Rule based Trust management using RT – third lecture Sandro Etalle University of Twente & Eindhoven thanks to Ninghui Li - Purdue William H. Winsborough.

Slides:



Advertisements
Similar presentations
Logical Model and Specification of Usage Control Xinwen Zhang, Jaehong Park Francesco Parisi-Presicce, Ravi Sandhu George Mason University.
Advertisements

A Logic Specification for Usage Control Xinwen Zhang, Jaehong Park Francesco Parisi-Presicce, Ravi Sandhu George Mason University SACMAT 2004.
Towards A Times-based Usage Control Model Baoxian Zhao 1, Ravi Sandhu 2, Xinwen Zhang 3, and Xiaolin Qin 4 1 George Mason University, Fairfax, VA, USA.
CS4026 Formal Models of Computation Part II The Logic Model Lecture 1 – Programming in Logic.
Completeness and Expressiveness
Temporal Logic and the NuSMV Model Checker CS 680 Formal Methods Jeremy Johnson.
Rigorous Software Development CSCI-GA Instructor: Thomas Wies Spring 2012 Lecture 11.
Rule based Trust management using RT - second lecture Sandro Etalle thanks to Ninghui Li - Purdue William H. Winsborough – University of Texas S. Antonio.
Identity Management Based on P3P Authors: Oliver Berthold and Marit Kohntopp P3P = Platform for Privacy Preferences Project.
Rule Based Systems Michael J. Watts
On Comparing the Expressing Power of Access Control Model Frameworks Workshop on Logical Foundations of an Adaptive Security Infrastructure (WOLFASI) A.
Privacy and Contextual Integrity: Framework and Applications Adam Barth, Anupam Datta, John C. Mitchell (Stanford), and Helen Nissenbaum (NYU) TRUST Winter.
Lecture 2 Page 1 CS 236, Spring 2008 Security Principles and Policies CS 236 On-Line MS Program Networks and Systems Security Peter Reiher Spring, 2008.
Trust Management II Anupam Datta Fall A: Foundations of Security and Privacy.
11 World-Leading Research with Real-World Impact! RT-Based Administrative Models for Community Cyber Security Information Sharing Ravi Sandhu, Khalid Zaman.
Winter 2004/5Pls – inductive – Catriel Beeri1 Inductive Definitions (our meta-language for specifications)  Examples  Syntax  Semantics  Proof Trees.
Dr. Alexandra I. Cristea CS 319: Theory of Databases: C3.
An Introduction to Decentralized Trust Management Sandro Etalle University of Twente thanks to William H. Winsborough – University of Texas S. Antonio.
Halting Problem. Background - Halting Problem Common error: Program goes into an infinite loop. Wouldn’t it be nice to have a tool that would warn us.
Partnering & Strategic Alliances
Reaching Goals: Plans and Controls
1st MODINIS workshop Identity management in eGovernment Frank Robben General manager Crossroads Bank for Social Security Strategic advisor Federal Public.
Role-based Trust Management Security Policy Analysis and Correction Environment (RT-SPACE). Gregory T. Hoffer CS7323 – Research Seminar (Dr. Qi Tian)
Lecture 18 Page 1 CS 111 Online Design Principles for Secure Systems Economy Complete mediation Open design Separation of privileges Least privilege Least.
McGraw-Hill/Irwin Copyright © 2008 by The McGraw-Hill Companies, Inc. All rights reserved. Reaching Goals: Plans and Controls Today’s smart supervisor.
CS590U Access Control: Theory and Practice Lecture 21 (April 11) Distributed Credential Chain Discovery in Trust Management.
TRUST NEGOTIATION IN ONLINE BUSINESS TRANSACTIONS BY CHANDRAKANTH REDDY.
Rule based Trust management using RT Sandro Etalle thanks to Ninghui Li - Purdue William H. Winsborough – University of Texas S. Antonio. The DTM team.
POLIPO: Policies & OntoLogies for Interoperability, Portability, and autOnomy Daniel Trivellato.
Ninghui Li (Purdue University) 2 nd Int’l Summer School in Computation Logic June 17, 2004 Logic and Logic Programming in Distributed Access Control (Part.
1 Security on Social Networks Or some clues about Access Control in Web Data Management with Privacy, Time and Provenance Serge Abiteboul, Alban Galland.
Team Roles. Logvinovich Kristina BTK91. Meredith Belbin. Meredith Belbin is a British researcher and management theorist, best known for his work on management.
Security Policies and Procedures. cs490ns-cotter2 Objectives Define the security policy cycle Explain risk identification Design a security policy –Define.
