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.
Read or Download Data and Applications Security and Privacy XXIV: 24th Annual IFIP WG 11.3 Working Conference, Rome, Italy, June 21-23, 2010. Proceedings PDF
Best security books
Constructing a data safeguard software that clings to the primary of protection as a company enabler needs to be step one in an enterprise’s attempt to construct an efficient safeguard application. Following within the footsteps of its bestselling predecessor, info defense basics, moment version offers details safety execs with a transparent figuring out of the basics of safeguard required to handle the variety of concerns they'll adventure within the box.
Securing VoIP: preserving Your VoIP community secure will assist you take the initiative to avoid hackers from recording and exploiting your company's secrets and techniques. Drawing upon years of useful event and utilizing various examples and case experiences, know-how guru Bud Bates discusses the enterprise realities that necessitate VoIP method safety and the threats to VoIP over either cord and instant networks.
This booklet constitutes the refereed court cases of the sixth overseas convention on belief and privateness in electronic enterprise, TrustBus 2009, held in Linz, Austria, in September 2009 at the side of DEXA 2009. The sixteen revised complete papers offered have been rigorously reviewed and chosen from various submissions.
This ebook offers the complaints of the seventh overseas convention on belief, P- vacy and defense in electronic enterprise (TrustBus 2010), held in Bilbao, Spain in the course of August 30–31, 2010. The convention endured from past occasions held in Zaragoza (2004), Copenhagen (2005), Krakow (2006), Regensburg (2007), Turin (2008) and Linz (2009).
Additional info for Data and Applications Security and Privacy XXIV: 24th Annual IFIP WG 11.3 Working Conference, Rome, Italy, June 21-23, 2010. Proceedings
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 , 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.