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Universally Composable MPC using Tamper-Proof HardwarePowerPoint Presentation

Universally Composable MPC using Tamper-Proof Hardware

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Universally Composable MPC using Tamper-Proof Hardware

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### Universally Composable MPC using Tamper-Proof Hardware

Jonathan Katz

Overview I

- Goal: construct protocols that are secure when run concurrently alongside arbitrary other protocols
- Specifically, within the UC framework [C01]

- Unfortunately…this is impossible in the “plain” network model[CF01]

Overview II

- One idea: introduce setup assumptions
- Previous suggestions seem to require some trusted parties (think: CRS)
- Is this inherent?

- This talk: physical assumptions as a possible alternative to trusted setup
- Specifically, the existence of tamper-proof hardware

Outline of the talk

- MPC, UC framework, impossibility results, existing setup assumptions, …
- Physical assumptions (e.g., tamper-proof hardware) as a new direction
- Potential advantages

- Quick intuition as to why tamper-proof hardware helps
- UC-MPC from tamper-proof hardware

Secure multi-party computation

- Parties P1, …, Pn holding x1, …, xn
- Want to compute f = (f1(x1, …, xn), …, fn(x1, …, xn)), while maintaining
- Privacy
- Correctness
- Independence of inputs
- …

- Formalize using simulation paradigm

Settings

- Stand-alone setting
- Major results from mid-80s establish that secure computation of any function is possible [Y82,GMW87,RB89,…]

- Concurrent setting
- Situation is less clear…
- Focus of much recent research
- Let’s see the problem

transcript

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Zero knowledge, stand-alone(verifier)

Handling concurrent executions

- For ZK, security in a concurrent setting is possible [RK99,KP01,PRS02]
- What about other functions?
- How to manage the complexity of this setting, in general?

(Simplified) overview

- A key feature of the model is that the environment cannot be rewound
- A protocol proven secure in the UC framework remains secure under general concurrent composition
- Analyze a protocol in isolation; conclude that it is secure in a concurrent setting

Impossibility results

- In the “plain model” with no honest majority, UC-computation of any “interesting” function is impossible [CF01,CKL03]
- In some sense, this is an inherent limitation of concurrency
- I.e., not just an artifact of the UC framework [L03,L04]

“Setup assumptions”

- That is, augment the plain model
- E.g., a common reference/random string (CRS) available to all parties
- This idea has a long history [BFM88], and was the first setup assumption proposed in the UC setting [CF01]
- Most commonly-used setup assumption
- All feasibility results recovered [CLOS02]

How to generate a CRS?

- Rely on a trusted party to generate it?
- What if we are unwilling to assume any trusted parties?
- Anyone who generates the CRS can potentially “attack” any protocol.

- Use naturally-occurring random sources?
- Unclear… (need correct distribution, synchronization, “privacy”[CDPW07])

Other setup assumptions?

- Public-key registration services [BCNP04,CDPW07]:
- Very strong requirements
- E.g., must check all parties’ secret keys to make sure keys are well-formed

- Again, requires a high degree of trust

Other setup assumptions?

- “Signature cards” [HM-QU05]:
- Government issued cards carrying out a specific functionality

- Again, requires trust

An alternative?

- Existing setup assumptions all appear to require some set of trusted parties
- Perhaps physical assumptions can be used to circumvent existing impossibility results?
- This might potentially lead to an approach that entirely avoids the need for trust!

Physical assumptions?!

- Not as crazy as it might (at first) sound:
- IT bounds on secret communication can be circumvented if noisy channels are assumed [Wyner75, CK78, Maurer93]
- Quantum key exchange [BB84]
- Broadcast with dishonest majority using physical multicast channels [FM00]
- Network timing [DNS98, KLP05]

This talk: tamper-proof hardware

- Assume the existence of tamper-proof hardware tokens
- Users can create tokens implementing any functionality
- No guarantee for tokens created by dishonest users

- Dishonest users can do no more than observe input/output of honest tokens

- Users can create tokens implementing any functionality
- Given the above, what can be done?

(Possible) advantages?

- Elimination of trust
- Users can produce their own tokens…

- Reduction or distribution of trust
- Each user can choose their own hardware vendor (not possible with other setup assumptions)

- Accountability/falsifiability
- Demonstrate hardware not tamper proof

Two (philosophical) caveats

- Is the assumption reasonable?
- Perhaps not today, perhaps someday…
- Weaker assumptions (tamper-evident hardware?) may suffice…

- Has the assumption been modeled appropriately?
- You tell me
- This is always a concern…

Inspiration from prior work

- Using tamper-proof hardware to obtain more efficient/more secure protocols is not new
- Inspired by the work on “observers” in the context of e-cash [CP, Brands, CP]

- This is the first time it has been suggested for concurrent security or general MPC

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Dependency

eliminated!

