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Jun Sup Lee Dependable Software LAB at KAIST Nov. 21 th 2006

Coordinated Sensor Deployment for Improving Secure Communications and Sensing Coverage Yinian Mao, Min Wu Security of ad hoc and Sensor Networks, Proceedings of the 3rd ACM workshop on Security of ad hoc and sensor networks, November 07 - 07, 2005 Paper Review. Jun Sup Lee

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Jun Sup Lee Dependable Software LAB at KAIST Nov. 21 th 2006

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  1. Coordinated Sensor Deployment for Improving Secure Communications and Sensing CoverageYinian Mao, Min WuSecurity of ad hoc and Sensor Networks,Proceedings of the 3rd ACM workshop on Security of ad hoc and sensor networks, November 07 - 07, 2005Paper Review JunSupLee DependableSoftwareLAB at KAIST Nov.21th2006

  2. Agenda • Introduction • Problem Statement • Contribution • Contents • Background • Static Sensor deployment • Location Adjustment • Conclusion • Q&A

  3. Introduction| Sensor Network and Security Sensor Network – Great Potential in application Habitat monitoring Wildlife tracking Building surveillance Military combat Important design Issue Efficient sensing coverage Node-to-node or node-to-base-station communications Security in information gathering and relay by the sensors • This paper shows that the system performance on these aspects • How the sensors are deployed in the field • How the sensor locations can be adjusted after the initial deployment

  4. Introduction| Sensor Network and Security | characteristic Sensing and Communication on Sensor Node Limitation of sensing range and the communication range  because of physical characteristics Placement of sensor nodes will have great impacts on sensing coverage communication connectivity Rely on Wireless Transmission malicious adversaries could intercept the communications Modify the data packets, or inject falsified packets. Message authentication code with cryptographic Symmetric key cryptography lower computational complexity Preferred in practice Key Pre-distribution

  5. Introduction| Contribution Analyze Impact on secure connectivity and sensing coverage Static Sensor deployment Hexagon lattice topology Square lattice topology Location adjustment after deployment VFSec algorithm Weighted Centroid algorithm • Current Work • Optimize the sensing coverage • Do not concern secure sensor communication • A new framework for coordinated updates of sensor locations. • Jointly optimize sensing coverage and secure connectivity

  6. Background| Sensing Coverage and Sensing Capability Sensing Coverage Rs : Sensing radius d(*,*) : Euclidean distance S = 1 : sensor has the capability to sense S = 0 : otherwise Sensing Capability Rc : Communication radius d(*,*) : Euclidean distance T = 1 : link exists T = 0 : otherwise

  7. Background| Efficient Sensing in Static Deployment • Static Deployment • Sensing efficiency ratio – (Circle covering problem : covering density, covering thickness) • , , • Acol : actual covered area by all the sensor nodes • Aseq : sum of the area covered by each individual sensor • Lowerbound : (by hexagon lattice) • Nomalize distance D1 • D1 : distance to its horizontal/vertical neighbor in Square lattice deployment • D2 : distance to its diagonal neighbor in Square lattice deployment • D3 : distance from a node to its six neighbors in hexagon lattice deployment

  8. Background| Key Pre-distribution for Sensor Networks Key Pool P Each node randomly selects R keys (Key Ring) N1 N2 N3 N4 … • When |P| = 1000, R=20 / 30 • p (two nodes have a common key) =0.335 / 0.605 • Key pre-distribution in WSNs • Loading Keys into sensor nodes prior to deployment • Two nodes find a common key between them after deployment • Challenges • Memory/Energy efficiency • Security: nodes can be compromised • Scalability: new nodes might be added later

  9. Lattice-Structured Deployment| Fundamental Relations Between Deployment Lattices • Expected number of secure links versus communication radius • Square lattice and Hexagon lattice, key-pre distribution • : Key sharing probability

  10. Lattice-Structured Deployment| Secure Connectivity Under Perturbed Deployment Lattice • Expected number of secure links per node versus communication radius. • Actual deployment location : • r : zero-mean distribution with Gaussian • Probability that a designed neighbor in the hexagon lattice can establish a secure link with the center node : • expected number of secure links for the center node (hexagon): • expected number of secure links for the center node (square): • A : horizontal/vertical neighbors • B : diagonal neighbors

  11. Lattice-Structured Deployment| Secure Connectivity Under Perturbed Deployment Lattice • Expected number of secure links per node versus communication radius. • Key ring 100 / Key pool : 1200

  12. Location Adjustment : Virtual Force| Effect on Secure Connectivity by the Existing Approach • Virtual Force algorithm • Maximize total sensing coverage • : Unit-length pointing from the location of ni to nj. • Move Node ni • Direction : • Magnitude :

  13. Location Adjustment : Virtual Force| Effect on Secure Connectivity by the Existing Approach • Impact of location adjustment to the establishment of secure links using VFA • Half of the nodes are no longer connected with the largest connected group, which reduces the capability of secure communications between the sensor nodes.

  14. Location Adjustment : VFSec| VFSec • VFSec Algorithm • Performance metric : ( : total sensing coverage, : secure link per node) • While average number of secure links per node is around 3 • W1 = 1 • W2 = 1/3 • VFSec

  15. Location Adjustment : VFSec| Simulation Results • Comparison of VFA and VFSec with Uniform random initial deployment

  16. Location Adjustment : VFSec| Simulation Results • Comparison of VFA and VFSec using square deployment lattice under Gaussian deployment deviation. • Comparison of deployment lattice using VFSec under Gaussian deployment deviation.

  17. Location Adjustment : WTC| Weighted Centroid Algorithm • Weighted Centroid Algorithm • 1. Compute Voronoi cell V • 2. Generate uniform grid points • 3. Assign weight using assignment procedure • 4. Compute location : • 5. Compute the movement vector

  18. Location Adjustment : WTC| Simulation Results • Comparison of the WTC and minmax algorithm, small Gaussian deployment deviation, hexagon lattice - key pre-distribution. • Comparison of the WTC and minmax algorithm, large Gaussian deployment deviation, hexagon lattice - key pre-distribution.

  19. Location Adjustment : WTC| Simulation Results • Comparison of the weighted centroid and minmax algorithm, uniform random deployment with basic key pre-distribution.

  20. Conclusion| Conclusions and outlook of this paper Static sensor deployment Square / Hexagon lattice two lattice topology exhibits range-dependent performance there is no all-time winner in the context of secure connectivity Location Adjustment VFSec / WTC WTC algorithm outperforms under moderate to abundant node density VFSec algorithm outperforms than the existing virtual force based algorithms WTC is more suitable to be performed by individual sensors than VF Performing WTC generally requires more computation than performing schemes based on virtual force

  21. Thankyou • Question? • Formorediscussion: • Rm4428,Jslee@dependable.kaist.ac.kr

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