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Network Coding and Information Security Raymond W. Yeung The Chinese University of Hong Kong Joint work with Ning Cai, Xidian University

Network Coding and Information Security

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Network Coding and Information Security. Raymond W. Yeung The Chinese University of Hong Kong Joint work with Ning Cai , Xidian University. Outline. Introduction to Network Coding The Max-flow Bound Secure Network Coding Concluding Remarks. Introduction to Network Coding. - PowerPoint PPT Presentation

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Page 1: Network Coding  and Information Security

Network Coding and Information Security

Raymond W. YeungThe Chinese University of Hong Kong

Joint work with Ning Cai, Xidian University

Page 2: Network Coding  and Information Security

Outline

• Introduction to Network Coding• The Max-flow Bound• Secure Network Coding• Concluding Remarks

Page 3: Network Coding  and Information Security

Introduction toNetwork Coding

Page 4: Network Coding  and Information Security

A Network Coding Example

The Butterfly Network

Page 5: Network Coding  and Information Security

b1 b2

b1

b1b1

b2

b2

b2

b2

b1

b1 b2

b1

b1

b2

b2b1+b2

b1+b2b1+b2

Page 6: Network Coding  and Information Security

A Network Coding Example

with Two Sources

Page 7: Network Coding  and Information Security

b1b2

b1 b2

b1 b2 b2b1

b1 b2

b2b1

b1+b2

b1+b2

b1+b2

Page 8: Network Coding  and Information Security

Wireless/Satellite Applicationb1 b2

t = 1b1

t = 2

t = 3b1+b2

b2

b1+b2

50% saving for downlink bandwidth!

Page 9: Network Coding  and Information Security

Two Themes of Network Coding• When there is 1 source to be multicast in a

network, store-and-forward may fail to optimize bandwidth.

• When there are 2 or more independent sources to be transmitted in a network (even for unicast), store-and-forward may fail to optimize bandwidth.

In short, Information is NOT a commodity!

Page 10: Network Coding  and Information Security

Model of a Point-to-Point Network

• A network is represented by a directed graph G = (V,E) with node set V and edge (channel) set E.

• A symbol from an alphabet F can be transmitted on each channel.

• There can be multiple edges between a pair of nodes.

Page 11: Network Coding  and Information Security

Single-Source Network Coding• The source node S generates an information

vector x = (x1 x2 … xk) Fk.

• What is the condition for a node T to be able to receive the information vector x?

• Max-Flow Bound. If maxflow(T) < k, then T cannot possibly receive x.

Page 12: Network Coding  and Information Security

The Basic Results• If network coding is allowed, a node T can

receive the information vector x iff maxflow(T) ≥k

i.e., the max-flow bound can be achieved simultaneously by all such nodes T. (ACLY00)

• Moreover, this can be achieved by linear network coding for a sufficiently large base field. (LYC03, KM03)

Page 13: Network Coding  and Information Security

Secure Network Coding

Cai and Y, 2002(discussed with Ueli Maurer, ISIT 2000)

Page 14: Network Coding  and Information Security

Problem Formulation• The underlying model is the same as network multicast

using network coding except that some sets of channels can be wiretapped.

• Let A be a collection of subsets of the edge set E.• A subset in A is called a wiretap set.• Each wiretap set may be fully accessed by a wiretapper.• No wiretapper can access more than one wiretap set.• The network code needs to be designed in a way such

that no matter which wiretap set the wiretapper has access to, the multicast message is information-theoretically secure.

Page 15: Network Coding  and Information Security

Our Coding Scheme

• The multicast message is (s,w), where• s is the secure message• w is the randomness

• Both s and w are generated at the source node.

Page 16: Network Coding  and Information Security

A Example of a Secure Network Code

Page 17: Network Coding  and Information Security

s-w s+w

s-w

s-w

s+w

s+ww

wwOne of the 3 One of the 3 red channelsred channels can can be wiretappedbe wiretappeds is the secure messages is the secure messagew is the randomnessw is the randomness

Page 18: Network Coding  and Information Security

Another Example of Secure Network Coding

The (1,2)-threshold Secret Sharing Scheme

Page 19: Network Coding  and Information Security

ww s+ws+w s-ws-w

One of the 3 One of the 3 red channelsred channels can can be wiretappedbe wiretappeds is the secure messages is the secure messagew is the randomnessw is the randomness

Page 20: Network Coding  and Information Security

Construction of Secure Network Codes

• Let n = minT maxflow(T).• We have obtained a sufficient condition under which a

secure linear network code can be constructed. • In particular, if A consists of all the r-subsets of E, where r <

n, then we can construct a secure network code with multicast message (s,w) such that |s|=n-r and |w|=r.

• For this case, the condition is also necessary.• Interpretation: For a sink node T, if r channels in the network

are wiretapped, the number of “secure paths” from the source node to T is still at least n-r. So n-r symbols can go through securely.

Page 21: Network Coding  and Information Security

Global Encoding Kernels of a Linear Network Code

• Recall that x = (x1 x2 … xk) is the multicast message.

• For each channel e, assign a column vector fe such that the symbol sent on channel e is x fe. The vector fe is called the global encoding kernel of channel e.

• The global encoding kernel of a channel is analogous to a column in the generator matrix of a classical block code.

• The global encoding kernel of an output channel at a node must be a linear combination of the global encoding kernels of the input channels.

Page 22: Network Coding  and Information Security

An Example

k = 2, let x = (b1, b2)

Page 23: Network Coding  and Information Security

b1 b2

b1

b1

b2

b2b1+b2

b1+b2b1+b2

10

10

01

11

11

11

10

01

01

Page 24: Network Coding  and Information Security

Idea of Code Construction• Start with a linear network code for multicasting n

symbols.• For all wiretap set A A, let fA = { fe : e A }, the set of

global encoding kernels of the channels in A.• Let dim(span(fA)) r for all A A. [sufficient condition]

• When the base field F is sufficiently large, we can find b1, b2, …, bn-r Fn such that

b1, b2, …, bn-r are linearly independent of fA

for all A A.

Page 25: Network Coding  and Information Security

• Let the multicast message be (s,w), with |s| = n-r and |w| = r.

• Take a suitable linear transformation of the given linear network code to obtain the desired secure network code.

Page 26: Network Coding  and Information Security

Recent Work (Cai and Y, ISIT 2007)

• We obtained a necessary and sufficient condition for the security of linear network codes.

• This condition applies in the cases when • There are more than one information source

nodes in the network.• The random keys are not uniformly distributed.

• This condition also shows that the security of a linear network code does not depend on the source distribution.

Page 27: Network Coding  and Information Security

Resources

• Network Coding Homepagehttp://www.networkcoding.info

• R. W. Yeung, S.-Y. R. Li, N. Cai and Z. Zhang, Network Coding Theory, now Publishers, 2005 (Foundation and Trends in Communications and Information Theory).

• N. Cai and R. W. Yeung, “Secure network coding,” preprint.

Page 28: Network Coding  and Information Security

Concluding Remarks

• Secure network coding is a generalization of both (regular) network coding and secret sharing.

• The subject is still in its infancy, and a lot of basic questions are yet to be answered.