Source-Location Privacy Protection in Wireless Sensor Network

Presented by:

Yufei Xu Xin Wu Da Teng

Outline

Introduction Related Work Model and Assumptions Implementation Theoretical Analysis Conclusion

Introduction

Wireless Sensor Network

1. A set of low-cost radio devices

2. Supplied with limited amount of energy

3. Through multi-hops to deliver data to the base station

Introduction (Cont.)

Source-location Privacy Problem in Wireless Sensor Network Open architecture of the underlying wireless-communication

technology An adversary can easily detect the source by back tracing the

routing path Evaluating Source-Location Privacy Protection

Techniques Safety Time

The number of messages sent by source before it is identified

Energy Consumption Level Total number of messages sent within the entire sensor network

Related Work

Basically, techniques for preserving source-location privacy are built upon routing protocols

Two popular routing protocols employed in sensor network: Flooding Routing

The source forwards a message to all its neighbours Subsequent sensor nodes also forward the message to their

neighbours Each sensor node only forward the same message once

Single-Path Routing Only one path is established between the source and the base station e.g. the shortest path

Related Work (Cont.)

Both of them can’t protect the source-location privacy in sensor network

As an approach, fake source messaging is proposed in [1] Introduce fake source which generates false messages to

mislead the adversary Fake messages have same length and also encrypted so that

an adversary can’t differentiate with the actual messages. As indicated in [2], this approach has a set of limitations

Not efficient in energy conservation Location of fake source is important Frequency of message generation is also important

Related Work (Cont.)

As a contribution, the phantom routing approach is proposed in [2]: Phantom routing contains two phases:

Directed random walk phase to deliver a message to a phantom source (either sector-based or hop-based random walk)

Deliver the message from phantom source to base station by using either flooding or single-path routing

As indicated in [3], phantom routing still has limitations It may lead the pre-termination of the random walk phase due to

the inappropriate selection of random walk direction Thus there may be performance dropdown in certain area of the

sensing field

Related Work (Cont.)

As an improvement, a self-adjusting directed random walk approach is presented in [3] It divides the neighbour set into four directions (E, W, N, S) The real source randomly selects one direction as the random

walk direction By encoding the direction vector into messages, it allows self-

adjusting of random walk even when random walk is blocked on one direction

When two directions are blocked, a predetermined ratio is used to determine whether to continue the random walk or not

However, we find that the above approach can be further improved

Model and assumptions

A simulative environment is created for estimating performance.[3]– a square area of 6000x6000(m2).– 10000 sensor nodes are located randomly in it.– the transmission range of each sensor node is

chosen in a way such that a sensor, in average, has 8.5 neighbors.

Model and assumptions (Cont.)

– the sink is set at the center of this area.– there is only one monitored asset.– its location remains unchanged before it is caught

by the adversary.– 4 landmarks are set at 4 corners of this square,

which will generate a message flood to help every sensor get location information of itself.

Model and assumptions (Cont.)

On the other hand, an adversary may adopt two kinds of tracing strategy.

– Patient Adversary : is referred as the adversary waits at a location until he receives a new message.

– Cautious Adversary : which means he waits at a location for a specific period of time; if no message arrives within this period, he will return to its previous location.

Implementation

Direction and position– four distinct directions:

NE,NW,SW,SE -- more precise.– square area is divided into four

parts.– each node belongs to one part.– another useful info is the distance

to sink – hops number.– neighbors are grouped into four

sets.

Landmark

Sector 2

Sector 3

Sector 1

Sector 4

Sink

ab

Implementation (Cont.)

Goal for random walk– for the phantom routing protocol, the randomness of

choosing phantom source is very important – unpredictable path.

– it can be noticed that the farther from the phantom source to the real source, the better the location-privacy can be protected.

Implementation (Cont.)

Workflow of improved method– each node maintains 4 lists for its neig

hbors.– before random walk, the real source c

hecks whether it is near the center by comparing a threshold Dsink and its hops from sink.

if in circle -> any direction if not -> direction to opposite part send msg to a neighbor in that directio

n

Landmark

Sector 2

Sector 3

Sector 1

Sector 4

Sink

ab

Implementation (Cont.)

– when a node receives msg, it checks its hops

if hops > hwalk -> take shortest-path to sink

if not -> deliver to a neighbor on the way

– if a node find no neighbor on the way, it change direction and forward msg.

– if a node is in a corner, it just stops forwarding and begin to send msg to sink usin

g shortest-path routing.-- no need to continue random walk coz msg has already traveled long enough.

c

Sink

Theoretical Analysis

Longer effective distance

Phantom Routing: 180 degree

Our improved approach: 90 degree

Theoretical Analysis (Cont.)

Phantom Routing:

oscillation-way near

Our improved approach:

relative position

far & lowest likelihood

smaller probabilities to hit the boundary

d

g

h

e

f

Original version

Improved version

Theoretical Analysis (Cont.)

Less energy consumption

Phantom Routing: directional information

Our improved approach: no directional information

Conclusion

Our approved approach achieves a longer safety time without consuming more energy than its original version. It is better than self-adjusting phantom routing in protecting source-location privacy.

Reference

[1] Ozturk, C., Zhang, Y. and Trappe, W., ”Source-location privacy in energy-constrained sensor network routing”, Proceedings of the 2nd ACM workshop on Security of ad hoc and sensor networks SASN '04, pp. 88-93, Oct. 2004

[2] Kamat, P., Zhang, Y., Trappe, W. and Ozturk, C., “Enhancing Source-Location Privacy in Sensor Network Routing”, Proceedings of the 25th IEEE International Conference on Distributed Computing Systems, pp. 599-608, June 2005

[3] Zhang, L.,”A self-adjusting directed random walk approach for enhancing source-location privacy in sensor network routing”, Proceedings of the 2006 international conference on Wireless communications and mobile computing, pp. 33-38, 2006.

Question

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