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Secrecy Capacity Scaling of Large- Scale Cognitive Networks Yitao Chen 1 , Jinbei Zhang 1 , Xinbing Wang 1 , Xiaohua Tian 1 , Weijie Wu 1 , Fan Fu 2 , Chee Wei Tan 3 1 Dept. of Electronic Engineering, Shanghai Jiao Tong University 2 Dept. of Computer Science and Engineering, Shanghai Jiao Tong University 3 Dept. of Computer Science, City University of Hong Kong

Secrecy Capacity Scaling of Large-Scale Cognitive Networks

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Secrecy Capacity Scaling of Large-Scale Cognitive Networks. Yitao Chen 1 , Jinbei Zhang 1 , Xinbing Wang 1 , Xiaohua Tian 1 , Weijie Wu 1 , Fan Fu 2 , Chee Wei Tan 3 1 Dept. of Electronic Engineering, Shanghai Jiao Tong University - PowerPoint PPT Presentation

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Page 1: Secrecy Capacity Scaling of Large-Scale Cognitive Networks

Secrecy Capacity Scaling of Large-Scale Cognitive Networks

Yitao Chen1, Jinbei Zhang1, Xinbing Wang1,

Xiaohua Tian1, Weijie Wu1, Fan Fu2, Chee Wei Tan3

1 Dept. of Electronic Engineering, Shanghai Jiao Tong University

2 Dept. of Computer Science and Engineering, Shanghai Jiao Tong University

3 Dept. of Computer Science, City University of Hong Kong

Page 2: Secrecy Capacity Scaling of Large-Scale Cognitive Networks

2

Outline Introduction

Network Model and Definition

Independent Eavesdroppers

Colluding Eavesdroppers

Conclusion

Page 3: Secrecy Capacity Scaling of Large-Scale Cognitive Networks

Motivations Security is a major concern in wireless networks

3

Mobile Payment Virtual Property

Privacy Military Communication

Page 4: Secrecy Capacity Scaling of Large-Scale Cognitive Networks

4

Motivations

Physical Layer Security Assume eavesdroppers

have infinite computation power

Require the intended receiver should have a stronger channel than eavesdroppers

Provable security capacity

Cryptographic methods Key distribution

Rapid growth of computation power

Improvement on

decoding technology

log(1 ) log(1 )eC SNR SNR

Page 5: Secrecy Capacity Scaling of Large-Scale Cognitive Networks

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Related works

Secrecy capacity in large-scale networks Guard zone [9] Artificial noise + Fading gain (CSI needed) [8] Using artificial noise generated by receivers to suppress

eavesdroppers’ channel quality [11]

[9] O. Koyluoglu, E. Koksal, E. Gammel, “On Secrecy Capacity Scaling in Wireless Networks”, IEEE Trans. Inform. Theory, May 2012.

[8] S. Vasudevan, D. Goeckel and D. Towsley, “Security-capacity Trade-off in Large Wireless Networks using Keyless Secrecy,” in Proc. ACM MobiHoc, Chicago, Illinois, USA, Sept. 2010.

[11] J. Zhang, L. Fu, X. Wang, “Asymptotic analysis on secrecy capacity in large-scale wireless networks,” in IEEE/ACM Trans. Netw., Feb. 2014.

Cited from [8]

Page 6: Secrecy Capacity Scaling of Large-Scale Cognitive Networks

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Motivations

Limited spectrum resources and CR networks

Key questions:

What is the impact of security in cognitive networks?

What is the performance we can achieve?

Page 7: Secrecy Capacity Scaling of Large-Scale Cognitive Networks

7

Outline Introduction

Network Model and Definition

Independent Eavesdroppers

Colluding Eavesdroppers

Conclusion

Page 8: Secrecy Capacity Scaling of Large-Scale Cognitive Networks

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Network Model and Definition – I/III

Network Area: a square Legitimate Nodes

primary users , secondary users I.I.D

Self-interference cancelation [17] adopted CSI unknown

Eavesdroppers eavesdroppers Location positions unknown CSI unknown

Cited from [17]

[17] J. I. Choiy, M. Jainy, K. Srinivasany, P. Levis and S. Katti, “Achieving Single Channel, Full Duplex Wireless Communication”, in ACM Mobicom’10, Chicago, USA, Sept. 2010.

