Location-Aware Security Services for Wireless Sensor Networks using Network Coding

1. Location-Aware Security Services for Wireless Sensor Networks using Network Coding IEEE INFOCOM 2007 최임성

2. Agenda • Introduction • Preliminaries • Location-aware Network Coding Security (LNCS) • Security Analysis and Performance Evaluation • Comparison with LEDS • Conclusion and Discussion

3. Introduction • Wireless Sensor Networks (WSNs) Sink node Source node

4. Introduction • End-to-End Data Security Requirements • Data Confidentiality • Data Authenticity • Data Availability Sink node Source node

5. Introduction • Previous work • IHA [ZSJN04] • SEF [YLLZ05] • LBRS [YYYLA05] • LEDS [RLZ06] Cannot provide Data Availability since data is transmitted on a path. 2 3 1

6. Preliminaries • Network coding • Present novel way to distribute information • Allow mixing of data at intermediate nodes

7. Preliminaries • Naïve Secret Sharing Algorithm • Divide a secret into pieces called shares, and distribute them amongst a set of user • User can reconstruct the secret with pieces • (T,n)-threshold scheme (T ≧ n) • Divide a secret into T pieces • Anyone has n pieces can reconstruct the secret

8. Preliminaries • Pseudo-random Function • Randomly mapping a input in the domain to a value in the range

9. Preliminaries • Hash Tree

10. Notations

11. LNCS-Overview • Setup • Secure Initialization • Report Generation • Report Authentication and Filtering • Report Forwarding • Sink Verification

12. LNCS-Secure Initialization

13. LNCS-Report Generation 1. Broadcast its own sensor reading to other selected nodes 2. Aggregate all sensor reading with median 3. Make the report using secret sharing algorithm as like 4. Broadcast the di to other node 5. Make the coefficients matrix C0

14. LNCS-Report Generation 6. Encodes the vector d as follows 7. Divide e0 and C0 uniformly as much as T0 8. Each node broadcasts the packets

15. LNCS-Report Authentication and Filtering

16. LNCS-Report Forwarding

17. LNCS-Sink Verification

18. Security Analysis • Data Confidentiality • To recover original report data, the adversary should have the node keys of T0 at least t. • In case of cell key

19. Security Analysis • Data Authenticity

20. Security Analysis

21. Security Analysis • Data Availability

22. Security Analysis

23. Performance Evaluation • No simulation • Computation Overhead • O(T03) • Communication Overhead • O(T02)

24. Comparison with LEDS • More resilient against node compromise, but more Communication overhead occur due to transmission of coefficients matrix

25. Conclusion • LNCS provides end-to-end data security with network coding. • LNCS has higher resilience against node compromise and provides better data availability than LEDS.

26. Discussion • No simulation • High overhead • Long end-to-end delay compared with shortest path • Meaningful? LEDS already have sufficient resilience to node compromise

27. Reference [ZSJN04] S. Zhu, S. Setia, S. Jajodia, and P. Ning, “An interleaved hop-by-hop authentication scheme for filtering of injected false data in sensor networks,” in Proc. IEEE Symp. Secur. and Privacy. CA: IEEE Comput. Soc., May 2004, pp. 259–271. [YLLZ05] F. Ye, H. Luo, S. Lu, and L. Zhang, “Statistical en-route filtering of injected false data in sensor networks,” IEEE J. Sel. Areas Commun., vol. 23, no. 4, pp. 839–850, Apr. 2005. [YYYLA05] H. Yang, F. Ye, Y. Yuan, S. Lu, and W. Arbaugh, “Toward resilient security in wireless sensor networks,” in Proc. ACM Int. Symp. Mobile Ad Hoc Net. Comput. - MobiHoc’05. NY: ACM Press, 2005, pp. 34–45. [RLZ06] K. Ren, W. Lou, and Y. Zhang, “LEDS: Providing location-aware end-toend data security in wireless sensor networks,” in Proc. IEEE Conf. Comput. Commun. - INFOCOM’06, 2006.