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Table 12 Default Privacy-Authorizations Table purpose table attributes authorized-users
2006
"... In PAGE 12: ...If an enterprise has already defined a privacy authorization table, this latter table can be compared with the new one to verify whether it does not disclose more information than needed. Example 6 Table12 shows the privacy authorization table derived from minimum cost path in Fig. 4.... In PAGE 12: ... This corre- sponds to the need-to-know principle for which data subjects want to ensure that their data are not delegated to recipients that do not need it. Therefore, in our scenario, Mississippi should not be entitled to access credit card information for credit assessment or shipping address for direct delivery as the minimal privacy authorization table shows ( Table12 ). In practice, these data should be channelled directly to the cor- responding partners.... ..."
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Table 1: Information decoupling in a printing scenario Component Information revealed
"... In PAGE 4: ... Using the information in these tickets, the service can make a decision whether to authorize the user or not (step 8). To illustrate the decoupling of information, Table1 shows what information is revealed to which component in a scenario where a user is trying to access a printer in a particular room by getting a ticket from the printing TGS. Table 1: Information decoupling in a printing scenario Component Information revealed ... ..."
Table 5. Purposes end-users gave for using career information in the future, according to CCC (1998)
2002
Table 10: Default Privacy-Authorizations Table
in Abstract
2005
"... In PAGE 14: ...Table10 (Appendix B) shows the PAT derived from minimum cost path in Fig. 4.... In PAGE 19: ... B Comparison among Privacy-Authorizations Tables The privacy authorization tables derived by privacy policies tables presented in Appendix A by using the Hippocratic database approach are in Table 8 and 9. Table10 and 11 show the privacy authorization tables derived from the minimal decomposition path in Fig. 4 and 8, respectively.... In PAGE 19: ... This entails that they do not implement the notion of minimality of disclosure of information with respect to preferences of single users. For example, Mississippi is authorized to access both email and fax number for notifying the status of the order (Table 8) when just one of these data items is necessary and suf cient to achieve noti cation purpose ( Table10 and 11). Furthermore, Table 8 and 9 show how the Hippocratic database approach grants additional unnecessary authorizations.... In PAGE 19: ... This is corresponds to need-to- know principle for which data owners want to ensure that their data are not delegated to recipients that do not need to have permission on it. For instance, Mississippi should not access credit card information for credit assessment as show in Table10... ..."
Table 2. USDA Homeland Security Funding, by Function Budget authority, including user fees ($ million)
2004
"... In PAGE 4: ...................20 Table2 . USDA Homeland Security Funding, by Function .... In PAGE 26: ...! Defending against catastrophic threats ! Emergency preparedness and response Table2 presents the information by homeland security function. Over a multi- year period, border inspections are the largest USDA homeland security activity even after most of the inspectors were transferred to DHS.... ..."
Table 2 Authority and Leadership-Patterns Across Cases
"... In PAGE 9: ... (Additional information on the data analysis is provided in the appendix.) Authority and Leadership Patterns Across Cases Table2 summarizes and compares the leadership and authority patterns for our four cases. The short narratives below provide the basis of the assessment for each case.... ..."
Table 2. IT User Information
Table 4.The top 20 authors with the highest loadings on each of the first four factors5.
1999
"... In PAGE 9: ...he top four factors alone explain 52.1% of the variance. Each extracted factor corresponds to a research area in hypertext. These research areas are categorised based on the profiles of the top 20 authors, ranked by their factor loadings ( Table4 ). The research areas corresponding to the first four factors are identified as (1) classic hypertext, (2) information retrieval, (3) graphical user interfaces and information visualisation, and (4) links and linking mechanisms.... ..."
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