Data and Applications Security XXIII: 23rd Annual IFIP WG - download pdf or read online

By Joachim Biskup, Jens Seiler, Torben Weibert (auth.), Ehud Gudes, Jaideep Vaidya (eds.)

ISBN-10: 3642030068

ISBN-13: 9783642030062

ISBN-10: 3642030076

ISBN-13: 9783642030079

This e-book constitutes the refereed complaints of the 23nd Annual IFIP WG 11.3 operating convention on facts and purposes protection held in Montreal, Canada, in July 2009.

The 18 revised complete papers and four brief papers have been conscientiously reviewed and chosen from forty seven submissions. The papers are geared up in topical sections on database protection; safety regulations; privateness; intrusion detection and protocols; and relied on computing.

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Read or Download Data and Applications Security XXIII: 23rd Annual IFIP WG 11.3 Working Conference, Montreal, Canada, July 12-15, 2009. Proceedings PDF

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Additional info for Data and Applications Security XXIII: 23rd Annual IFIP WG 11.3 Working Conference, Montreal, Canada, July 12-15, 2009. Proceedings

Sample text

Similarly, the second literal is the view predicate view employees(’alice’, Name, Addr, , , Optin). The view view employees is added to the FROM clause list and given an alias e. User = ’alice’ is added to the WHERE clause list. Optin, respectively, all of which are added to the list of variable bindings. The don’t-care symbols (underscores) are ignored, since they impose no conditions on the values in the view. The third literal is the built-in predicate =(Optin, ’true’). Optin = ’true’ to the WHERE clause list.

1. Threat Tree Forest An Approach to Security Policy Configuration 3 37 Semantic Threat Graphs A semantic threat graph is an extended threat tree that addresses the issues discussed in Section 2. A semantic threat graph can be defined as a graph that represents the semantics (meaning) of a threat domain. Intuitively, a semantic threat graph makes explicit the information that is typically implicit in a threat tree. Figure 2 provides a model of the components in a semantic threat graph and Figure 3 depicts an instantiation of this model for the threat tree example in the previous section.

Unintended access from the tier-1 through the dataNAC may be considered to have less of a threat impact if one can guarantee that firewalls upstream apply more restrictive port-forwarding controls. However, and in keeping with the defense-in-depth approach, countermeasure cntrsshT ier1Gen should be refined to have a more restrictive access policy. Analysis of security policy configuration is performed using the Semantic Web Rule Language SWRL [22]. SWRL complements DL providing the ability to infer additional information from DL constrained ontologies.

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Data and Applications Security XXIII: 23rd Annual IFIP WG 11.3 Working Conference, Montreal, Canada, July 12-15, 2009. Proceedings by Joachim Biskup, Jens Seiler, Torben Weibert (auth.), Ehud Gudes, Jaideep Vaidya (eds.)


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