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Protocols for Secure Communication in Wireless Sensor Networks

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82 Chapter 3. A Security Model <strong>for</strong> <strong>Wireless</strong> <strong>Sensor</strong> <strong>Networks</strong><br />

Random Spread Distribution<br />

This model assumes that the adversary picks arbitrary nodes randomly from<br />

the network and takes control over them. This is probably a very unrealistic<br />

model if applied to an already deployed network. It requires that the adversary<br />

breaks <strong>in</strong>to a s<strong>in</strong>gle sensor node and then randomly moves to another node.<br />

If there are measures to track such movements, this attack bears a high risk<br />

of detection. Consider<strong>in</strong>g the large number of nodes <strong>in</strong> a sensor network, a<br />

s<strong>in</strong>gle node is only of very limited value to the attacker. This value is probably<br />

exceeded by the cost of mov<strong>in</strong>g from one node to the next, which makes the<br />

attack uneconomical.<br />

However, the follow<strong>in</strong>g scenario may be more realistic. Assume that the<br />

adversary ga<strong>in</strong>s access to a set of nodes be<strong>for</strong>e deployment and manages to<br />

replace the program code on these nodes with his own. The nodes will then<br />

be randomly deployed on the network area, and the adversary ends up with a<br />

number of randomly distributed nodes he has control over.<br />

The advantage of this attack is that the adversary has access to nodes distributed<br />

throughout the whole network area, which allows him to monitor a<br />

large portion of the message traffic with relatively few nodes. In this regard,<br />

the attack is efficient <strong>for</strong> eavesdropp<strong>in</strong>g and monitor<strong>in</strong>g purposes. However,<br />

active attacks are not very effective, as the amount of data that can be <strong>in</strong>jected<br />

by a few randomly distributed nodes is small compared to the total amount of<br />

data <strong>in</strong> the network. Also, a s<strong>in</strong>gle compromised node surrounded by legitimate<br />

nodes is more likely to be expelled when show<strong>in</strong>g abnormal behaviour or<br />

report<strong>in</strong>g data with a high divergence from its neighbours.<br />

Concentrated Distribution<br />

When an already deployed sensor network is be<strong>in</strong>g attacked, the attacker might<br />

start at a certa<strong>in</strong> position and try to subvert as many nodes around that position<br />

as possible. This would allow him to control all message traffic that is go<strong>in</strong>g<br />

<strong>in</strong>to or out of that area. The cost <strong>for</strong> mov<strong>in</strong>g around (and the <strong>in</strong>volved risk of<br />

detection) is amortized over a larger number of compromised nodes, thus this<br />

attack mode is more efficient than randomly mov<strong>in</strong>g around and pick<strong>in</strong>g out<br />

s<strong>in</strong>gle nodes.<br />

As a simple <strong>for</strong>mal model of this type of attacks, we assume a start<strong>in</strong>g position<br />

and a function f that describes the probability with which a node <strong>in</strong> a<br />

certa<strong>in</strong> distance from the start<strong>in</strong>g position is be<strong>in</strong>g compromised. At the start<strong>in</strong>g<br />

position itself, this probability is equal to a success probability p0 with<br />

0 ≤ p0 ≤ 1, i.e. f (0) = p0. With <strong>in</strong>creas<strong>in</strong>g distance from the center, this

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