240 likes | 398 Views
An Attribute-based Authorization Policy Framework with Dynamic Conflict Resolution. Apurva Mohan Douglas M. Blough Georgia Institute of Technology. Contents. Problem introduction Motivating scenario Proposed solution Performance of the proposed framework Conclusion. Introduction.
E N D
An Attribute-based Authorization Policy Frameworkwith Dynamic Conflict Resolution Apurva Mohan Douglas M. Blough Georgia Institute of Technology
Contents • Problem introduction • Motivating scenario • Proposed solution • Performance of the proposed framework • Conclusion
Introduction • Policy based authorization systems • Role-based vs. attribute-based systems • Multi-authority systems • Conflicts in policy decisions
Problem Introduction • Conflict resolution in current systems is static • Most policy based systems do not provide modularity • Difficult to add or remove special purpose policies • Evaluation of a large number of non-applicable rules • Fast indexing scheme for finding applicable policies
Motivating Scenario Superior Health Care (SHC) Proxy request Alex’s policy Data source policy response Querier SHC’s policy Regulatory policy EMR Repository
Scenario – Cont. Alex’s Policy Deny Overrides Permit Overrides 1 2 3 1 2 3 Normal Emergency
Proposed Solution • Dynamic Conflict Resolution • Decide Applicable policies based on context • Dynamically include (remove) specialized policies • Increase modularity of policies • Increasing the efficiency of policy target matching
Motivating Scenario revisited What Alex wants – • Only his Doctor can access his EMR • During his trip, ‘Doctors’ or ‘paramedics in Florida’ can access his EMR • Attributes used – Alex’s location, Doctor’s credentials, paramedics credentials and location, Alex’s trip duration
Motivating Scenario revisited Location Provider Atlanta Proxy Server Alex’s policy (‘doctor’ or ‘paramedic in FL’) and (AlexLocation = FL) and (date = [d1,d2]) P1 P2 P3 Florida EMR Repository paramedic in FL
Scenario - Continued Location Provider Atlanta Proxy Server Alex’s policy (‘doctor’ or ‘paramedic in FL’) and (AlexLocation = FL) and (date = [d1,d2]) P1 P2 P3 Florida EMR Repository paramedic in FL
Experimental Setup • Total Applicable Policy Set evaluation • 1,2,4 and 8 rules/policy • 1,10, 100, 1000 and 10000 policies • PCA selection evaluation • 7 PCA’s, 2-10000 attributes/rule • Evaluation time • 1,2,4,and 8 rules/policy • 1,10,100, 1000 and 10000 policies
Conclusion • Proposed a framework for dynamically changing the PCA • Selecting the applicable policies in a dynamic and efficient manner • Included modularity in policies • Add/remove specialized policies dynamically