Secure Information Exchange for
Omniscience
Chung Chan (CityU)
Joint work with Navin Kashyap (IISc), Praneeth Kumar Vippathalla, (IISc) and Qiaoqiao Zhou (CUHK)

Audio slides: https://www.cs.cityu.edu.hk/~ccha23/isit2020
Secure information exchange
Formulation
Public
info.
Private
info.
Network
Nodes
Target
info.
Censored
info.
Interactive Public discussion
Characterize \(\mathcal{R}:=\operatorname{closure}\{\text{$(u_V,\ell_V,r_V)$ achievable by some $\mathsf{F}$}\}\) given source \(P_{\mathsf{X}_V,\mathsf{Y}_V,\mathsf{Z}_V}\).
Related problems
- Private information extraction problem [Asoodeh et al 19]
- \( V =\{1,2\}\)
- \( \mathsf{Z}_1 = (\mathsf{X}_2, \mathsf{Y}_2)\) and \(\mathsf{X}_1\), \(\mathsf{Y}_1\), \(\mathsf{Z}_2\) are null
- Information bottleneck [Tishby et al 99]
- \( V =\{1,2\}\)
- \(\mathsf{X}_1\), \(\mathsf{Y}_1\), \(\mathsf{X}_2\) and \(\mathsf{Z}_2\) are null
By restricting the source model, the problem reduces to:
Secure omniscience
A special scenario of secure information exchange
Characterize \(R_{\text{L}}:=\inf\{ \ell_{\text{w}}|(u_V,\ell_V,r_V)\in \mathcal{R},u_i=H(\mathsf{Z}_V|\mathsf{Z}_i)\,\forall i\in A\}\).
Example
With uniformly random and independent bits: \(\mathsf{X}_a,\mathsf{X}_b, \mathsf{X}_c\),
\(R_L = 0\)
Communication for Omniscience
[Csiszar and Narayan 04]
Characterize \(R_{\text{CO}}:=\inf\{ \sum_{i\in U} r_i|(u_V,\ell_V,r_V)\in \mathcal{R},u_i=H(\mathsf{Z}_V|\mathsf{Z}_i)\,\forall i\in A\}\).
Minimum leakage vs minimum discussion rate
From [Csiszar and Narayan 04],
$$R_{\text{CO}} = \min \left\{\left.\sum\nolimits_{i=1}^3 r_i\right| r_1+r_2 \geq 0, r_1+r_3 \geq 1, r_2+r_3 \geq 1\right\}$$
Claim: Any scheme with \((r_1,r_2,r_3)=(0,0,1)\) cannot have \(R_{\text{L}} = 0\)
Proposition \(R_{\text{L}}\) and \(R_{\text{CO}}\) are not simultaneously achievable in general.
\(\mathsf{F}=\mathsf{F}_3=\mathsf{Z}_3^n\)
\(R_{\text{CO}}\)-achieving scheme:
\(\ell_{\text{w}} =H(\mathsf{Z}_3|\mathsf{Z}_{\text{w}})=1\geq 0=R_{\text{L}}\)
Proposition \(R_{\text{L}}=R_{\text{CO}}\) if \(\mathsf{Z}_{\text{w}}\) is null.
\(=1\) solved uniquely by \((r_1,r_2,r_3)=(0,0,1)\)
Main Results
Lower bound on minimum leakage
Theorem 1 For the secure omniscience scenario with \(|A| \geq 2\),
$$\begin{aligned} R_{\text{L}} &\geq H(\mathsf{Z}_U|\mathsf{Z}_{\text{w}}) - C_{\text{S}}\\ &\geq R_{\text{CO}}(\mathsf{Z}_U|\mathsf{W}) - I(\mathsf{Z}_U \wedge \mathsf{Z}_{\text{w}} | \mathsf{W}) \end{aligned}$$
for any random variable \(\mathsf{W}\) satisfying the Markov condition \(I(\mathsf{W}\wedge \mathsf{Z}_U | \mathsf{Z}_{\text{w}})=0\).
$$\limsup_{n\to \infty} \frac1n I(\mathsf{K}\wedge \mathsf{F},\mathsf{Z}_{\text{w}}^n)=0\kern8em\text{(secrecy)}$$
$$\limsup_{n\to \infty}\frac1n H(\mathsf{K}|\mathsf{Z}_i^n,\mathsf{F})=0 \quad \forall i\in A \qquad\text{(recoverability)}$$
Definition (Multiterminal secret key agreement [Csiszar and Narayan 04])
Proof Idea
For the first lower bound, similar to an argument in [Csiszar and Narayan 04], $$C_{\text{S}}\geq H(\mathsf{Z}_U|\mathsf{Z}_{\text{w}})-R_{\text{L}}$$ by privacy amplication after secure omniscience.
