Hao Yang, Fan Ye, Yuan Yuan, Songwu Lu, William Arbaugh

(UCLA, IBM, U. Maryland)MobiHoc 2005

Toward Resilient Security in Wireless Sensor Networks.

Outline

Introduction and Background On resiliency of existing solutions Design Analysis and Simulation Results Discussions and Conclusions

Introduction

Target problem: Compromised nodes Report fabrication attacks

Existing solution and their problem Multiple parties endorse an legitimate event;

en-route filtering. Problem: Threshold breaks down.

Their approach: use location-based information to achieve resilience.

General Scenario

Large scale sensor network that monitors a vast geographic terrain.

Size and shape of the terrain is known a priori Sensor nodes are uniformly randomly

deployed to the terrain. Once deployed, each node can obtain its

geographic location via a localization scheme.

One resourceful sink.

General En-route Filtering Framework

Initial: A node store some keys, it use its own key to generate a Message Authentication Code (MAC) attached to an event report. It use others keys to verify the report forwarded to it. Each key has a unique index.

Own keys: k1, …

Others keys: k2, k3, k4, …

General En-route Filtering Framework

On event occur: A legitimate report must carry m distinct MACs. Multiple nodes sense the event and collaborate generate (one or more) reports with more than m MACs.

Report | index3 | MAC3

Report | index1 | MAC1

Report | index5 | MAC5

Report | index2 | MAC2

Report | index4 | MAC4

Report | index6 | MAC6

| index1 | MAC1Report | index3 | MAC3 | index4 | MAC4

General En-route Filtering Framework

Intermediate nodes:

Received Report

Check if it has more than m MACs

Check if it can verify the MACs

Is the MACs valid?

Forward packetDrop

No

No

No

Yes

General En-route Filtering Framework

Sink verification: Sink knows every keys, it can verify every MACs.

Outline

Introduction and Background On resiliency of existing solutions Design Analysis and Simulation Results Discussions and Conclusions

Interleaved Hop-by-Hop Authentication (IHA) Design parameter: m Sensing cluster with at least m+1 nodes and

a cluster head. Along the path, two nodes that are m+1 hops

away are associated by a pair-wise key. Threshold: m.

Interleaved Hop-by-Hop Authentication (IHA)

Statistical En-route Filtering (SEF)

Global key pool is divided into m partition. Each node pre-loaded with a few keys rando

mly chosen from a single partition. When an event occurs, detecting nodes jointl

y endorse the report with m MACs, each using a key in a different partition.

Thershold: attackers obtain keys from m partition.

Outline

Introduction and Background On resiliency of existing solutions Design Analysis and Simulation Results Discussions and Conclusions

Location-Based Resilient Security (LBRS)

Terrain divided into geographic grid and each cell binded with L keys.

Each node stores one key for each of its sensing cells.

Each node randomly chosen a few remote cells based on location information as its verifiable cells, and store one key for each.

Location-Based Resilient Security (LBRS)

Location-Based Resilient Security (LBRS)

A legitimate report is jointly generated by detecting nodes, and should carries m distinct MACs.

Intermediate nodes and sink verification processes are similar to general framework.

Two more new check: All m distinct MACs should bonded to one cell. Location attached in the report consistent with the

location of MACs

Location-binding key generation

Location-binding key generation: Terrain divided into geographic grid and each cell binded with L keys.

How to construct a grid? How to derive keys based on the location info

rmation in a computationally efficient manner?

How to construct a grid

Construct a virtual square grid uniquely defined by two parameters: a cell size C, and a reference point (X0,Y0) (e.g., sink location).

Denote a cell by the location of its center, (X i,Yj), such that

How to derive keys

Preload each node with: cell size C, reference (X

0,Y0), master secret KI .

Once deployed, a node first obtains its geographic location through a localization scheme.

Derives keys during bootstrapping phase with H() is a one-way hash function. (Xi,Yj) is the loca

tion of the cell.

Location-guided key selection

A node defines an upstream region based on location information and only forward packet for its upstream region.

After defined upstream region, for each cell in its upstream region, select it as a verifiable cell with probability

d is the node’s distance to the sink, Dmax is the max distance between network edge and sink

Location-guided key selection

Location-guided key selection

How to select upstream region and accommodate node failures? Designed to work with geographic routing

protocol. Upon moderate node failures, geographic

routing protocol find a closer detoured paths . Define beam width b. Use b and d (distance to sink) to define

upstream region.

Benefits

Damage is bonded to some local cells. Randomized multiple compromised nodes are

difficult to compromise a cell. Location-guided key selection can reduce the

keys stored on one node and still achieve reasonable filtering power.

Outline

Introduction and Background On resiliency of existing solutions Design Analysis and Simulation Results Discussions and Conclusions

Parameter settings

Analysis—Filtering Effectiveness

One node compromised. Detection Ratio: close to one. Filtering Position:

Analysis—Key Storage Overhead

Simulation

Platform: own simulator by Parsec language 30K nodes, 5Km x 5Km field, 100m x 100m

cell. Each simulation repeated 1000 times.

Simulation—Resiliency to random node compromise

Compromised nodes randomly scattered. How many cells will be compromised.

Simulation—Resiliency to random node compromise How many distinct keys compromised in cells

Nc = Number of compromised nodes

Simulation—Filtering Power

Kc = number of compromised keys in a cell

Simulation—Delivery Ratio

Outline

Introduction and Background On resiliency of existing solutions Design Analysis and Simulation Results Discussions and Conclusions

Discussion

Prototype implementation: could all these fit into sensor nodes??

Platform: MICA2 Code size:

9358 bytes ROM, 665 bytes RAM Execution time: 100x100 cells

Bootstrapping: 2.8 sec MAC generation and verification: 10 ms

Discussion (Cont’)

Sensor deployment: Location information is known? Location information is required?

Routing Upstream region estimation is designed to work

with geographic routing protocols. They found some non-geographic routing

protocols (Directed Diffusion, GRAB) fit well with this model.

Require future study.

Conclusions If location is a required information, embedded

keys with locations seem to be obvious. Upstream region model is a good way to reduce

the key storage and still maintain the filtering power.

They did quite a bit of analysis and simulations to verify their claims.

Security setting is based on application scenario.