Source: N. Damianou, A. Bandara, M. Sloman, and E. Lupu. A Survey of Policy Specification Approaches. Technical re- port, Department of Computing, Imperial College of Sci-
ence Technology and Medicine, London, 2002.
Jajodia et al. 1997, proposes that a conflict, once detected could be handled in one of three ways. The most obvious and simplest one is for the system to declare an error condition whenever a conflict arises. However, this solution is not particularly interesting since it does not allow for the system to automatically recover from the conflicting scenario. Other solutions are to allow the positive policy to override; or to let the negative policy override. The latter strategy is adopting an approach of ‘‘do no harm’’, based on the assumption that the negative policy (i.e. the one that prevents an action being performed) has a more benign effect on the system than its conflicting counterpart. As would be expected, the positive policy override strategy is the exact converse of the negative override approach described.
In addition to the negative and positive override strategies mentioned above, [Lupu and Sloman 1999] also identifies some alternatives. One approach suggested is to assign explicit priorities to every policy. This way when a conflict arises the agent enforcing the policy could simply compare the priority values and enforce the policy that has the highest priority. However, this approach could easily lead to inconsistent behaviour of the system if, as is common in distributed systems, multiple people are responsible for defining policies and assigning their priorities. Other strategies suggested include giving priority to the policy that is ‘closest’ to the managed object; or using the specificity of the policy definition to determine the priority.
[Moffet and Sloman 1993] introduces the idea of policy hierarchies and the application of policy refinement to derive lower-level, more specific policies from high-level ones.
policy refinement is to transform high-level policy specifications into more specific policies that would be better suited for use in different execution environments.
ence Technology and Medicine, London, 2002.
Jajodia et al. 1997, proposes that a conflict, once detected could be handled in one of three ways. The most obvious and simplest one is for the system to declare an error condition whenever a conflict arises. However, this solution is not particularly interesting since it does not allow for the system to automatically recover from the conflicting scenario. Other solutions are to allow the positive policy to override; or to let the negative policy override. The latter strategy is adopting an approach of ‘‘do no harm’’, based on the assumption that the negative policy (i.e. the one that prevents an action being performed) has a more benign effect on the system than its conflicting counterpart. As would be expected, the positive policy override strategy is the exact converse of the negative override approach described.
In addition to the negative and positive override strategies mentioned above, [Lupu and Sloman 1999] also identifies some alternatives. One approach suggested is to assign explicit priorities to every policy. This way when a conflict arises the agent enforcing the policy could simply compare the priority values and enforce the policy that has the highest priority. However, this approach could easily lead to inconsistent behaviour of the system if, as is common in distributed systems, multiple people are responsible for defining policies and assigning their priorities. Other strategies suggested include giving priority to the policy that is ‘closest’ to the managed object; or using the specificity of the policy definition to determine the priority.
[Moffet and Sloman 1993] introduces the idea of policy hierarchies and the application of policy refinement to derive lower-level, more specific policies from high-level ones.
policy refinement is to transform high-level policy specifications into more specific policies that would be better suited for use in different execution environments.
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