On Reducing the Global State Graph for Verification of Distributed Computations Vijay K. Garg, Arindam Chakraborty Parallel and Distributed Systems Laboratory.
5.3 Geometric Introduction to the Simplex Method The geometric method of the previous section is limited in that it is only useful for problems involving.
Confidentiality-preserving Proof Theories for Distributed Proof Systems Kazuhiro Minami National Institute of Informatics FAIS 2011.
COMP 111 Threads and concurrency Sept 28, Tufts University Computer Science2 Who is this guy? I am not Prof. Couch Obvious? Sam Guyer New assistant.
MA 1128: Lecture 17 – 6/17/15 Adding Radicals Radical Equations.
Reading and Writing Mathematical Proofs Spring 2015 Lecture 4: Beyond Basic Induction.
More on Description Logic(s) Frederick Maier. Note Added 10/27/03 So, there are a few errors that will be obvious to some: So, there are a few errors.
ARTIFICIAL INTELLIGENCE [INTELLIGENT AGENTS PARADIGM] Professor Janis Grundspenkis Riga Technical University Faculty of Computer Science and Information.
Computer Science 1 Mining Likely Properties of Access Control Policies via Association Rule Mining JeeHyun Hwang 1, Tao Xie 1, Vincent Hu 2 and Mine Altunay.
Securing Passwords Against Dictionary Attacks Presented By Chad Frommeyer.
Usable Security – CS 6204 – Fall, 2009 – Dennis Kafura – Virginia Tech Automatic Trust Negotiation Rajesh Gangam
Manipulating the Quota in Weighted Voting Games (M. Zuckerman, P. Faliszewski, Y. Bachrach, and E. Elkind) ‏ Presented by: Sen Li Software Technologies.
KR A Principled Framework for Modular Web Rule Bases and its Semantics Anastasia Analyti Institute of Computer Science, FORTH-ICS, Greece Grigoris.
Introduction to Access Control and Trust Management Daniel Trivellato.
1 Reasoning with Infinite stable models Piero A. Bonatti presented by Axel Polleres (IJCAI 2001,
Copyright 2001, Matt Dwyer, John Hatcliff, and Radu Iosif. The syllabus and all lectures for this course are copyrighted materials and may not be used.
ece 627 intelligent web: ontology and beyond
Rule based Trust management using RT – third lecture Sandro Etalle University of Twente & Eindhoven thanks to Ninghui Li - Purdue William H. Winsborough.
Policy-Based Dynamic Negotiation for Grid Services Authorization Ionut Constandache, Daniel Olmedilla, Wolfgang Nejdl Semantic Web Policy Workshop, ISWC’05.
Newcastle uopn Tyne, September 2002 V. Ghini, G. Lodi, N. Mezzetti, F. Panzieri Department of Computer Science University of Bologna.
Enable Semantic Interoperability for Decision Support and Risk Management Presented by Dr. David Li Key Contributors: Dr. Ruixin Yang and Dr. John Qu.
Daniel Kroening and Ofer Strichman 1 Decision Procedures An Algorithmic Point of View Basic Concepts and Background.
DBC NOTES. Design By Contract l A contract carries mutual obligations and benefits. l The client should only call a routine when the routine’s pre-condition.
Lecture 041 Predicate Calculus Learning outcomes Students are able to: 1. Evaluate predicate 2. Translate predicate into human language and vice versa.
INF3110 Group 2 EXAM 2013 SOLUTIONS AND HINTS. But first, an example of compile-time and run-time type checking Imagine we have the following code. What.
Lecture 3 Page 1 CS 236 Online Security Mechanisms CS 236 On-Line MS Program Networks and Systems Security Peter Reiher.
1 Authorization Sec PAL: A Decentralized Authorization Language.
Wishnu Prasetya Extended Static Checking (LN Chapter 2)
Metalogic Soundness and Completeness. Two Notions of Logical Consequence Validity: If the premises are true, then the conclusion must be true. Provability:
On Abductive Equivalence Katsumi Inoue National Institute of Informatics Chiaki Sakama Wakayama University MBR
Artificial Intelligence Knowledge Representation.
Decentralized Access Control: Overview Deepak Garg Foundations of Security and Privacy Fall 2009.
Decentralized Access Control: Policy Languages and Logics
Kent Seamons Brigham Young University Marianne Winslett, Ting Yu
Beyond Proof-of-compliance: Security Analysis in Trust Management
This Lecture Substitution model
Protecting Privacy During On-line Trust Negotiation
Presentation transcript:

