Web-based inference detection

16th USENIX Security Symposium

Volumn , Issue , 2007, Pages 71-86

  Staddon, Jessica ^a   Golle, Philippe ^a   Zimny, Bryce ^a,b  

^a PALO ALTO RESEARCH CENTER   (United States)

^b UNIVERSITY OF WATERLOO   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

WEBSITES;

AUTOMATED TOOLS; INFERENCE CONTROL; INFERENCE DETECTIONS; PRIVATE DATA; PUBLIC KNOWLEDGE; RE IDENTIFICATIONS; SEARCH QUERIES; WEB BASED;

RISK PERCEPTION;

EID: 84872236868     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (45)

1. B. Aleman-Meza, M. Nagarajan, C. Ramakrishnan, L. Ding, P. Kolari, A. Sheth, B. Arpinar, A. Joshi and T. Finin. Semantic analytics on social networks: experiences in addressing the problem of conflict of interest detection. 15th International World Wide Web Conference, 2006.
2. M. Atallah, C. McDonough, S. Nirenburg, and V. Raskin. Natural Language Processing for Information Assurance. Proc. 9th ACM/SIGSAC New Security Paradigms Workshop (NSPW 00), pp.51-65, 2000.
3. Apache Lucene. http://lucene.apache.org/java/docs/
4. AOL Keyword Searches. http://dontdelete.com/default.asp
5. M. Barbaro and T. Zeller. A face is exposed for AOL searcher no. 4417749. The New York Times, August 9, 2006.
6. http://www.bongonews.com/layout1.php?event=2315
7. W. Broad. U. S. Web Archive is Said to Reveal a Nuclear Primer. The New York Times, November 3, 2006.
8. http://www.judicialwatch.org/archive/2005/osama.pdf
9. Executive Order 12958, Classified National Security Information. http://www.dss.mil/seclib/eo12958.htm
10. B. Davison, D. Deschenes and D. Lewanda. Finding relevant website queries. Twelfth International World Wide Web Conference, 2003.
11. O. de Vel, A. Anderson, M. Corney and G. Mohay. Mining email content for author identification forensics. SIGMOD Record, Vol. 30, No. 4, December 2001.
12. Mike Dowman, Valentin Tablan, Hamish Cunningham and Borislav Popov. Web-Assisted Annotation, Semantic Indexing and Search of Television and Radio News. WWW, 2005.
13. Factiva Insight: Reputation Intelligence. http://www.factiva.com
14. Fetch Technologies. http://www.fetch.com
15. GATE: General Architecture for Text Engineering. http://gate.ac.uk/projects.html
16. N. Glance. Community Search Assistant. IUI, 2001.
17. P. Golle. Revisiting the Uniqueness of Simple Demographics in the US Population. Workshop on Privacy in the Electronic Society, 2006.
18. Google SOAP search API. http://code.google.com/apis/soapsearch/
19. J. Hale and S. Shenoi. Catalytic inference analysis: detecting inference threats due to knowledge discovery. IEEE Symposium on Security and Privacy, 1997.
20. S. Hill and F. Provost. The myth of the double-blind review? Author identification using only citations. SIGKDD Explorations, 2003.
21. T. Hinke. Database inference engine design approach. Database Security II: Status and Prospects, 1990.
22. D. Jones. Google’s PowerPoint blunder was preventable. IR Web Report. http://www.irwebreport.com/perspectives/2006/mar/google blunder.htm
23. E. Kin, Y. Matsuo, M. Ishizuka. Extracting a social network among entities by web mining. ISWC ‘06 Workshop on Web Content Mining with Human Language Technologies, 2006.
24. M. Koppel and J. Schler. Authorship verification as a one-class classification problem. Proceedings of the 21st International Conference on Machine Learning, 2004.
25. M. Koppel, J. Schler, S. Argamon and E. Messeri. Authorship attribution with thousands of candidate authors. SIGIR ‘06.
26. M. Lapata and F. Keller. The Web as a Baseline: Evaluating the Performance of Unsupervised Web-based Models for a Range of NLP Tasks, HLT-NAACL, 2004.
27. G. Leech, P. Rayson and A. Wilson. Word frequencies in written and spoken english: based on the British National Corpus., Longman, London, 2001.
28. C. Manning and H. Schutze. Foundations of statistical natural language processing. MIT Press, 1999.
29. MedicineNet.com. http://www.medterms.com/script/main/hp.asp
30. P. Nakov and M. Hearst. Using the Web as an Implicit Training Set: Application to Structural Ambiguity Resolution. HLT-NAACL, 2005.
31. Nstein Technologies. http://www.nstein.com/pim. asp
32. G. Pant, S. Bradshaw and F. Menczer. Search engine-crawler symbiosis: adapting to community interests.7th European Conference on Digital Libraries, 2003.
33. X. Qian, M. Stickel, P. Karp, T. Lunt and T. Garvey. Detection and elimination of inference channels in multilevel relational database systems. IEEE Symposium on Security and Privacy, 1993.
34. M. Steyvers, P. Smyth, M. Rosen-Zvi and T. Griffiths. Probabilistic author-topic models for information discovery. KDD‘04.
35. L. Sweeney. AI Technologies to Defeat Identity Theft Vulnerabilities. AAAI Spring Symposium on AI TEchnologies for Homeland Security, 2005.
36. L. Sweeney. Uniqueness of Simple Demographics in the U.S. Population. LIDAP-WP4. Carnegie Mellon University, Laboratory for International Data Privacy, Pittsburgh, PA, 2000.
37. P. Turney. Coherent Keyphrase Extraction via Web Mining. IJ-CAI, 2002.
38. Unified Medical Language System. http://www.umm.edu/glossary/a/index.html
39. Personal communication.
40. Wikipedia. Alcoholism. http://en.wikipedia.org/wiki/Alcoholism
41. Wikipedia. Sexually transmitted disease. http://en.wikipedia.org/wiki/Sexually transmitted disease
42. http://wordweb.info/free/
43. R. Yip and K. Levitt. Data level inference detection in database systems. IEEE Eleventh Computer Security Foundations Workshop, 1998.
44. D. Zhao and T. Sapp. AOL Search Database. http://www.aolsearchdatabase.com/
45. http://www.zoominfo.com/