Information leakage in optimal anonymized and diversified data

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 5284 LNCS, Issue , 2008, Pages 30-44

  Fang, Chengfang ^a   Chang, Ee Chien ^a  

^a NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

Author keywords

Data dissemination; K anonymity and diversity; Privacy preserving

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMPUTER SCIENCE; COMPUTERS;

DATA DISSEMINATION; GENERALIZATION PROCESS; GENERIC FRAMEWORKS; INFORMATION LEAKAGE; K-ANONYMITY AND -DIVERSITY; OPTIMIZATION PROBLEMS; PRIVACY PRESERVING; PRIVACY REQUIREMENTS;

INFORMATION DISSEMINATION;

EID: 57149146430     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-88961-8_3     Document Type: Conference Paper

References (20)

1. Adam, N.R., Wortmann, J.C.: Security-control methods for statistical databases: A comparative study. ACM Computing Surveys, 515-556 (1989)
2. Aggarwal, C.C.: On k-anonymity and the curse of dimensionality. In: 31st International Conference on Very Large Data Bases, pp. 901-909 (2005)
3. Aggarwal, G., Feder, T., Kenthapadi, K., Motwani, R., Panigrahy, R., Thomas, D., Zhu, A.: k-anonymity: Algorithms and hardness. Technical report, Stanford University (2004)
4. Aggarwal, G., Feder, T., Kenthapadi, K., Motwani, R., Panigrahy, R., Thomas, D., Zhu, A.: Anonymizing tables. In: 10th International Conference on Database Theory, pp. 246-258 (2005)
5. Aggarwal, G., Feder, T., Kenthapadi, K., Motwani, R., Panigrahy, R., Thomas, D., Zhu, A.: Approximation algorithms for k-anonymity. Journal of Privacy Technology (2005)
6. Bayardo, R.J., Agrawal, R.: Data privacy through optimal k-anonymization. In: International Conference on Data Engineering, pp. 217-228 (2005)
7. Bettini, C., Wang, X.S., Jajodia, S.: Protecting privacy against location-based personal identification. Secure Data Management, 185-199 (2005)
8. Duncan, G.T., Feinberg, S.E.: Obtaining information while preserving privacy: A markov perturbation method for tabular data. In: Joint Statistical Meetings, pp. 351-362 (1997)
9. Fung, B., Wang, K., Yu, P.: Top-down specialization for information and privacy preservation. In: International Conference on Data Engineering, pp. 205-216 (2005)
10. Gedik, B., Liu, L.: A customizable k-anonymity model for protecting location privacy. In: 25th International Conference on Distributed Computing Systems (2005)
11. LeFevre, K., DeWitt, D.J., Ramakrishnan, R.: Mondrian multidimensional k-anonymity. In: International Conference on Data Engineering (2006)
12. LeFevrea, K., DeWitt, D.J., Ramakrishnan, R.: Incognito: Efficient fulldomain k-anonymity. In: SIGMOD (2005)
13. Machanavajjhala, A., Gehrke, J., Kifer, D., Venkitasubramaniam, M.: ℓ-diversity: Privacy beyond k-anonymity. In: International Conference on Data Engineering, p. 24 (2006)
14. Meyerson, A., Williams, R.: On the complexity of optimal k-anonymity. In: 23rd ACM Symposium on the principles of Database Systems, pp. 223-228 (2004)
15. Samarati, P.: Protecting respondents' identities in microdata release. In: IEEE Transactions on Knowledge and Data Engineering, pp. 1010-1027 (2001)
16. Samarati, P., Sweeney, L.: Protecting privacy when disclosing information: k-anonymity and its enforcement through generalization and suppression. Technical report, CMU, SRI (1998)
17. Sweeney, L.: Achieving k-anonymity privacy protection using generalization and suppression. International Journal of Uncertainty, Fuzziness and Knowledge-Based System, 571-588 (2002)
18. Sweeney, L.: k-anonymity: a model for protecting privacy. International Journal of Uncertainty, Fuzziness and Knowledge-Based System, 557-570 (2002)
19. Xu, S., Yung, M.: k-anonymous secret handshakes with reusable credentials. In: 11th ACM Conference on Computer and Communications Security, pp. 158-167 (2004)
20. Yao, G., Feng, D.: A new k-anonymous message transmission protocol. In: 5th International Workshop on Information Security Applications, pp. 388-399 (2004)