Data and Applications Security and Privacy XXIV: 24th Annual by Shiyuan Wang, Divyakant Agrawal, Amr El Abbadi (auth.), Sara

By Shiyuan Wang, Divyakant Agrawal, Amr El Abbadi (auth.), Sara Foresti, Sushil Jajodia (eds.)

This booklet constitutes the court cases of the twenty fourth Annual IFIP WG 11.3 operating convention on information and purposes protection, held in Rome Italy in June 2010. The 18 complete and eleven brief papers offered during this quantity have been rigorously reviewed and chosen from sixty one submissions. the subjects coated are question and information privateness; facts defense; entry keep an eye on; info confidentiality and question verification; coverage definition and enforcement; and belief and identification management.

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Example text

A Logic of Privacy 19 for (key) identification. -A countable set A of named atomic actions, where a0 , a1 , . . are used to denote arbitrary action identifiers. -A countable set R of resource identifiers, where r0 , r1 , . . denote arbitrary resources, r(t1 , . . , tn ) is an arbitrary n-place relation and ti (1 ≤ i ≤ n) is a term, a function, a constant or a variable. -A countable set P of purposes, where p0 , p1 , . . are used to denote arbitrary purpose identifiers. -A countable set of meta-policy identifiers; for example, c (for closed policies), o (for open policies), do (for a denials override policy), .

ACM Trans. Inf. Syst. Secur. 12(1) (2008) 22. : Flexible support for multiple access control policies. ACM TODS 26(2), 214–260 (2001) 23. : IT-Security and Privacy. edu Abstract. Publishing decision trees can provide enormous benefits to the society. Meanwhile, it is widely believed that publishing decision trees can pose a potential risk to privacy. However, there is not much investigation on the privacy consequence of publishing decision trees. To understand this problem, we need to quantitatively measure privacy risk.

The work here is dedicated to solve a significantly different problem, that is, to understand the privacy breach when a decision tree is published. Besides, the modeling processes differ far from each other. In [19], all the constraints are explicit according to the disguised dataset. For decision trees, not only do we need to consider the information explicitly in decision trees, we also need to consider the implicit information in decision trees that might cause privacy disclosure. 38 Z. Zhu and W.

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