Security Policy Reconciliation in Distributed Environments

1
Security Policy Reconciliation in Distributed
Environments

• Hao Wang, Somesh Jha, Miron Livny
• University of Wisconsin

Patrick D. McDaniel ATT Research
2
Policy Reconciliation

• To reconcile multiple policies among participants

Session policy
1. 2.
1. 2. 3.
Alice
Bob
3
MotivationSecure Communication
SSH Session
Server Policy Client Policy
SSH Protocol 1. SSH1 2. SSH2 1. SSH2
Different requirement
Encryption 1. AES-128 1. 3DES 1. AES-128 1. 3DES
MAC 1. HMAC-SHA1 2. HMAC-MD5 1. HMAC-MD5 2. HMAC-SHA1
Different preference
Compression 1. None 2. Zlib 1. Zlib 2. None
Different preference
4
MotivationResource Sharing

• Policy reconciliation also occurs in
  collaborative environments
• E.g. GRID, Condor, SETI_at_Home
• Policies may change frequently

1. MUST authenticate
2. Use PKI
3. Use Kerberos
4. MUST encrypt all channels
5. Use AES-128

1. MUST authenticate
2. Use PKI
3. Use Kerberos
4. MUST encrypt all channels
5. Use AES-128
6. Use DES-128
7. Use Blowfish-128
8. MAY use integrity check
9. HMAC-MD5

?
Internet
?

1. MUST authenticate
2. Use Kerberos
3. MAY encrypt all channels
4. Use AES-128

5
Recurring Theme

• Each site/host/user may have
• Different security requirements
• Different security preferences
• Session policy is dynamic

Internet
6
Policy Reconciliation

• To establish a provisioning session policy among
  participants

Session policy
1. 2.
1. 2. 3.
Alice
Bob
Reconciliation Engine
7
Problem Domain

• We deal with session provisioning policy
• E.g. a secure session between two parties
• We do not deal with
• Policy decisions
• Policy constructions, transformations
• Resolving policy conflicts
• Separation of policies and mechanisms
• Our work provides the mechanism

8
Outline

• Motivation
• Policy Representation using DAG
• Policy Reconciliation
• Implementation

9
Security Policy Reconciliation

• How to represent security policies
• Need to capture dependencies within each policy
• Need to capture policy preferences
• How to reconcile security policies
• Need to resolve policy preferences
• Need to be efficient

10
Existing Approaches

• How to represent security policies
• Flat
• Do not address preferences
• e.g. IPsec policy
• Proposal 1 AH
• Transform 1 HMAC-SHA
• Transform 2 HMAC-MD5
• Proposal 2 ESP
• Transform 1 3DES with HMAC-SHA
• Transform 2 3DES with HMAC-MD5
• Proposal 2 PCP
• Transform 1 LZS
• Transform 2 Deflate

Proposal 1 may use one of the 2 listed transforms
This policy offers 2 proposals
Proposal 2 MUST use both ESP and PCP and there
are two transforms each for ESP and PCP.
11
Existing Approaches (cont.)

• How to reconcile security policies
• Policies with preferences have not been well
  addressed
• Dependencies within policies are not expressed
  explicitly
• Generally a NP-complete problem
• Gong and Qian, 1994
• McDaniel and Prakash, 2002

12
Our Contributions

• How to represent security policies
• Use directed acyclic graph (DAG) to represent
  policies
• Concise
• Capture dependencies among policy components
• Allow efficient reconciliation
• Handle policies with preferences

13
Our Contributions

• How to reconcile security policies
• DAG model simplifies the problem
• Policy is reconciled only once per session
• Reconcile policies with preferences
• Polynomial time reconciliation
• Supports multi-party reconciliation
• Current implementation supports two-party
  reconciliation

14
Policy Representation

• Graph model
• Use Directed Acyclic Graph (DAG) S (N, E)
  called schema
• Nset of nodes
• Each node is either an AND ( ) or an OR ( )
  node
• AND node collection
• OR node decision
• Eset of edges
• A policy P (S, C) is a sub-schema derived from
  S, where C is the condition function
• A policy instance is derived from P

15
Policy Schema

• Authentication
• Kerberos
• PKI (X.509)
• Password
• Encryption
• AES-CBC
• 3DES-CBC
• Blowfish-CBC
• Integrity
• HMAC-MD5
• HMAC-SHA1

root
Integrity
Authentication
Encryption
HMAC
Kerberos
PKI
Password
AES
3DES
Blowfish
MD5
SHA1
CBC
16
Policy Schema Policies