Rule based Trust management using RT – third lecture Sandro Etalle University of Twente & Eindhoven thanks to Ninghui Li - Purdue William H. Winsborough – University of Texas S. Antonio. The DTM team of the UT (Marcin, Jeroen, Jerry). And the many people I’ve taken ideas from for this lecture (Winslett, Li, Seamons…)

FOSAD 2006 summer schoolEtalle: Rule Based Trust Management with RT 2 Summary: A, B, D: principals r, r1, r2: role names A.r: a role (a principal + a role name) Four types of credentials:  A.r  D Role A.r contains principal D as a member  A.r  B.r 1 A.r contains role B.r 1 as a subset  A.r  A.r 1.r 2 A.r  B.r 2 for each B in A.r 1  A.r  A 1.r 1  A 2.r 2 A.r contains the intersection

FOSAD 2006 summer schoolEtalle: Rule Based Trust Management with RT 3 Example: find the semantics Alice.s  Alice.u.v Alice.u  Bob Bob.v  Charlie Bob.v  Charlie.s What is the semantics?

Back to expressivity issues

RT0 limitations attributes (parameters) threshold separation of duty FOSAD 2006 summer schoolEtalle: Rule Based Trust Management with RT 5

Attributes (parameters) How can you make clear that Alice is the manager of Sandro and Bob is the manager of Eve.  FC.managerof(Sandro) <- Alice.  FC.managerof(Eve) <- Bob. Extends to Rules  FC.evaluatorof(?X) <- FC.managerof(?X). These are defined in RT1  RT1 has the concept of constraints and of domains for variables.  Important: study the syntax of RT1 FOSAD 2006 summer schoolEtalle: Rule Based Trust Management with RT 6

Additional Dialects Logical Sets (RT2)  skip it Threshold and Separation of duties (RTT)  check this out Delegation of role activation (RTD)  skip it I expect students to be able to say if a given policy can be expressed in RT0 and/or RT1 and if not, why. FOSAD 2006 summer schoolEtalle: Rule Based Trust Management with RT 7

FOSAD 2006 summer schoolEtalle: Rule Based Trust Management with RT 8 A personal view on negation in TM. Negation is good provided that  It is always in a context GOOD: all doctors that don’t have a specialty BAD: all non-doctors.  The negated predicate should rely on a definition we can “count on” Eg: FC.acc  FC.acc2 – FC.buyer FC should be able to tell who populates FC.buyer without having to beg around for credentials. See paper by Czenko et. al  (yes, I confess, I am one of the authors).

FOSAD 2006 summer schoolEtalle: Rule Based Trust Management with RT 9 Non-monotonicity In the Flexible Company FC, a buyer may not be an accountant. How do we do this?

FOSAD 2006 summer schoolEtalle: Rule Based Trust Management with RT 10 First way of solving this Use negation in the policies  FC.acc  FC.acc2 – FC.buyer When is Alice a member of FC.acc?  If Alice is a member of FC.acc2  AND Alice is NOT a member of FC.buyer But how do we determine that Alice is NOT a member of FC.buyer?  The easy way: if Alice is not in [[FC.buyer]] We are making a nonmonotonic inference.  What is nonmonotonicity?  What is the problem with nonmonotonicity?

Monotonic vs nonmonotonic A monotonic system satisfies the following  For each A, B.r, P and P'  If A is a member of [[B.r]] in policy P  and P' contains P  Then A is a member of [[B.r]] also in P' RT0 is monotonic But if we introduce negation it is not monotonic any longer Exercise: find an example of this FOSAD 2006 summer schoolEtalle: Rule Based Trust Management with RT 11

Why do we need monotonicity? Because in TM  Peers may not be available  Peers may withhold some information If you can't discover a credential  In a monotonic system the worst it can happen is that you do not manage to deduce something that is right  In a non-monotonic system you could make a wrong deduction This is because the absence of a credential is interpreted as "presence of negative information" It is a form of negation-as-failure FOSAD 2006 summer schoolEtalle: Rule Based Trust Management with RT 12

How do you solve the problem? You have to make sure that you are able to discover all the credentials of the policy that may occur "under negation". This prevents you from making wrong inferences. FOSAD 2006 summer schoolEtalle: Rule Based Trust Management with RT 13

FOSAD 2006 summer schoolEtalle: Rule Based Trust Management with RT 14 A second way of solving this Using an integrity constraint. FC.log ⊒ FC.buyer  FC.accountant Need a mechanism to monitor it. External to the RT system.  See Etalle & Winsborough…

