Presentation is loading. Please wait.

Presentation is loading. Please wait.

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.

Similar presentations


Presentation on theme: "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."— Presentation transcript:

1 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

2 2 Outline Introduction Network Model and Definition Independent Eavesdroppers Colluding Eavesdroppers Conclusion

3 Motivations  Security is a major concern in wireless networks 3 Mobile Payment Virtual Property Privacy Military Communication

4 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

5 5 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]

6 6 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?

7 7 Outline Introduction  Network Model and Definition Independent Eavesdroppers Colluding Eavesdroppers Conclusion

8 8 Network Model and Definition – I/III 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.

9 9 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

10 10 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

11 11 Outline Introduction Network Model and Definition  Independent Eavesdroppers Colluding Eavesdroppers Conclusion

12 12 Independent Eavesdroppers Successful transmission No eavesdropper can decode the message

13 13 Independent Eavesdroppers

14 14 Independent Eavesdroppers

15 15 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

16 16 Independent Eavesdroppers No order cost comparing to the scenario without security concern!

17 17 Outline Introduction Network Model and Definition Independent Eavesdroppers  Colluding Eavesdroppers  Difference with previous case Conclusion

18  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 18 Colluding Eavesdroppers

19 19

20 20 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.

21 21 Outline Introduction Network Model and Definition Independent Eavesdroppers’ Case Colluding Eavesdroppers’ Case  Conclusion

22 22 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.

23 Thank you !


Download ppt "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."

Similar presentations


Ads by Google