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Secure Supply Chain Collaboration

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Smaller entities could collaborate to do the same. Share capacity and workload information ... Collaboration beneficial. But information disclosure has costs ... – PowerPoint PPT presentation

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Title: Secure Supply Chain Collaboration


1
Secure Supply Chain Collaboration
  • Chris Clifton

2
Supply Chain Information Security
  • Making the supply chain work requires information
  • Need to keep the information secure
  • What does this mean?
  • Nobody sees anything they shouldnt
  • What you see is correct
  • You get what you need in time

3
Example Order Planning
  • Goal Reduce inefficiency by reducing inventory,
    out of stock
  • Inventory costs (interest, storage) significant
  • Information sharing can solve the problem
  • Walmart demands everyones information
  • Result improved efficiency ? lower prices
  • Who wins?
  • We need fair knowledge sharing

4
Tradeoff Vertical Integration
  • Vertical integration solves the information
    sharing problem
  • All participants have the same bottom line
  • Common authority/purpose
  • But comes at a cost
  • Loss of flexibility
  • Lost opportunities for economies of scale
  • Can we get both?

5
Goal Share Capacitywithout sharing information
  • Large Corporations achieve economies of scale
  • Lots of capacity
  • Lots of work
  • Enables smoothing out the rough spots
  • Smaller entities could collaborate to do the same
  • Share capacity and workload information
  • But knowledge is power (competitive advantage)
  • We face a tradeoffrevealing secrets vs.
    enhanced efficiency
  • Or do we?

6
Confidential Computation
  • Idea Many parties have components of the input
    to a function
  • Want to get the function result
  • But not reveal your input component
  • Preserves confidentiality of the data
  • Unless disclosure inherent in the result
  • Example Secure Sum

7
Gold StandardTrusted Third Party
8
Secure Multiparty Computation
  • Collaboration beneficial
  • But information disclosure has costs
  • Goal Collaboration without Disclosure
  • Trusted third-party model

9
Secure Multiparty ComputationIt can be done!
  • Goal Compute function when each party has some
    of the inputs
  • Yaos Millionaires problem (Yao 86)
  • Secure computation possible if function can be
    represented as a circuit
  • Idea Securely compute gate
  • Continue to evaluate circuit
  • Works for multiple parties as well (Goldreich,
    Micali, and Wigderson 87)

10
Others you should talk to
  • Mike Atallah (ComputerScience /CERIAS)
  • Ananth Iyer (Krannert)
  • VinayakDeshpande(Krannert)
  • Lee Schwarz (Krannert)

11
Routes of Great Eastern
Routes of Western Trucking
Chicago
South Bend
Western Trucking
Gary
Great Eastern
Ft. Wayne
12
Example Transportation
  • Two trucking companies wish to share deliveries
  • Swap deliveries so each gets a shorter route
  • But dont want to reveal customers
  • What is the minimum that must be disclosed?
  • Swapped customers!
  • Can we do this without revealing more?

13
Traveling Salespeople
14
After swapping customers
New route of A
New route of B
Original customers of A
Original customers of B
New customers of A (swapped from B)
New customers of B (swapped from A)
15
Space Filling Curve Approach
  • For each customer, via a space filling curve,
    calculate a corresponding position on an
    interval.
  • Securely find the median on the interval.
  • Salesman A doesnt know how may customers
    salesman B has and vice versa.
  • They only know the customers swapped and
    additional information induced from the traded
    customers.
  • Swap customers so that all customers of A are on
    one side of the median and all customers of B on
    the other side of the median.
  • Find a route for each salesman via the same space
    filling curve.

16
Space-Filling Curve
Median
17
For each customer of salesman A, calculate a
corresponding position on an interval.
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For each customer of salesman B, calculate a
corresponding position on an interval
19
lbound 0, ubound
i 1
lbound 1, ubound
i 2
lbound 2, ubound
i 4
lbound 2, ubound 4
i 3
lbound 3, ubound 4
i 3
1
11
13
15
3
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lbound 0, ubound
i 1
lbound 1, ubound
i 2
lbound 2, ubound
i 4
lbound 2, ubound 4
i 3
lbound 3, ubound 4
i 3
1
5
7
9
11
13
15
3
21
i 1
i 2
i 4
Lbound 2, ubound 4
i 3
Lbound 3, ubound 4
22
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23
Algorithm One Dimensional Secure Relative
Outlier Detection
24
Oblivious Transfer
  • What is it?
  • A has inputs ai
  • B makes choice
  • A doesnt know choice, B only sees chosen value.
  • How?
  • A sends public key p to B
  • B selects k random values b
  • encrypts (only) bchoice with fp, sends all to A
  • A decrypts all with private key, sends to B ci
    ai ? e(fp-1(bi))
  • B outputs cchoice ? e(bchoice) achoice ?
    e(fp-1(fp(bchoice))) ? e(bchoice)
  • Slightly more complicated if B might cheat
  • E.g., B encrypts all with fp,

