiosyncrasies for Authorship Attribution. In: Proceedings of IJCAI 2003 Workshop on Computational Approaches to Style Analysis and Synthesis, pp. 69–72 (2003)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Sridhar Neralla
    • 1
  • D. Lalitha Bhaskari
    • 1
  • P. S. Avadhani
    • 1
  1. 1.Dept. of CS&SEAndhra UniversityVisakhapatnamIndia

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