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Concurrent zero knowledge(verifier)

Problem: dependence of the different executions

Details…

- Functionality of token:
- Run ZK protocol; sign statement being proven plus a bit indicating acceptance

- Protocol (for prover):
- Obtain token; run ZK protocol with the token; upon completion, send the final output of the token to the verifier

Security analysis (informal)

- When the verifier is honest
- Soundness of ZK proof system + security of signature scheme imply soundness

- When the prover is honest
- Zero knowledge of each proof system (in stand-alone sense) means that the view of each token can be simulated
- Does not matter if the token runs incorrect protocol, or if there is a covert channel

Note on the proof…

- The token can be rewound
- (Intuition:) rewinding token ok since it is “isolated” from the network
- This will follow from the formal model

- Parties still cannot be rewound
- In particular, MPC not trivial to achieve
- (Think ZK proofs of knowledge…)

Modeling tamper-proof hardware(simplified)

- On input (create, P, P’, M) from P (where M is an interactive Turing machine) do:
- Send (create, P, P’) to P’
- Store (P, P’, M)

- On input (run, P, msg) from P’, do:
- As expected…
- Chose random coins for M and run an execution of M with incoming message msg
- (Maintain state)

Fwrap

Observation

- Implicit in Fwrap are the following assumptions:
- A party creating a token “knows” the code the token will run
- An token is completely tamper-proof, and has access to a source of randomness (this can be relaxed to some extent with a PRG)
- Token cannot communicate directly with external network

UC computation using Fwrap

- Using results of [CLOS02], it suffices to realize the (multiple) commitment functionality
- Notation: (g, h, G, H)
- Is a Diffie-Hellman tuple if loggG = loghH
- Is a random tuple otherwise

- Com(g,h,G,H)(b) = (gxhy, GxHygb)
- Perfectly hiding if (g,h,G,H) is a random tuple
- Extractable if it is a DH tuple and loggG is known

The protocol I

- S creates the following token:
- Receive (g, h)
- Choose random G1, H1 and commit to them using a perfectly-hiding scheme
- Receive (G2, H2); set G=G1G2 and H=H1H2
- Decommit to G1, H1 and set tSR=(g,h,G,H)
- Output a signature on tSR

- R creates a token symmetrically, and the parties exchange tokens

The protocol II

- S and R each interact with the token sent by the other party, and then exchange tSR/tRS and signatures
- At the end of this step, both parties hold tSR and tRS
- (or abort)

Proof intuition I

- Say P honest and P’ malicious
- What can we argue about tPP’?
- Since rewinding of P’ is not allowed, there is no way for a simulator to “force” the value of tPP’
- Nevertheless, with all but negligible probability tPP’ will be a random tuple

Proof intuition II

- (P honest and P’ malicious)
- What about tP’P?
- When P’ sends M to Fwrap, the simulator obtains it
- Although we cannot rewind P’, we can rewind the extracted M (i.e., the token)
- Can “force” tP’P to be a Diffie-Hellman tuple with known discrete logarithm
- (Indistinguishable from a random tuple)

The protocol III

- To commit to b, S does:
- Commit to b using standard commitment C
- Compute commitment Com to b using tSR
- Send both commitments to R and give witness indistinguishable proof that either
- Commitments are to same value
- Or, tRS is a Diffie-Hellman tuple

The protocol IV

- To decommit, S does:
- Send b
- Give witness indistinguishable proof that either
- Commitments C and Com were to b
- Or, tRS is a Diffie-Hellman tuple

- Crucial that Com is perfectly hiding
- (since impossible to “force” the value of tSR)

- Proof is now straightforward…
- Say S is honest
- tSR random tuple; tRS Diffie-Hellman tuple
- Simulation:
- Commit to garbage; give WI proof using tRS
- Send correct bit b; give WI proof using tRS

Proof intuition IV

- Say R is honest
- tRS random tuple; tSR Diffie-Hellman tuple
- S sends C and Com + WI proof
- Since tRS random tuple, this means that C and Com are commitments to the same value
- Extract from Com using known discrete logarithm of tSR

- In decommitment phase, WI proof can only be given successfully for the same bit

Conclusions and future directions

- UC multi-party computation is impossible without extending the “plain model”
- A natural goal is to find extensions that are both useful and realistic
- Here, we suggest physical assumptions and tamper resistance in particular

- Future work
- General assumptions, more efficient protocols
- Weaker models of tamper resistance
- Other setup assumptions? Characterization?