Herbert west - Deanonymizer

HotSec 2011 - 6th USENIX Workshop on Hot Topics in Security

Volumn , Issue , 2011, Pages

  Nanavati, Mihir ^a   Taylor, Nathan ^a   Aiello, William ^a   Warfield, Andrew ^a  

^a UNIVERSITY OF BRITISH COLUMBIA   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION TECHNIQUE; HIGH QUALITY; HIGH-ACCURACY; LONG-TERM RELATIONSHIPS; POLICY-BASED; SCIENTIFIC JOURNALS; SELECTION COMMITTEE; THREAT MODELING;

EID: 84903435014     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (24)

1. ABBASI, A., AND CHEN, H. Writeprints: A stylometric approach to identity-level identification and similarity detection in cyberspace. In ACM TOIS (2008).
2. BACKES, M., DRMUTH, M., AND UNRUH, D. Information flow in the peer-reviewing process. In IEEE S&P (May 2007).
3. BLANK, R. M. How blind is blind review? American Psychologist 39 (1984), 1491-94.
4. BLANK, R. M. The effects of double-blind versus single-blind reviewing: Experimental evidence from the American Economic Review. AER 81 (December 1991).
5. DE VEL, O. Mining e-mail authorship. In KDD (2000).
6. EWALT, D. Why anonymity rules. Forbes (March 12 2011).
7. HAND, D., AND YU, K. Idiot's Bayes - Not so stupid after all? International Statistical Review (2001).
8. HILL, S., AND PROVOST, F. The myth of the double-blind review? Author identification using only citations. SIGKDD Ex-plor. Newsl. 5 (December 2003), 179-184.
9. HOLMES, D., AND FORSYTH, R. The Federalist revisited: New directions in authorship attribution. Literary and Linguistic Computing (1995).
10. IQBAL, F., BINSALLEEH, H., FUNG, B. C. M., AND DEBBABI, M. Mining writeprints from anonymous e-mails for forensic investigation. Digital Investigation 7, 1-2 (October 2010), 56-64.
11. JUOLA, P. Authorship attribution. Found. Trends Inf. Retr. 1 (December 2006).
12. KMIETOWICZ, Z. Double blind peer reviews are fairer and more objective, say academics. British Medical Journal (2008).
13. KOPPEL, M., AKIVA, N., AND DAGAN, I. Feature instability as a criterion for selecting potential style markers. J. Am. Soc. Inf. Sci. Technol. 57 (September 2006).
14. KOPPEL, M., AND SCHLER, J. Exploiting stylistic idiosyncrasies for authorship attribution. In IJCAI03 Workshop on Computational Approaches to Style Analysis and Synthesis (2003).
15. LOPER, E., AND BIRD, S. NLTK: The Natural Language Toolkit. In ACL Workshop on Effective Tools and Methodologies for Teaching Natural Language Processing and Computational Linguistics (2002).
16. MADDEN, S., AND DEWITT, D. Impact of double-blind reviewing on SIGMOD publication rates. SIGMOD Record 35 (2006).
17. MANNING, C. D., RAGHAVAN, P., AND SCHTZE, H. Introduction to Information Retrieval. Cambridge University Press, 2008.
18. MEMBER OF THE 18TH INTERNATIONAL COLLOQUIUM ON STRUCTURAL INFORMATION, A. P., AND (SIROCCO), C. C. Review of Multiparty Equality Function Computation in Networks with Point-to-Point Links, 2011.
19. MOSTELLER, F., AND WALLACE, D. L. Applied Bayesian and Classical Inference - The Case of The Federalist Papers. 1964.
20. MOSTELLER, F., AND WALLACE, D. L. Inference and Disputed Authorship: The Federalist. 1964.
21. RENNIE, J. D. Improving multi-class text classification with Naive Bayes. Master's Thesis, Massachusetts Institute of Technology Tech Report AITR-2001-004 (2001).
22. SAHAMI, M., DUMAIS, S., HECKERMAN, D., AND HORVITZ, E. A Bayesian approach to filtering junk E-mail. In Learning for Text Categorization (1998).
23. SAVAGE, S. On the caching and prefetching of program committees. ACM SIGCOMM, Outrageous Opinions Session (1999).
24. ZHENG, R., LI, J., CHEN, H., AND HUANG, Z. A framework for authorship identification of online messages: Writing-style features and classification techniques. J. Am. Soc. Inf. Sci. Technol. 57 (February 2006).