25
Oblivious Transfer
  • ? generates and publishes three numbers
  • p a large prime number (all randoms in 1, ,
    p-1)
  • C a random number
  • g the generator of ps multiplicative group,
    i.e., every number between 1 and p-1 can be
    written as gk mod p for some k
  • ? picks random k sets Ps gk P1-s C/Ps
  • sends P0 to ?
  • ? sets P1 C/P0 chooses random r0, r1 sets
  • E0 (gr0, H((P0)r0) ? B0)
  • E1 (gr1, H((P1)r1) ? B1)
  • sends E0, E1 to ?
  • ? computes Bs H(Ps)rs) ? Es

26
Oblivious Transfer
  • What is it?
  • A has inputs ai
  • B makes choice
  • A doesnt know choice, B only sees chosen value.
  • How?
  • A sends public key p to B
  • B selects 4 random values b
  • encrypts (only) bchoice with fp, sends all to A
  • A decrypts all with private key, sends to B ci
    ai ? e(fp-1(bi))
  • B outputs cchoice ? e(bchoice) achoice ?
    e(fp-1(fp(bchoice))) ? e(bchoice)

27
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28
Is it Secure?
  • Oblivious transfer secure even in malicious
    model
  • Extends to comparison
  • Full protocol
  • Given final result, result of each comparison
    known
  • Is this enough?
  • No!
  • But neither is trusted third party / malicious
    model
  • Dishonest party falsifies input

29
SolutionIncentive Compatibility
  • Cheating party will be worse off than being
    honest
  • True if cheating results in
  • Longer travel for cheater
  • Getting caught
  • Protocol gives optimal answer

30
Incentive Compatible (cont.)
  • Protocol gives optimal answer
  • If cheating gives different comparison, cant
    arrive at optimal answer
  • If cheating gives same comparison, no knowledge
    gained
  • Protocol is incentive compatible!

31
Does it Work?Trials on Actual Logistics Data
32
Does it Work?Trials on Actual Logistics Data
33
Ideas
  • Reha Assymetry small suppliers, large
    customers
  • Needs to be easy to use for suppliers
  • Subcontractors
  • Need to ascertain process
  • Process improvements possible?
  • Vendor-managed inventory
  • Customer only gets combined information
  • Vendors dont see each others information
  • Avoid disclosing promotions at different levels
    of supply chain
  • Issue Repetitive work may reveal information
    will this only work for one-time issues?
  • Sales through third-party distributors likely
    market
  • Reluctance to share with distributors and
    vice-versa
  • How to get information to customer, and from
    customer?
  • Sharing distribution facilities / cross-docking
    without revealing customers

34
Secure Multiparty ComputationIt can be done!
  • Goal Compute function when each party has some
    of the inputs
  • Yaos Millionaires problem (Yao 86)
  • Secure computation possible if function can be
    represented as a circuit
  • Idea Securely compute gate
  • Continue to evaluate circuit
  • Works for multiple parties as well (Goldreich,
    Micali, and Wigderson 87)

35
How does it work?
b1
a1
b2
a2
Aa1a2
Bb1b2
  • Each side has input, knows circuit to compute
    function
  • Add random value to your input, give to other
    side
  • Each side has share of all inputs
  • Compute share of output
  • Add results at end
  • XOR gate just add locally
  • AND gate send your share encoded in truth table
  • Oblivious transfer allows other side to get only
    correct value out of truth table

Circuit
c1
c2
Cc1c2
36
Oblivious Transfer
  • What is it?
  • A has inputs ai
  • B makes choice
  • A doesnt know choice, B only sees chosen value.
  • How?
  • A sends public key p to B
  • B selects 4 random values b
  • encrypts (only) bchoice with fp, sends all to A
  • A decrypts all with private key, sends to B ci
    ai ? e(fp-1(bi))
  • B outputs cchoice ? e(bchoice) achoice ?
    e(fp-1(fp(bchoice))) ? e(bchoice)

37
Challenges
  • Extend secure multiparty computation to
    real-world problems
  • Need to identify the problems!
  • Business models to utilize the technology
  • What is fair sharing?
  • Moving this to industry
  • VICS (Voluntary Intraindustry Commerce Standards)
    Association
  • CCSI (Collaborative Commerce Standards Institute)

38
Related ideas
  • Rapid Product Realization
  • Customer-driven design
  • Must share details between supply chain
    components
  • Protect proprietary information
  • Secure Multiparty Computation allows both!
  • Talk to Prof. Ramani for more

39
How is this related to Infrastructure Protection?
  • Critical Infrastructure not monolithic
  • Telecommunications / power interrelated
  • Multiple ISPs
  • Protecting the infrastructure requires sharing
    information
  • Attack identification and isolation
  • Competitors reluctant to share
  • Need data analysis without data disclosure!

40
Next Steps
  • What are real-world applications?
  • Logistics
  • Manufacturing
  • ?
  • Who would be willing to try this out?
  • Are you using a broker today?
  • Do you give the broker all relevant information?
  • Is this safe?
  • Develop algorithms/tools and try them out

Want to participate? Contact me
(clifton_at_purdue.edu) orProf. Mike Atallah
(mja_at_cs.purdue.edu)
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