Detecting Phantom Nodes in Wireless Sensor Networks Joengmin Hwang, Tian He, Yongdae Kim (ACM Infocom2007) Presenter : Justin.

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Presentation transcript:

Detecting Phantom Nodes in Wireless Sensor Networks Joengmin Hwang, Tian He, Yongdae Kim (ACM Infocom2007) Presenter : Justin

Main ideas  Two factors:  Prevent the phantom nodes from generating consistent ranging (distance) claims to multiple honest nodes.  Detect phantom nodes by the proposed speculative method

Generating ranging claims  If the locations of neighboring nodes are known, it is easy to generate a fake location.  Without the location information of the neighboring nodes, it is hard for an attacker to generate a set of consistent ranging values (distances)

Generating ranging claims C B D A D’

Generating ranging claims C B D A D’ D’C and D’B decrease D’A increase

Generating ranging claims C B D A D’

Generating ranging claims C B D A D’ D’C and D’B increase D’A decrease

The detailed approach  Definition:  A set of nodes is consistent, if they can be projected on the unique Euclidean plane (in 3-D case, Euclidean space), keeping the measured distances among themselves.

The detailed approach  Problem:  Given a node set Nbr(v) that consists of a node v and its neighbors, and a distance set D that consists of the measured distance, denoted by Find the largest consistent subset of Nbr(v).

The detailed approach  Two phases:  Distance Measurement Phase  Filtering Phase

Distance Measurement 1)Node v measures distance to each neighbor i 2)Node v announces the measured distance 3)Node i announces its measured distance to its neighbor j, and v collects 4)For each collected distance, if, it is included in the filtering phase

Filtering  Using a graph G(V,E) to construct a consistent subset.  The set V is used to contain the node v and its neighbors  The set E is used to keep the edges between two nodes when the distance information between them maintains consistency.

Filtering 1)The local coordinate system L is determined by three nodes v, i, j with measured distance 2)Each node, calculating its location on L 3)Picking a pair of nodes, whose location on L are 4)Comparing the distance and ( which obtained in distance measurement phase ) 5)If, create edge e(i, j) in E 6)Choose the largest sizeof G(V,E)

Filtering

 If, create edge e(i, j) in E  Choose the largest sizeof G(V,E)

Filtering  Node 6 is a phantom node

Filtering

Experiment results

Conclusions  Pros  Presenting a way to exclude the phantom nodes by projecting each nodes into a local coordinate  The filtering operation is efficient  Cons  By using TDOA or TOA to measure distance, nodes need to be deployed at wide-space  It’s not suitable for small area application