Transcript Slides PPT
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
Outline
Introduction
Network Model and Definition
Independent Eavesdroppers
Colluding Eavesdroppers
Conclusion
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Motivations
Security is a major concern in wireless networks
Mobile Payment
Privacy
Virtual Property
Military Communication
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Motivations
Cryptographic methods
Key distribution
Rapid growth of
computation power
Improvement on
decoding technology
Physical Layer Security
Assume eavesdroppers
have infinite computation
power
Require the intended
receiver should have a
stronger channel than
eavesdroppers
Provable security
capacity
C log(1 SNR ) log(1 SNRe )
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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]
Cited from [8]
[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.
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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?
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Outline
Introduction
Network Model and Definition
Independent Eavesdroppers
Colluding Eavesdroppers
Conclusion
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Network Model and Definition – I/III
Network Area: a 𝑛 × 𝑛 square
Legitimate Nodes
𝑛 primary users {𝑋𝑖 }𝑛 , 𝑚 secondary users {𝑌𝑖 }𝑚
I.I.D
Self-interference cancelation [17] adopted
CSI unknown
Eavesdroppers
𝑛𝜙𝑒 (𝑛) 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. 8
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
Interference from other primary TXs
Interference from secondary TXs
Interference from other primary RXs
Interference from secondary TXs
Define the physical model for secondary users and eavesdroppers
similarly.
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Network Model and Definition – III/III
Definition of Per Hop Secrecy Throughput:
Independent eavesdropper
Colluding eavesdroppers
Definition of Asymptotic Capacity
𝜆𝑝 𝑛 = Θ(𝑔(𝑛)), if
Similarly, we can define the asymptotic per-node capacity for the
secondary network
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Outline
Introduction
Network Model and Definition
Independent Eavesdroppers
Colluding Eavesdroppers
Conclusion
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Independent Eavesdroppers
Physical Feasibility of Security
Primary Networks
𝑝
𝑆𝐼𝑁𝑅𝑖𝑗 ≥ 𝛾𝑝
and
Successful transmission
𝑝
𝑆𝐼𝑁𝑅𝑖𝑒 ≤ 𝛾𝑒
No eavesdropper can
decode the message
Secondary Networks
𝑠
𝑆𝐼𝑁𝑅𝑖𝑗
≥ 𝛾𝑠 and
𝑠
𝑆𝐼𝑁𝑅𝑖𝑒
≤ 𝛾𝑒
𝛾𝑒 < min{𝛾𝑝 , 𝛾𝑠 }
Operation Rules:
• Primary users disregard secondary users;
• Secondary users should affect primary users little.
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Independent Eavesdroppers
Intuitive
Primary Networks
𝑝
𝑆𝐼𝑁𝑅𝑖𝑒
𝑝𝑟𝑖𝑚𝑎𝑟𝑦
𝑃𝑟𝑒𝑐𝑒𝑖𝑣𝑒𝑟
Concurrent Transmission Range
Secrecy Capacity
Secondary Networks
𝑠𝑒𝑐𝑜𝑛𝑑𝑎𝑟𝑦
𝑃𝑟𝑒𝑐𝑒𝑖𝑣𝑒𝑟
Unknown
? Good or bad for primary nodes
? Good or bad for eavesdroppers
Depend on SUs’ locations
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Independent Eavesdroppers
Primary T-R pair (node i to node j)
•
For other primary transmitter k and receiver l
𝑝
𝑆𝐼𝑁𝑅𝑖𝑗 ≥ 𝛾𝑝
𝑝
𝑆𝐼𝑁𝑅𝑖𝑒 ≤ 𝛾𝑒
•
For other secondary transmitter k and receiver l
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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
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Independent Eavesdroppers
Routing scheme
Highway 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.
Distance of primary concurrent transmission range is Θ(1).
Secrecy Capacity is Θ( 1/𝑛) for primary network.
Secrecy Capacity is Θ( 1/m) for secondary network.
No order cost comparing to the scenario without security concern!
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Outline
Introduction
Network Model and Definition
Independent Eavesdroppers
Colluding Eavesdroppers
Difference with previous case
Conclusion
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Colluding Eavesdroppers
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
Choice of Concurrent Transmission Range k
k , artificial noise , throughput
k , SINR of eavesdroppers , security
𝑆 𝑑
𝐺 𝑑 = log 1 +
𝑁0 + 𝐼 𝑑
𝑝
≥ log(1 +
≥
≥
𝑃𝑡 1+ 2𝑐 𝑑+1
)
𝑁0 +𝑏7′ 𝑃𝑡𝑠 +𝑃𝑟𝑠 𝜙𝑠 𝑛 𝑘𝑐 −𝛼
𝑝
𝑏7′′ 𝑃𝑡 1 +
𝑝
𝑏7 𝑃𝑡 𝑑 −𝛼
when choosing 𝑘 = Θ
−𝛼
(𝑃𝑟𝑠 𝜙𝑠
𝑛
2𝑐 𝑑 + 1
1
𝛼
−𝛼
) and 𝑏7 is a constant.
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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.
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Outline
Introduction
Network Model and Definition
Independent Eavesdroppers’ Case
Colluding Eavesdroppers’ Case
Conclusion
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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.
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Thank you !