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class viewall; } /* create a last resort local login account */ user admin { full-name Last resort account ; uid 9999; class mysuperuser; authentication { encrypted-password <encrypted password> ; } } } services { /* permit ftp only when specifically needed. Otherwise leave deactivated */ inactive: ftp { connection-limit 1; rate-limit 1; } /* permit only SSHv2 authentication */ ssh { root-login deny; protocol-version 2; connection-limit 4; rate-limit 4; } /* permit telnet only if SSH is not available - e.g. export releases */ inactive: telnet { connection-limit 4; rate-imit 4; } } /* configure system logging */ syslog { archive size 10m files 10; user * { any emergency; } host 195.111.253.3 { any info; } host 195.111.254.3 { any info; } file messages { any info; authorization info; } file security.log { interactive-commands any; archive size 10m files 10; } }

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location This means that if one knew that an individual fitted these criteria it would be possible to search for them Even without these tell-tale criteria, participation in a longitudinal survey, almost by definition, means that there will be repeated contacts between the study team and the study members that may increase the likelihood that attention will be drawn to an individual s participation For example, ALSPAC invites children to visit clinics where measurements are taken, and the density of study children in local schools means that discussion at the school-gate about participation is almost inevitable (and indeed is welcomed) In these and other similar cases, an outside observer might relatively easily identify a study member if very strict controls were not imposed As a result, ALSPAC have traditionally had stringent data control arrangements Many longitudinal surveys have multiple sample members within a household (for example, MCS, ELSA and BHPS).

Summary

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In some cases, these individuals may even give some of their responses in each other s presence An individual with the right set of skills may be able to find their own record on a dataset, and by association is quite likely to find that of their partner, child or other household member It is unlikely that someone would wish to do this and have the wherewithal to do so, but it is not inconceivable, particularly when we remember that households split and that some longitudinal surveys (such as BHPS and ELSA) will continue to follow several parties To some extent, the complexity involved in carrying out longitudinal analysis may provide a natural barrier to casual or accidental abuse Nevertheless, the arguments above suggest that our approach to the protection of confidentiality and the avoidance of disclosure could, perhaps, be based on stricter criteria.

It doesn't appear that you are making many changes to the proxy object. The chief difference in the RMI version is that you aren't going to deploy this proxy object anymore but instead are going to deploy a stub generated from it. You are preparing the stub to communicate back over the wire to the object that will stay with the service object and actually perform the calculation. Here's the new proxy code.

This is something that is implicitly or explicitly acknowledged by many longitudinal survey teams The various levels of controls exercised by some of the main longitudinal surveys are illustrated in the following examples: (1) Signed agreement from the study investigators is needed before data from surveys such as NCDS and BCS70 can be released from the social science data archive by the (UK) Economic and Social Data Service (ESDS) The ESDS has recently introduced special licenses to provide additional controls for more sensitive datasets (see wwwesdsacuk/orderingdata/speciallicenceasp) Some longitudinal surveys only allow analysis to take place in a secure data enclave, or by using special tools that facilitate secure remote analysis This is true of the ONS Longitudinal Study and the Scottish Longitudinal Study, which do not allow any data to be released externally.

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