The second lower bound follows from $$C_{\text{S}}\leq H(\mathsf{Z}_U|\mathsf{W}) - R_{\text{CO}}(\mathsf{Z}_U|\mathsf{W}),$$ an upper bound on \(C_{\text{S}}\) in [Csiszar and Narayan 04].
Theorem 1 For the secure omniscience scenario with \(|A| \geq 2\),
$$\begin{aligned} R_L &\geq H(\mathsf{Z}_U|\mathsf{Z}_{\text{w}}) - C_{\text{S}}\\ &\geq R_{\text{CO}}(\mathsf{Z}_U|\mathsf{W}) - I(\mathsf{Z}_U \wedge \mathsf{Z}_{\text{w}} | \mathsf{W}) \end{aligned}$$
for any random variable \(\mathsf{W}\) satisfying the Markov condition \(I(\mathsf{W}\wedge \mathsf{Z}_U | \mathsf{Z}_{\text{w}})=0\).
Example
Is the lower bound achievable?
\(\because\) user 1 is active
by Theorem 1
Theorem 1 For the secure omniscience scenario with \(|A| \geq 2\),
$$\begin{aligned} R_L &\geq H(\mathsf{Z}_U|\mathsf{Z}_{\text{w}}) - C_{\text{S}}\\ &\geq R_{\text{CO}}(\mathsf{Z}_U|\mathsf{W}) - I(\mathsf{Z}_U \wedge \mathsf{Z}_{\text{w}} | \mathsf{W}) \end{aligned}$$
for any random variable \(\mathsf{W}\) satisfying the Markov condition \(I(\mathsf{W}\wedge \mathsf{Z}_U | \mathsf{Z}_{\text{w}})=0\).
Main Results
Upper bound on minimum leakage
Theorem 2 For the secure omniscience scenario,
$$R_{\text{L}} \leq \frac{1}{m} [ R_{\text{CO}}(\mathsf{Z}_U^m|\mathsf{F}') + I(\mathsf{Z}_U^m \wedge \mathsf{F}' | \mathsf{Z}_{\text{w}}^m) ] \leq R_{\text{CO}}$$
where \(\mathsf{F}'\) is a public discussion for block length \(m\geq 1\).
Proof idea
Theorem 2 For the secure omniscience scenario,
$$R_{\text{L}} \leq \frac{1}{m} [ R_{\text{CO}}(\mathsf{Z}_U^m|\mathsf{F}') + I(\mathsf{Z}_U^m \wedge \mathsf{F}' | \mathsf{Z}_{\text{w}}^m) ] \leq R_{\text{CO}}$$
where \(\mathsf{F}'\) is a public discussion for block length \(m\geq 1\).
by setting \(m=1\) and \(\mathsf{F}'\) to null
concat.
\(\frac{n}{m}\) blocks
How to attain omniscience?
Omniscience possible with \(\sum_{i\in U} r''_i = R_{\text{CO}}(\mathsf{Z}_U^m|\mathsf{F}')\).
Example
Do the upper and lower bounds match in general?
by Theorem 1
N.b., \(F'\) already achieves omniscience, so \(R_{\text{CO}}(\mathsf{Z}_U^m|\mathsf{F}')=0\).
by Theorem 2
\(m=1\) does not work but \(m=2\) works.
Try
Theorem 2 For the secure omniscience scenario,
$$R_{\text{L}} \leq \frac{1}{m} [ R_{\text{CO}}(\mathsf{Z}_U^m|\mathsf{F}') + I(\mathsf{Z}_U^m \wedge \mathsf{F}' | \mathsf{Z}_{\text{w}}^m) ] \leq R_{\text{CO}}$$
where \(\mathsf{F}'\) is a public discussion for block length \(m\geq 1\).