Page 9: Secrecy Capacity Scaling of Large-Scale Cognitive Networks

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Network Model and Definition – II/III

Random permutation traffic, no cross network traffic Communication Model

Physical Model: Primary user i transmits to primary user j

Define the physical model for secondary users and eavesdroppers similarly.

Interference from other primary TXs Interference from other primary RXs

Interference from secondary TXs Interference from secondary TXs

Page 10: Secrecy Capacity Scaling of Large-Scale Cognitive Networks

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Network Model and Definition – III/III

Definition of Per Hop Secrecy Throughput: Independent eavesdropper

Colluding eavesdroppers

Definition of Asymptotic Capacity

Similarly, we can define the asymptotic per-node capacity for the secondary network

, if

Page 11: Secrecy Capacity Scaling of Large-Scale Cognitive Networks

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Outline Introduction

Network Model and Definition

Independent Eavesdroppers

Colluding Eavesdroppers

Conclusion

Page 12: Secrecy Capacity Scaling of Large-Scale Cognitive Networks

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Independent Eavesdroppers

Physical Feasibility of Security Primary Networks and Secondary Networks and Operation Rules:

• Primary users disregard secondary users;• Secondary users should affect primary users little.

Successful transmission No eavesdropper can decode the message

Page 13: Secrecy Capacity Scaling of Large-Scale Cognitive Networks

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Independent Eavesdroppers

Intuitive Primary Networks

Concurrent Transmission Range

Secrecy Capacity

Secondary Networks Unknown ? Good or bad for primary nodes

? Good or bad for eavesdroppers Depend on SUs’ locations

Page 14: Secrecy Capacity Scaling of Large-Scale Cognitive Networks

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Independent Eavesdroppers

Primary T-R pair (node i to node j)• For other primary transmitter k and receiver l

• For other secondary transmitter k and receiver l

Page 15: Secrecy Capacity Scaling of Large-Scale Cognitive Networks

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Independent Eavesdroppers

Scheduling scheme Cell Partition Round-Robin Scheduling:

• Tessellate the network into cells.• Different cells take turn to transmit.• Secondary users can transmit in non-occupied cells with the

guarantee of affecting primary transmissions little.

Figure: Simple 9-TDMA

Page 16: Secrecy Capacity Scaling of Large-Scale Cognitive Networks

Routing schemeHighway System

– Draining Phase– Highway Phase– Delivery Phase

Bottleneck: Highway Phase (nodes need to relay packets for others) Distance of primary T-R pairs is 1.

Secrecy Capacity is for primary network. Secrecy Capacity is for secondary network.

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Independent Eavesdroppers

No order cost comparing to the scenario without security concern!

Page 17: Secrecy Capacity Scaling of Large-Scale Cognitive Networks

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Outline Introduction

Network Model and Definition

Independent Eavesdroppers

Colluding Eavesdroppers

Difference with previous case

Conclusion

Page 18: Secrecy Capacity Scaling of Large-Scale Cognitive Networks

SINR of Colluding Eavesdroppers– maximum ratio combining of SINR

Bound the SINR of eavesdroppers:Disjoint rings with same size.Eavesdroppers in the same ring has a

similar SINR.Artificial noise + Path loss gain +

Cooperation

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Colluding Eavesdroppers

Page 19: Secrecy Capacity Scaling of Large-Scale Cognitive Networks

Colluding Eavesdroppers

Choice of Concurrent Transmission Range kk , artificial noise , throughputk , SINR of eavesdroppers , security

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when choosing and is a constant.

Page 20: Secrecy Capacity Scaling of Large-Scale Cognitive Networks

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Colluding Eavesdroppers

Result comparison

Cooperation in cognitive networks helps to increase secrecy capacity, compared to stand-alone networks [11].

[11] J. Zhang, L. Fu, X. Wang, “Asymptotic analysis on secrecy capacity in large-scale wireless networks,” to appear in IEEE/ACM Trans. Netw., 2013.

Page 21: Secrecy Capacity Scaling of Large-Scale Cognitive Networks

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Outline Introduction

Network Model and Definition

Independent Eavesdroppers’ Case

Colluding Eavesdroppers’ Case

Conclusion

Page 22: Secrecy Capacity Scaling of Large-Scale Cognitive Networks

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Conclusion

In this paper, we study physical layer security in cognitive networks.

Our scheme adopting self-interference cancellation is very efficient.

Cooperation between secondary network and primary network in CR networks can help to strengthen physical layer security.

Page 23: Secrecy Capacity Scaling of Large-Scale Cognitive Networks

Thank you !