PCL: A Policy Combining Language EXAM: E nvironment for X acml policy A nalysis & M anagement

1. Access Control Policy Combining & Comparison • PCL: A Policy Combining Language • EXAM: Environment for Xacml policy Analysis & Management Elisa Bertino, Ninghui Li (Purdue University)

2. Why Policy Combining? • A policy may contain multiple sub-policies. The effect of the whole policy is determined by combining the effects of sub-policies • Firewalls: first-applicable • XACML: deny-overrides, permit-overrides, first-applicable, only-one-applicable

3. Other Useful Combining Algorithms • Weak-consensus: • Strong-consensus: • Weak-majority: • Strong-majority:

4. Our Goal An expressive and practical language for specifying policy combining algorithms Our solution: PCL NINGHUI LI, ELISA BERTINO, QIHUA WANG, WAHBEH QADARJI Purdue University

5. Overview of PCL • Uses four values: Σ = {P, D, NA, IN} • Evaluation errors are represented by non-empty subsets of {P, D, NA, IN} • 15 possible values • Two ways to specify policy combining behavior • Using a Policy Combining Operator (PCO) • Using linear constraints

6. Policy Combining Operators • Policy combining operator (PCO) • is a PCA that combines two policies (or rules) • g: Σ × Σ -> Σ, where Σ = {P, D, NA, IN} • A PCO can be represented as a matrix Deny-overrides First-applicable

7. Deny-overrides Any Any P D D P Any Any P, NA Any D, IN D, IN D IN P P IN NA NA IN NA NA From PCO to PCA • PCA should be a function Σ+ -> Σ • Given a PCO g, its recursive PCA is the function f: • f(P1) = P1 • f(P1, P2) = g(P1, P2) • f(P1,…,Pn) = g(f(P1,…,Pn-1), Pn) • DFA-representation of policy evaluation First-applicable

8. Using Linear Constraints • PCOs cannot express counting-based strategies. • Second approach for PCA specification uses linear constraints on the number of sub-policies that return P, D, NA, and IN. • A Linear Constraint is an expressions that uses #P, #D, #NA, #IN, addition/subtraction, comparisons, and AND  and OR 

9. Other Issues We Considered • Optimized evaluation of PCAs • Specify how to specify obligation-handling behavior in a PCA

10. Expressive Power: There are Examples for each numbered area

11. Using PCL in XACML • An XACML Policy can include the PCA it wants to use • A PDP that understands PCL can parse and understand all PCAs specified in it • makes deployment of new PCAs feasible

12. Implementation • We implemented PCL and integrated it with Sun’s implementation for XACML 1.1 • Changes and additions were made to several classes and the Result class in particular to account for errors in evaluation

13. EXAM Environment for Xacml policy Analysis & Management EXAM is a comprehensive environment for analyzing and managing XACML access control policies. It supports acquisition, editing and retrieval of policies in addition to policy similarity filtering, policy similarity analysis and policy integration. ELISA BERTINO, NINGHUI LI, GABRIEL GHINITA, PRATHIMA RAO Purdue University

14. User User User User Interface Policy Annotation PolicyRepository EXAM Overview: Architecture … Query Dispatcher PolicySimilarity Filter Policy Integration Framework Policy Similarity Analyzer

15. Key Feature –Policy Similarity Analysis • Goal • Characterize the relationships among the sets of requests respectively authorized by a set of policies. • Two techniques • Policy Similarity Filter • Less precise, faster (based on techniques from document matching techniques) • Policy Similarity Analyzer • Precise, slower (based on MTDBB) • A visualization environment has been developed to visualize policy similarity results

16. Multi-level Grid Visualizationof Policy Similarity p3 <Time  [9am,1am]> p4 <Time  [1am,9am]> “DRILL-DOWN” Action Type

17. Policy Integration • A Fine-grained Integration Algebra (FIA) • 3-valued (Permit, Deny, NotApplicable) • Specify behavior at the granularity of requests and effects • Restrict domain of applicability • Support expressive policy languages like XACML • Framework for specifying integration constraints and generating integrated policies. • MTBDD based implementation of FIA • Generation of integrated policy in XACML syntax.

18. Fine-grained Integration Algebra (FIA) Vocabulary of attribute names and domains Unary operators Negation Domain Projection Policy constants Permit policyDeny policy Binary operators Addition Intersection

19. FIA - Theoretical Results • Expressivity • FIA can express all XACML policy combining algorithms • FIA can express policy “jumps” • FIA can model closed policies and open policies • Completeness • A completeness notion has been developed, based on the concept of policy combination matrix, and FIA is complete with respect to such notion • Minimality • Identification of the minimal complete subsets of the FIA operators

20. Current Status of EXAM • A prototype has been completed that includes the similarity filter and analyzer • The visualization tool has been completed • We expect to release EXAM to the project team in December 2009

21. On-Going Work • Study the specification and analysis of stateful policies in a practical way • e.g., by extending XACML • User experimental study – the goal is to assess whether the similarity filter is a good predictor for policy similarity as perceived by users • Extend EXAM with tools for synonym and dictionary management, and ontologies • Develop tools for collaborative privacy-preserving policy enforcement