PointBased Trust: Define How Much Privacy is Worth

1
Point-Based Trust Define How Much Privacy is
Worth

• Danfeng Yao Keith B. Frikken
• Brown University Miami University
• Mikhail J. Atallah Roberto Tamassia
• Purdue University Brown University

Funded by NSF IIS-0325345, IIS-0219560,
IIS-0312357, and IIS-0242421, ONR
N00014-02-1-0364, CERIAS, and Purdue Discovery
Park
ICICS December, 2006, Raleigh NC
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Outline of the talk
1. Introduction to privacy protection in
authorization
3. Secure 2-party protocol for knapsack problem
2. Point-based authorization and optimal
credential selection
2.1 New York State Division of Motor Vehicle
6-Point Authentication System
4. Applications
2.2 Knapsack problem
3
Protecting private information
Alice

• Trust negotiation protocols Winsborough Seamons
  Jones 00, Yu Ma Winslett 00, Winsborough Li 02,
  Li Du Boneh 03

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Our goals

• Prevent pre-mature information leaking by both
  parties
• Credentials should be exchanged only if services
  can be established
• Support some kind of cumulative privacy
  quantitatively
• Disclosing more credentials should incur higher
  privacy loss
• Support flexible service model
• Allow customized (or personalized) access
  policies
• Adjustable services based on qualifications

Our ultimate goal is to encourage users to
participate in e-commerce
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What can we learn from New York State DMV?
6-point proof-of-identity for getting NY drivers
license
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Another motivation adjustable services
Adjustable services based on the private
information revealed
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Point-based authorization model

• Credential type C1, C2, , Cn
• The service provider defines
• Point values p1, p2, , pn of credentials -----
  private
• Threshold T for accessing a resource -----
  private
• The user defines sensitivity scores a1, a2, , an
  of credentials ----- private
• Credential selection problem
• The user (or client) wants to satisfy threshold T
  with the minimum disclosure of privacy

This can be converted to a knapsack problem
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Example
Threshold of accessing a resource 10
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Where do points come from?

• Reputation systems Beth Borcherding Klein 94,
  Tran Hitchens Varadharajan Watters 05, Zouridaki
  Mark Hejmo Thomas 2005
• This is future work, but here is an idea

Evaluate
Evaluate
Evaluate
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Converting CSP into a knapsack problem

• Defines binary vector y1, y2, , yn, where yi
  1 xi
• ai Private to user
• pi Private to provider

n
Maximize ? ai yi Subject to ? pi yi lt T
i1
n
Let T ? pi - T
n
i1
i1
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Dynamic programming of knapsack problem

• Dynamic programming for 0/1 knapsack problem
• Construct a n-by-T table M, where

n
T ? pi - T
i1
M i, j M i-1, j if j lt pi
max M i-1, j, M i-1, j-pi ai if j
pi
ai Private to user pi Private to provider
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Overview of privacy-preserving knapsack
computation

• Uses 2-party maximization protocol Frikken
  Atallah 04
• Uses homomorphic encryption scheme
• E(x)E(y) E(x y)
• E(x)c E(xc)
• Preserves privacy for both
• Two phases table-filling and traceback

max , - 8 ai

• Add maximization and addition of ai to make the
  two computation procedures indistinguishable

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Preliminary 2-party maximization protocol in a
split format
Alices share Amazons share max (Alice1
Amazon1, Alice2 Amazon2)
Amazon1
Alice1
Amazon2
Alice2
Max
Alices share
Amazons share
Comparison can be done similarly Frikken Atallah
04
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Our protocol for dynamic programming of 0/1
knapsack problem
M i, j M i-1, j if j lt pi
max Mi-1, j , Mi-1, j-pi ai if
j pi
max , - 8 ai

• Computed entries are encrypted and stored by the
  provider
• The provider splits the two candidates of Mi, j
• The client and provider engage in a 2-party
  private maximization protocol to compute the
  maximum
• The client encrypts her share of the maximum and
  sends it to the provider
• The provider computes and stores the encrypted
  Mi, j

ai
E(Mi-1, j)
Alice
Amazon
Max
Alice
Amazon
E(Mi-1, j-pi)
Alices share
Amazons share
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Our protocol for knapsack (Contd)

• At the end of the 2-party dynamic programming,
  the provider has a n-by-T table of encrypted
  entries
• Number of credentials n4

n
T ? pi - T
i1
How does the client find out the optimal
selection of credentials?
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Traceback protocol get the optimal credential
selection
Item 0 Item 1 Item 2 Item 3 Item 4
0
E(Fi, j)
Fi, j 0 or 1

• Security in a semi-honest (honest-but-curious)
  model

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Security and efficiency of our privacy-preserving
knapsack computation

• Informally, security means that private
  information is not leaked
• Security definitions
• Semi-honest adversarial model
• A protocol securely implements function f if the
  view of participants are simulatable with an
  ideal implementation of the protocol
• Theorem The basic protocol of the private
  two-party dynamic programming computation in the
  point-based trust management model is secure in
  the semi-honest adversarial model.
• Theorem The communication complexity between the
  provider and the client of our basic secure
  dynamic programming protocol is O(nT'), where n
  is the total number of credentials and T' is the
  marginal threshold.

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Fingerprint protocol an improved traceback
protocol

• We want to exclude the provider in the traceback
• To prevent tampering and reduce costs

1. Filling knapsack table
2. (Encrypted) last entry
3. Decrypt and identity optimal credential
selection
Fingerprint protocol is a general solution for
traceback in DP
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Fingerprint protocol (contd)
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Application of point-based authorization fuzzy
location query in Presence systems
Ex
Where is Alice?
Boss
Mom
Alices mom
Where is Alice?
Alices boss
Where is Alice?
Alices ex
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Related work

• Hidden credentials Bradshaw Holt Seamons 04,
  Frikken Li Atallah 06
• Private policy negotiation Kursawe Neven Tuyls
  06, Optimizing trust negotiation Chen Clarke
  Kurose Towsley 05, Trust negotiation
  protocol/framework Winsborough Seamons Jones 00,
  Yu Ma Winslett 00, Winsborough Li 02, Li Du Boneh
  03, Li Li Winsborough 05
• Anonymous credential approaches Chaum 85,
  Camenisch Lysyanskaya 01
• Secure Multiparty Computation Atallah Li 04,
  Atallah Du 01
• OCBE Li Li 06
• Manet Zouridaki Mark Hejmo Thomas 05
• Platform for Privacy Preferences (P3P) W3C

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Conclusions and future work

• Our point-based model allows a client to choose
  the optimal selection of credentials
• We presented private 2-party protocol for
  knapsack problem
• Our fingerprint protocol is a general solution
  for traceback
• Future work
• Add typing to credentials
• Reputation systems and points