• The policy schema defines the blue print
• Each site has its own security policy based on
  the schema, i.e. sub-schema
• Similar to database schema

root
root
Authentication
Integrity
Encryption
Authentication
Integrity
Encryption
HMAC
HMAC
Kerberos
PKI
Password
AES
3DES
Blowfish
Kerberos
PKI
AES
3DES
Schema
Policy sub-schema
MD5
CBC
SHA1
MD5
SHA1
CBC
17
Policy Schema Policies
root
root
Authentication
Integrity
Encryption
Authentication
Integrity
Encryption
HMAC
HMAC
Kerberos
PKI
Password
AES
3DES
Blowfish
Kerberos
PKI
AES
3DES
Schema
Policy sub-schema
MD5
CBC
SHA1
MD5
SHA1
CBC
root
root
Authentication
Authentication
Integrity
Encryption
Integrity
Encryption
HMAC
HMAC
Kerberos
AES
PKI
3DES
Policy instance 1
Policy instance 2
MD5
CBC
MD5
CBC
18
Policies May Have Preferences

• Each user/host/site has its own preferences
• Either due to design or requirements
• E.g. A may consider Kerberos to be the preferred
  authentication algorithm over PKI while B
  prefers PKI
• A policy P with preference (S, C, Pref)
• Pref(n) partial order function for each node

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Policy With Preferences

• Authentication
• 1. Kerberos
• 2. PKI (X.509)
• 3. Password
• Encryption
• 1. AES-CBC
• 2. 3DES-CBC
• 3. Blowfish-CBC
• Integrity
• 1. HMAC-MD5
• 2. HMAC-SHA1

root
Integrity
Authentication
Encryption
1
1
1
2
2
3
3
HMAC
Kerberos
PKI
Password
AES
3DES
Blowfish
1
2
1
1
1
MD5
SHA1
CBC
20
Policy With Preferences

• Use partial ordering to express preferences

• Policy 1
• Authentication
• Kerberos or PKI
• Password

• Policy 2
• Authentication
• Kerberos
• PKI
• Password

21
Outline

• Motivation
• Policy Representation using DAG
• Policy Reconciliation
• Implementation

22
Policy Reconciliation

• Assumptions
• A common policy schema shared by participants
• Custom policy schemas for different participants
• Goals
• A common policy schema for the participants
• Reconciled once per session
• Must handle preferences

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Policy Construction
root
Authentication
Integrity
Encryption
HMAC
Kerberos
PKI
Password
AES
3DES
Blowfish
Schema
MD5
CBC
SHA1
root
root
Authentication
Integrity
Encryption
Integrity
Authentication
Encryption
HMAC
HMAC
Kerberos
PKI
Password
AES
3DES
Blowfish
Kerberos
PKI
Password
AES
Blowfish
Sub-schema A
Sub-schema B
CBC
MD5
CBC
SHA1
SHA1
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Reconciling Preferences
root
root
Authentication
Integrity
Encryption
Integrity
Authentication
Encryption
1
1
2
1
2
1
2
3
1
2
3
HMAC
HMAC
Kerberos
PKI
Password
AES
3DES
Blowfish
Kerberos
PKI
Password
AES
Blowfish
1
1
2
Sub-schema A
Sub-schema B
CBC
MD5
CBC
SHA1
SHA1
25
Policy Reconciliation With Preferences
root
root
root
Authentication
Authentication
Authentication
1
1
2
1
2
3
1
2
3
Password
Kerberos
PKI
Kerberos
Password
PKI
Kerberos
PKI
Password
Sub-schema A
Sub-schema B
Reconciled Policy Schema
Preference A
Preference B
Reconciled Preference
Preference A
26
Policy Reconciliation
root
root
Authentication
Integrity
Encryption
Integrity
Authentication
Encryption
1
1
2
1
2
1
2
3
1
2
3
HMAC
HMAC
Kerberos
PKI
Password
AES
3DES
Blowfish
Kerberos
PKI
Password
AES
Blowfish
1
1
2
Sub-schema A
Sub-schema B
CBC
MD5
CBC
SHA1
SHA1
root
Authentication
Integrity
Encryption
1
2
3
1
2
HMAC
Kerberos
PKI
Password
AES
Blowfish
1
Reconciled Policy
SHA1
CBC
27
Policy Instantiation
root
Authentication
Integrity
Encryption
AES-CBC
1
1
2
1
2
HMAC
Kerberos
PKI
Password
AES
Blowfish
Blowfish-CBC
1
Reconciled Policy
SHA1
CBC
Most preferred Instance
root
root
Authentication
Authentication
Encryption
Encryption
Integrity
Integrity
Kerberos
AES
HMAC
Kerberos
Blowfish
HMAC
Policy Instance 1
Policy Instance 2
SHA1
CBC
SHA1
CBC
28
Policy ReconciliationSummary
Schema
Policy sub-schema
Policy sub-schema
Policy sub-schema
Policy Reconciliation Engine
Reconciled Policy Schema
Policy Instance
Policy Instance
Policy Instance
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Implementation

• Policy Reconciliation Engine (PRE)
• See http//www.cs.wisc.edu/hbwang/PRE/tr1499.pdf
  for details
• Code available at http//www.cs.wisc.edu/hbwang/P
  RE
• Integrated with Condor, a high-throughput,
  distributed system
• http//www.cs.wisc.edu/condor

30
Conclusion

• We demonstrated a graph-based algorithm for
  policy reconciliation
• Exposes the structure of policies
• Is concise and efficient
• Handles policies with preferences
• Models dependencies within each policy