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A Key Management Scheme for Wireless Sensor Networks Using Deployment Knowledge

A Key Management Scheme for Wireless Sensor Networks Using Deployment Knowledge. Presenter: Todd Fielder. Key Agreement Schemes. Trusted Server Requires trusted infrastructure Self-Enforcing Asymmetric cryptography Pre-Distribution Key information is pre-distributed prior to deployment

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A Key Management Scheme for Wireless Sensor Networks Using Deployment Knowledge

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  1. A Key Management Scheme for Wireless Sensor Networks Using Deployment Knowledge Presenter: Todd Fielder

  2. Key Agreement Schemes • Trusted Server • Requires trusted infrastructure • Self-Enforcing • Asymmetric cryptography • Pre-Distribution • Key information is pre-distributed prior to deployment • In sensor networks, only a small portion of the keys are predistributed.

  3. Key Pre-distribution • Use only a subset of keys within the network and probabilistically guarantee a connected graph dependent on node density • Not all nodes will be connected • Possible to increase this probability and connected nodes if deployment knowledge is used • Nodes will be deployed in some order. • i.e. there is a higher probability that a node deployed at time t we be closer to other nodes deployed at time t than to nodes deployed at time (t+1).

  4. Definitions and Assumptions • Static Nodes • Deployment is evenly distributed through region. • Is this a safe assumption? • Deployment Point • Point location where a node may be deployed • May reside in an area around deployment point which is defined by a probability density function (pdf). • i.e. the helicopter where the node is dropped from • Resident Point • Point near the deployment point where sensor actually resides. • i.e. where the node lands.

  5. Group-Based Deployment Model • Group of sensors are deployed at a single deployment point. • Increases the pdf with a group • Decreases the pdf between groups. • For a uniform distribution policy, there is no knowledge about which nodes will be neighbors • Requires a larger key pool. • Decreases probability of sharing keys. • This research distributes nodes uniformly in a 2X2 grid.

  6. Protocol • Key Pre-Distribution • Global key pool, S, is divided into t*n (number of groups) number of key pools. • Goal is to allow nearby key pools S i, j to share keys with a neighboring group Si+1, j. • Each node contains a subset m of their groups key pool.

  7. Phases 2 & 3 • Shared key Discovery • Broadcast indices of keys. • Setup secure links with neighbors. • Path Key Establishment • Use previously established secure channels to setup keys with unconnected neighbors. • Allows intermediate nodes to determine keys. • Problem: Intermediate nodes may be compromised, choose a key known by attacker. • Probability of securing a link between nodes over three hops is close to one. • Requires communication overhead • Between nodes • To determine who is choosing the key

  8. Setting up Key Pools • Horizontally or vertically neighboring key pools share (0<a<.25) Sc keys2. • Diagonal neighbors share (0<b<.25) Sc keys • 4a + 4b = 1 • A and B are the over-lapping factors and define the amount of keys shared by neighboring groups. • Non-neighboring groups share no keys.

  9. Determining Overlapping Factors • A determines shared values between horizontal/vertical neighbors. • Connectivity (100)= .68 • B determines shared keys with diagonal neighbors. • Connectivity (100) = .48

  10. Key Pool Size • Group S1,1 chooses Sc from S, then removes those keys • For each cell S1,j, for j=2…n, pick a*(Sc) keys from S1,j-1. Then pick (1-a)*(Sc) from pool. • Repeat for each row Si,j, also picking b*(Sc) keys from Si-1,j-1. • Flaw: There is no guarantee that a key will not percolate from one grid to the next if node (j+1) can pick arbitrary keys from j. • Causes nodes to share keys.

  11. Experimental Setup • S = 100,000; a=.167; b=.083. • Number of nodes = 10,000 • Deployment area = 1000m X 1000m • t=n=10 • Grid size = t X n = 100m • Group size = number of nodes / #grids • 100 nodes per group • Communication Range (R) = 40m • Sc = 1770 (for each group)

  12. Evaluation • Local Connectivity: Probability that two neighboring nodes share a key. • M: number of keys

  13. Evaluation cont. • Global Connectivity: relation between size of isolated components and size of graph. • Excludes nodes outside of communication range since this is due to deployment and not key-distribution.

  14. Communication Overhead • As number of keys increase in memory, communication required decreases.

  15. Point of Uncertainty • If each group shares only 1770 keys, a lot of keys are reused unnecessarily. • 100 nodes per group * 100 keys per node. • Do we need 100 keys per group? • Is group connectivity guaranteed to be 100%?

  16. Questions???

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