Abstract
Publishing of data is usually only permitted when complying with a confidentiality policy. To this end, this work proposes an approach to weaken an original database instance: within a logic-oriented modeling definite knowledge is replaced by disjunctive knowledge to introduce uncertainty about confidential information. This provably disables an adversary to infer this confidential information, even if he employs his a priori knowledge and his knowledge about the protection mechanism. As evaluated based on a prototype implementation, this approach can be made highly efficient. If a heuristic – resulting only in a slight loss of availability – is employed, it can be even used in interactive scenarios.
This work has been supported by the DFG under grant SFB 876/A5.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Abiteboul, S., Hull, R., Vianu, V.: Foundations of Databases. Addison-Wesley, Reading (1995)
Bertossi, L.E., Li, L.: Achieving data privacy through secrecy views and null-based virtual updates. IEEE Transactions on Knowledge and Data Engineering 25(5), 987–1000 (2013)
Biskup, J.: Inference-usability confinement by maintaining inference-proof views of an information system. International Journal of Computational Science and Engineering 7(1), 17–37 (2012)
Biskup, J., Bonatti, P.A.: Controlled query evaluation with open queries for a decidable relational submodel. Annals of Mathematics and Artificial Intelligence 50(1-2), 39–77 (2007)
Biskup, J., Hartmann, S., Link, S., Lochner, J.-H., Schlotmann, T.: Signature-based inference-usability confinement for relational databases under functional and join dependencies. In: Cuppens-Boulahia, N., Cuppens, F., Garcia-Alfaro, J. (eds.) DBSec 2012. LNCS, vol. 7371, pp. 56–73. Springer, Heidelberg (2012)
Biskup, J., Preuß, M.: Database fragmentation with encryption: Under which semantic constraints and a priori knowledge can two keep a secret? In: Wang, L., Shafiq, B. (eds.) DBSec 2013. LNCS, vol. 7964, pp. 17–32. Springer, Heidelberg (2013)
Biskup, J., Wiese, L.: A sound and complete model-generation procedure for consistent and confidentiality-preserving databases. Theoretical Computer Science 412(31), 4044–4072 (2011)
Boost Graph Library: Maximum cardinality matching (2014), http://www.boost.org/doc/libs/1_55_0/libs/graph/doc/maximum_matching.html
Campan, A., Truta, T.M.: Data and structural k-anonymity in social networks. In: Bonchi, F., Ferrari, E., Jiang, W., Malin, B. (eds.) PinKDD 2008. LNCS, vol. 5456, pp. 33–54. Springer, Heidelberg (2009)
Ciriani, V., De Capitani di Vimercati, S., Foresti, S., Samarati, P.: k-Anonymity. In: Yu, T., Jajodia, S. (eds.) Secure Data Management in Decentralized Systems. Advances in Information Security, vol. 33, pp. 323–353. Springer, New York (2007)
Fung, B.C., Wang, K., Fu, A.W.C., Yu, P.S.: Introduction to Privacy-Preserving Data Publishing: Concepts and Techniques. Data Mining and Knowledge Discovery. CRC Press, Boca Raton (2011)
Hay, M., Miklau, G., Jensen, D., Towsley, D.F., Li, C.: Resisting structural re-identification in anonymized social networks. VLDB Journal 19(6), 797–823 (2010)
Knuth, D.E.: The Stanford GraphBase: A Platform for Combinatorial Computing. ACM Press, New York (1993)
Korte, B., Vygen, J.: Combinatorial Optimization: Theory and Algorithms, 5th edn. Algorithms and Combinatorics. Springer, Heidelberg (2012)
Levesque, H.J., Lakemeyer, G.: The Logic of Knowledge Bases. The MIT Press, Cambridge (2000)
Machanavajjhala, A., Kifer, D., Gehrke, J., Venkitasubramaniam, M.: ℓ-diversity: Privacy beyond k-anonymity. ACM Transactions on Knowledge Discovery from Data 1(1) (2007)
Magun, J.: Greedy matching algorithms: An experimental study. ACM Journal of Experimental Algorithmics 3(6) (1998)
Mehlhorn, K., Näher, S.: LEDA: A platform for combinatorial and geometric computing. Cambridge University Press, Cambridge (1999)
Ramakrishnan, R., Gehrke, J.: Database Management Systems, 3rd edn. McGraw-Hill, Boston (2003)
Stiege, G.: Playing with Knuth’s words.dat. Tech. Rep. 1/12, Department of Computer Science, University of Oldenburg, Germany (May 2012)
Sweeney, L.: k-anonymity: A model for protecting privacy. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 10(5), 557–570 (2002)
Vazirani, V.V.: A theory of alternating paths and blossoms for proving correctness of the \(O(\sqrt{|V|}.|E|)\) general graph maximum matching algorithm. Combinatorica 14(1), 71–109 (1994)
Wong, R.C.W., Fu, A.W.C.: Privacy-Preserving Data Publishing – An Overview. Synthesis Lectures on Data Management. Morgan & Claypool Publishers, San Rafael (2010)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Biskup, J., Preuß, M. (2014). Inference-Proof Data Publishing by Minimally Weakening a Database Instance. In: Prakash, A., Shyamasundar, R. (eds) Information Systems Security. ICISS 2014. Lecture Notes in Computer Science, vol 8880. Springer, Cham. https://doi.org/10.1007/978-3-319-13841-1_3
Download citation
DOI: https://doi.org/10.1007/978-3-319-13841-1_3
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-13840-4
Online ISBN: 978-3-319-13841-1
eBook Packages: Computer ScienceComputer Science (R0)