Applied quantitative information flow and statistical databases

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

Volumn 5983 LNCS, Issue , 2010, Pages 96-110

  Heusser, Jonathan ^a   Malacaria, Pasquale ^a  

^a QUEEN MARY UNIVERSITY OF LONDON   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

ALGEBRAIC STRUCTURES; DATABASE QUERIES; INFORMATION FLOWS; NOVEL APPLICATIONS; QUANTITATIVE INFORMATION; SOLID BASIS; STATISTICAL DATABASE; THEORETICAL FRAMEWORK;

WAVELET TRANSFORMS;

DATABASE SYSTEMS;

EID: 77953239541     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-12459-4_8     Document Type: Conference Paper

References (19)

1. Babić, D., Hutter, F.: Spear Theorem Prover. In: Proc. of the SAT 2008 Race (2008)
2. Backes, M., Köpf, B., Rybalchenko, A.: Automatic Discovery and Quantification of Information Leaks. In: Proc. 30th IEEE Symposium on Security and Privacy, S& P 2009 (2009) (to appear)
3. Barthe, G., D'Argenio, P.R., Rezk, T.: Secure Information Flow by Self-Composition. In: Proceedings of the 17th IEEE workshop on Computer Security Foundations CSFW (2004)
4. Bayardo, R., Schrag, R.: Using CSP look-back techniques to solve real-world SAT instances. In: Proc. of AAAI 1997, pp. 203-208. AAAI Press/The MIT Press (1997)
5. Clark, D., Hunt, S., Malacaria, P.: A static analysis for quantifying information flow in a simple imperative language. Journal of Computer Security 15(3) (2007)
6. Clark, D., Hunt, S., Malacaria, P.: Quantitative information flow, relations and polymorphic types. Journal of Logic and Computation, Special Issue on Lambda-calculus, type theory and natural language 18(2), 181-199 (2005) (Pubitemid 40860589)
7. Clarke, E., Kroening, D., Lerda, F.: A Tool for Checking ANSI-C Programs. In: Jensen, K., Podelski, A. (eds.) TACAS 2004. LNCS, vol. 2988, pp. 168-176. Springer, Heidelberg (2004)
8. Darwiche, A., Marquis, P.: A Knowledge Compilation Map. Journal of Artificial Intelligence Research 17, 229-264 (2002)
9. Denning, D.E., Schlšrer, J.: A fast procedure for finding a tracker in a statistical database. ACM Transactions on Database Systems 5(1), 88-102 (1980)
10. Dobkin, D., Jones, A.K., Lipton, R.J.: Secure databases: Protection against user influence. ACM Transactions on Database Systems 4, 97-106 (1979) (Pubitemid 9437765)
11. Chauhan, P., Clarke, E.M., Kroening, D.: Using SAT based Image Computation for Reachability. Carnegie Mellon University, Technical Report CMU-CS-03-151 (2003)
12. Köpf, B., Basin, D.: An information-theoretic model for adaptive side-channel attacks. In: Proceedings of the 14th ACM conference on Computer and communications security CCS 2007, pp. 286-296 (2007)
13. Landauer, J., Redmond, T.: A Lattice of Information. In: Proc. of the IEEE Computer Security Foundations Workshop. IEEE Computer Society Press, Los Alamitos (1993)
14. Malacaria, P.: Assessing security threats of looping constructs. In: Proc. ACM Symposium on Principles of Programming Language (2007)
15. Malacaria, P.: Risk Assessment of Security Threats for Looping Constructs. To appear in the Journal Of Computer Security (2009)
16. Nakamura, Y.: Entropy and Semivaluations on Semilattices. Kodai Math. Sem. Rep. 22, 443-468 (1970)
17. McCamant, S.A.: Quantitative Information-Flow Tracking for Real Systems. MIT Department of Electrical Engineering and Computer Science, Ph.D., Cambridge, MA (2008)
18. Terauchi, T., Aiken, A.: Secure information flow as a safety problem. In: Hankin, C., Siveroni, I. (eds.) SAS 2005. LNCS, vol. 3672, pp. 352-367. Springer, Heidelberg (2005)
19. Sweeney, L.: k-anonymity: a model for protecting privacy. International Journal on Uncertainty, Fuzziness and Knowledge-based Systems 10(5), 557-570 (2002)