Abstract
Time-related information in text posted on-line is one type of personal information targeted by attackers, one reason that sharing information online can be risky. Therefore, time information should be anonymized before it is posted on social networking services. One approach to anonymizing information is to replace sensitive phrases with anonymous phrases, but attackers can usually spot such anonymization due to its unnaturalness. Another approach is to detect temporal passages in the text, but removal of these passages can make the meaning of the text unnatural. We have developed an algorithm that can be used to anonymize time-related personal information by removing the temporal passages when doing so will not change the natural meaning of the message. The temporal phrases are detected by using machine-learned patterns, which are represented by a subtree of the sentence parsing tree. The temporal phrases in the parsing tree are distinguished from other parts of the tree by using temporal taggers integrated into the algorithm. In an experiment with 4008 sentences posted on a social network, 84.53 % of them were anonymized without changing their intended meaning. This is significantly better than the 72.88 % rate of the best previous temporal phrase detection algorithm. Of the learned patterns, the top ten most common ones were used to detect 87.78 % the temporal phrases. This means that only some of the most common patterns can be used to the anonymize temporal phrases in most messages to be posted on an SNS. The algorithm works well not only for temporal phrases in text posted on social networks but also for other types of phrases (such as location and objective ones), other areas (religion, politics, military, etc.), and other languages.
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References
Arnold, B.: Caslon Analytics privacy guide (2007). http://www.caslon.com.au/privacyguide4.htm
Chang, A.X., Manning, C.: Sutime: a library for recognizing and normalizing time expressions. In: Chair, N.C.C., Choukri, K., Declerck, T., Doan, M.U., Maegaard, B., Mariani, J., Odijk, J., Piperidis, S. (eds.) Proceedings of the Eight International Conference on Language Resources and Evaluation (LREC’12), Istanbul, Turkey, May 2012. European Language Resources Association (ELRA) (2012)
Chang, C.Y., Clark, S.: Adjective deletion for linguistic steganography and secret sharing. In: Proceedings of the 24th International Conference on Computational Linguistics, pp. 493–510 (2012)
Han, B., Cook, P., Baldwin, T.: Automatically constructing a normalisation dictionary for microblogs. In: Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning, EMNLP-CoNLL ’12, pp. 421–432. Association for Computational Linguistics, Stroudsburg (2012)
Klein, D., Manning, C.D.: Accurate unlexicalized parsing. In: Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1, ACL ’03, pp. 423–430. Association for Computational Linguistics, Stroudsburg (2003)
Kokkinakis, D., Thurin, A.: Anonymisation of Swedish clinical data. In: Bellazzi, R., Abu-Hanna, A., Hunter, J. (eds.) AIME 2007. LNCS (LNAI), vol. 4594, pp. 237–241. Springer, Heidelberg (2007)
Lam, I.-F., Chen, K.-T., Chen, L.-J.: Involuntary information leakage in social network services. In: Matsuura, K., Fujisaki, E. (eds.) IWSEC 2008. LNCS, vol. 5312, pp. 167–183. Springer, Heidelberg (2008)
Nguyen-Son, H.Q., Nguyen, Q.B., Tran, M.T., Nguyen, D.T., Yoshiura, H., Echizen, I.: Automatic anonymization of natural languages texts posted on social networking services and automatic detection of disclosure. In: The 7th International Workshop on Frontiers in Availability, Reliability and Security (FARES 2012) Proceedings of the International Conference on Availability, Reliability and Security (ARES 2012), pp. 358–364. IEEE (2012)
Nguyen-Son, H.-Q., Nguyen, Q.-B., Tran, M.-T., Nguyen, D.-T., Yoshiura, H., Echizen, I.: New approach to anonymity of user information on social networking services. In: Park, J.J., Leung, V.C.M., Wang, C.-L., Shon, T. (eds.) Future Information Technology, Application, and Service. LNEE, vol. 164, pp. 731–739. Springer, Heidelberg (2012)
Nguyen-Son, H.Q., Tran, M.T., Tran, T.D., Yoshiura, H., Sonehara, N., Echizen, I.: Automatic anonymization of natural languages texts posted on social networking services and automatic detection of disclosure. In: Proceedings of the 11th International Workshop on Digital-Forensics and Watermarking (IWDW 2012). pp. 731–739. Springer (2012)
Noro, T., Inui, T., Takamura, H., Okumura, M.: Time period identification of events in text. In: Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics, ACL-44, pp. 1153–1160. Association for Computational Linguistics, Stroudsburg (2006)
Ounis, I., Macdonald, C., Lin, J., Soboroff, I.: Overview of the TREC-2011 microblog track. In: Proceedings of the 20th Text REtrieval Conference (TREC 2011) (2011)
Samarati, P., Sweeney, L.: Generalizing data to provide anonymity when disclosing information. In: Proceedings of the Seventeenth ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems, PODS ’98, pp. 188–188. ACM, New York (1998)
Shuyo, N.: Language detection library for java (2010). http://code.google.com/p/language-detection/
Strötgen, J., Gertz, M.: Heideltime: high quality rule-based extraction and normalization of temporal expressions. In: Proceedings of the 5th International Workshop on Semantic Evaluation, SemEval ’10, pp. 321–324. Association for Computational Linguistics, Stroudsburg (2010)
Stutzman, F., Gross, R., Acquisti, A.: Silent listeners: the evolution of privacy and disclosure on facebook. J. Priv. Confid. 4(2), 2 (2012)
Suchanek, F.M., Kasneci, G., Weikum, G.: Yago: a core of semantic knowledge. In: Proceedings of the 16th international Conference on World Wide Web, WWW ’07, pp. 697–706. ACM, New York (2007)
Tam, D.: Facebook by the numbers: 1.06 billion monthly active users (2013). http://news.cnet.com/8301-1023_3-57566550-93/facebook-by-the-numbers-1.06-billion-monthly-active-users/
UzZaman, N., Allen, J.F.: Event and temporal expression extraction from raw text: first step towards a temporally aware system. Int. J. Semant. Comput. 04(04), 487–508 (2010)
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Nguyen-Son, HQ., Hoang, AT., Tran, MT., Yoshiura, H., Sonehara, N., Echizen, I. (2014). Anonymizing Temporal Phrases in Natural Language Text to be Posted on Social Networking Services. In: Shi, Y., Kim, HJ., Pérez-González, F. (eds) Digital-Forensics and Watermarking. IWDW 2013. Lecture Notes in Computer Science(), vol 8389. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-43886-2_31
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