Main Results
Tightness of the upper and lower bounds
Theorem 3 For any finite linear source with two users, i.e., \(A=U=\{1,2\}\),
$$R_{\text{L}} = H(\mathsf{Z}_1,\mathsf{Z}_2|\mathsf{Z}_{\text{w}}) - I(\mathsf{Z}_1\wedge \mathsf{Z}_2|\mathsf{G})$$
where \(\mathsf{G}\) is the maximum common function of \(\mathsf{Z}_{\text{w}}\) and \(\mathsf{Z}_1\), i.e., the unique solution to $$J_{\text{GK}}(\mathsf{Z}_{\text{w}} \wedge \mathsf{Z}_1) :=\max\limits_{\mathsf{G}: H(\mathsf{G}|\mathsf{Z}_{\text{w}})=H(\mathsf{G}|\mathsf{Z}_1)=0} H(\mathsf{G}). $$
Theorem 1 With \(|A| \geq 2\),
$$R_L \geq H(\mathsf{Z}_U|\mathsf{Z}_{\text{w}}) - C_{\text{S}} $$
for any \(\mathsf{W}\) with \(I(\mathsf{W}\wedge \mathsf{Z}_U | \mathsf{Z}_{\text{w}})=0\).
Proof of \(\geq\)
- Choose \(\mathsf{W}=\mathsf{G}\), and
- substitute \(C_{\text{S}}=I(\mathsf{Z}_1\wedge \mathsf{Z}_2|\mathsf{G})\).
Proof of \(\leq\)
- Choose \(m=1\), and
- \(\mathsf{F}'\) to align with \(\mathsf{Z}_{\text{w}}\).
Theorem 2
$$R_{\text{L}} \leq \frac{1}{m} [ R_{\text{CO}}(\mathsf{Z}_U^m|\mathsf{F}') + I(\mathsf{Z}_U^m \wedge \mathsf{F}' | \mathsf{Z}_{\text{w}}^m) ]$$
with discussion \(\mathsf{F}'\) for block length \(m\geq 1\).
Bounds do not match in general
Claim Minimum leakage is \(R_L \geq 1.\)
\(\mathsf{F} =\mathsf{F}_3=\mathsf{X}_b^n\)
\(\ell_{\text{w}} =1\)
Optimal scheme:
\(R_{\text{L}} \geq H(\mathsf{Z}_U|\mathsf{Z}_{\text{w}}) - C_{\text{S}} = 1-1=0\)
\(C_{\text{S}}\leq H(\mathsf{Z}_1) =1\)
Proposition The lower bound on \(R_{\text{L}}\) is loose.
Theorem 1 With \(|A| \geq 2\),
$$R_L \geq H(\mathsf{Z}_U|\mathsf{Z}_{\text{w}}) - C_{\text{S}} $$
for any \(\mathsf{W}\) with \(I(\mathsf{W}\wedge \mathsf{Z}_U | \mathsf{Z}_{\text{w}})=0\).
Extensions and challenges
- Tightness for hypergraphical sources can be proved.
- More explicit characterization \(R_{\text{L}}\) using graph entropy is possible.
- Lower bound can be improved for the counter-example.
- \(R_{\text{L}}\) remains unknown for finite linear sources.
- \(R_{\text{L}}\) for secure linear function computation, extending [Tyagi et. al 11].
References
I. Csiszár and P. Narayan, “Secrecy capacities for multiple terminals,” IEEE Transactions on Information Theory, vol. 50, no. 12, pp. 3047–3061, Dec. 2004.
A. Gohari and V. Anantharam, “Information-theoretic key agreement of multiple terminals—Part I,” IEEE Transactions on Information Theory, vol. 56, no. 8, pp. 3973 –3996, Aug. 2010.
S. Asoodeh, M. Diaz, F. Alajaji, and T. Linder, “Estimation efficiency under privacy constraints,” IEEE Transactions on Information Theory, vol. 65, no. 3, pp. 1512–1534, March 2019.
N. Tishby, F. C. Pereira, and W. Bialek, “The information bottleneck method,” in Thirty-Seventh Annual Allerton Conference on Communication, Control, and Computing, Sep. 1999.
H. Tyagi, P. Narayan, and P. Gupta, “When is a function securely computable?” IEEE Transactions on Information Theory, vol. 57, no. 10, pp. 6337–6350, 2011.
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By Chung Chan
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