FOSAD 2006 summer schoolEtalle: Rule Based Trust Management with RT 15 Why Integrity Constraints Policies do change: P  P 1 ...  P n A principal controls only a portion of the policy  Statements may be added or removed by other principals  nowadays: trusted principals give no feedback to the trusting ones Delegating trust implies an understanding between principals,  nowadays: not formalized Trusted principals need assistance in understanding global impact of delegations, revocations  Who could get access to what? (Safety) Assessing exposure  Who could be denied? (Availability) Ensuring applications have authorizations needed for correct operation

FOSAD 2006 summer schoolEtalle: Rule Based Trust Management with RT 16 Problem Instances “No-one should ever be both a buyer and an accountant”  Mutual Exclusion “Welders of BOVAG-accredited workshops should be fellows of the British Institute of Welding”  Containment “Every employee should have access to the WLAN network”  Containment, Availability

FOSAD 2006 summer schoolEtalle: Rule Based Trust Management with RT 17 Integrity Constraints: General Form General: L.l ⊒ R.r  L.l ⊒ R.r holds in P iff [[L.l]] P  [[R.r]] P  L.l and R.r may be sets and intersections of roles Special cases  Membership: A.r ⊒ { D 1, …, D n }  Boundedness: { D 1, …, D n } ⊒ A.r  expressiveness is limited (it is a universal formula) but we can express all safety properties of [LWM03]  counterexample: at least a manager should have access to the DB

FOSAD 2006 summer schoolEtalle: Rule Based Trust Management with RT 18 Exercise: find the right constraint: buyers and accountants should be disjoint every employee should have access to the WLAN network welders of BOVAG-accredited workshops should be fellows of the British Institute of Welding Bovag.welder  Bovag.accr.welder Bovag.accr  PietersWorkshop PietersWorkshop.welder  Pieter

FOSAD 2006 summer schoolEtalle: Rule Based Trust Management with RT 19 Answers buyers and accountants should be disjoint   ⊒ A.buyer  A.accountant every employee should have access to the WLAN network  WLAN.access ⊒ UT.employee welders of BOVAG-accredited workshops should be fellows of the British Institute of Welding Bovag.welder  Bovag.accr.welder Bovag.accr  PietersWorkshop PietersWorkshop.welder  Pieter  BIW.fellow ⊒ Bovag.welder

FOSAD 2006 summer schoolEtalle: Rule Based Trust Management with RT 20 The technical problem (a taste of research) P  P1 ...  Pn: policy change L.l ⊒ R.r: a constraint Need a (minimal) mechanism such that  IF L.l ⊒ R.r does not hold in Pi  THEN a warning is fired  without checking L.l ⊒ R.r each time a credential is added/removed How: by monitoring when some credentials are added or removed

FOSAD 2006 summer schoolEtalle: Rule Based Trust Management with RT 21 The solution in short P – policy, Q = L.l ⊒ R.r – IC Define 2 set of roles:  G = roles R.r depends on  S = roles satisfying [[L.l]] P|S  [[R.r]] P Theorem: Let P  P1 ...  Pn IF  P satisfies Q  no credential S is removed  no credential for G is added THEN  Pn satisfies Q  G and S don’t have to be recomputed

FOSAD 2006 summer schoolEtalle: Rule Based Trust Management with RT 22 The method P – policy, Q = L.l ⊒ R.r: constraint CHECKING FIRST, compute [[R.r]] P  here G is computed “for free” THEN, for each X  [[R.r]] P, check that X  [[L.l]]  here (one of the) S is computed “for free” MONITORING Let P  P1 ...  Pn IF  no credential for S is removed  no credential for G is added Then  OK Otherwise  Check Q again, and  Recompute G and S (even if Q still holds) To monitor this we need the cooperation of other principals

FOSAD 2006 summer schoolEtalle: Rule Based Trust Management with RT 23 Conclusions Integrity constraints:  tool to control a TM system. Monitoring requires the cooperation of trusted principals Trust management becomes a two way process  from the trusting to the trusted  and vice-versa

FOSAD 2006 summer schoolEtalle: Rule Based Trust Management with RT 24 Conclusions for the whole RT part Context:  2 or more parties in an open system.  parties are not in the same security domain. Goal  establish trust between parties to exchange information and services (access control) Constraint  access control decision is made NOT according to the party identity BUT according to the credentials it has

FOSAD 2006 summer schoolEtalle: Rule Based Trust Management with RT 25 Open problems Analysis  safety analysis we are now working with Spin in RT0, for RTC (with constraints) nothing is available  of negotiations protocols w.r.t. the TM goals. Integration with other systems  e.g. privacy protection location-dependent policies  ambient calculi? DRM Semantics is not correct when considering:  chain discovery  negotiations is not modular  certainly possible to improve this using previous work on omega-semantics. Types