KCSR: KEYMATCHES CONSTRAINED SECURE ROUTING IN

HETEROGENEOUS WIRELESS SENSOR NETWORKS

K. Shaila, G. H. Vineet, C. R. Prashanth, V. Tejaswi, K. R. Venugopal

Department of Computer Science and Engineering, University Visvesvaraya College of Engineering

Bangalore University, Bangalore 560 001, India

L. M. Patnaik

Vice Chancellor, Defence Institute of Advanced Technology, Pune, India

Keywords:

Heterogeneous Networks, Key Distribution, Node Compromise, WSNs Security.

Abstract:

Wireless Sensor Networks (WSNs) consists of a large number of tiny autonomous devices called sensors

which are vulnerable to security threats. Heterogeneous Wireless Sensor Networks consists of two types of

nodes L1 and L2 that employees Unbalanced Key Distribution Scheme to ensure enhanced security. In this

paper, the concept of Link Strength is utilized, which determines the path to be selected for secure routing.

Our Keymatches Constrained Secure Routing(KCSR) algorithm provides the ﬂexibility to choose secure path

and then route the data accordingly. In this approach, secure and stable paths are chosen for communication.

Simulation results show that the proposed algorithm yields better results emphasizing security when compared

with earlier works.

1 INTRODUCTION

Wireless Sensor Networks (WSNs) consists of

spatially distributed autonomous devices. They are

used to assimilate and interpret real time data in

smart environment applications like in military bases

or vehicle target tracking systems. Owing to the

criticality of data, many applications require secure

communication. WSNs are vulnerable to security

attacks: due to the broadcast nature of transmission,

easily accessible to the attackers and the nodes are

exposed which can be destroyed.

WSNs needs a secure key management technique

to protect itself from any attack that targets conﬁden-

tiality, integrity and authentication properties of its

communication channels. A well appreciated solu-

tion that has been widely used is random deployment

of keys in a balanced network. Such a homogeneous

network made the nodes more vulnerable to security

breaches.

Motivation: Predeployed nodes exchange encrypted

messages to establish communication. Secure com-

munication is established depending on the number

of keymatches. Multiple common keys provides

enhanced security compared to a single key match.

The security level is enhanced by considering a

heterogeneous network with an asymmetric key

management technique.

Contribution: We utilize an asymmetric predis-

tribution of keys for all nodes in heterogeneous

environment. Nodes that desire to communicate,

exchange their key identiﬁers along with the keys

to ﬁnd a match. Instances wherein there are no

key matches, leverages the use of small percentage

of more capable sensor nodes with enhanced level

of security. We have proposed Link Strength that

depends on the number of key matches and total

number of secure links as a measure of security in

the network. When the keys between any two nodes

match with each other, then a link is established

between the nodes.

Organization: The remaining part of the paper con-

sists of a brief review of Related works in Section 2.

Section 3 explains System Model and Problem Deﬁ-

nition. A mathematical model is derived in Section 4

followed by Algorithm in Section 5. Section 6 analy-

ses the performance and conclusions in Section 7.

Shaila K., Vineet G., Prashanth C., Tejaswi V., Venugopal K. and Patnaik L..

KCSR: KEYMATCHES CONSTRAINED SECURE ROUTING IN HETEROGENEOUS WIRELESS SENSOR NETWORKS.

DOI: 10.5220/0003438700130022

In Proceedings of the 13th International Conference on Enterprise Information Systems (ICEIS-2011), pages 13-22

ISBN: 978-989-8425-56-0

 2011 SCITEPRESS (Science and Technology Publications, Lda.)

GW GW

Data

Sink

Figure 1: Model for Heterogeneous networks consisting of

two types of nodes.

2 RELATED WORK

WSNs are small autonomous networked, low power

bodies, called motes and are made of piezoelectric

material (F. L. Lewis and Wiley, 2004). WSNs

consists of spatially distributed autonomous devices

used for distributed information accumulationin unat-

tended areas. Eschenauer et al., (Eschaenauer and

Gligor, 2002) proposed a Probabilistic Key Predistri-

bution Scheme for pairwise key establishment. Each

senor node randomly picks a set of keys from a key

pool before deployment so that any two sensor nodes

have a certain probability of sharing atleast one com-

mon key.

Du et al., (Wenliang Du and V, 2003) proposed a

new predistribution scheme which uses pairwise keys

that enable authentication. It assures substantially im-

proved network resilience against node capture over

the existing schemes. Chan et al., (Haowen Chan and

Song, 2006) further extended this idea and developed

two key predistribution techniques: q composite key

predistribution and random pair-wise key distribution

scheme. This scheme randomly picks pairs of sensors

and assigns each, a pair of unique random keys.

Traynor et al., (Traynor et al., 2006)(Traynor

et al., 2007) proposed LIGER, a Hybrid Key Man-

agement Scheme with the presence and absence of

a Key Distribution Center (KDC). When KDC is

not available, nodes communicate securely with each

other based upon a probabilistic unbalanced method

of key management. They probabilistically authenti-

cate neighboringdevices with which they are commu-

nicating.

Perrig et al., (Perrig et al., 2002) proposed Se-

curity Protocols for Sensor Networks(SPINS). Here,

each sensor node shares a secret key with the base

station. Debao et al., (Debao Xiao and Zhou, 2006)

extended SPINS to provide additional security. Jian

Chao et al., (Chao and Xiuli, 2008) presents an

overview of the various attacks and defenses on each

of the concerned layers in Sensor Networks. Roman

et al., (Rodrigo Roman and Lopez, 2005) identiﬁed

three basic factors in the design of a key infrastruc-

ture for WSNs: Key Storage, KeyDistribution and Key

Maintenance.

Yong Wang et al., (Wang and Ramamurthy, 2008)

use ﬁve different types of keys to ensure security in

the Sensor Network. The protocol assumes the com-

promise of the base station and sensor nodes. Karlof

et al., (Chris Karlof and Wagner, 2004) proposed

a link layer security architecture for WSNs, where,

the keying mechanism described gives an emulated

overview about Tinyseckey.

Wang et al., (Yong Wang and Xue, 2008) pro-

posed security of the base station and proposes m key-

ing which has two schemes namely, key predistribu-

tion scheme and key revocation scheme. Chao et al.,

(Chao and Xiuli, 2008) presents an overview of the

various attacks and defenses on each of the concerned

layers in Sensor Networks. A number of key distribu-

tion schemes exists, but the most widely used is the

q-composite Key Predistribution Scheme. A matrix

key distribution presents a novel bidirectional method

which generates a number of combinations. How-

ever, the computation increases drastically consum-

ing a large amount of energy, reducing the efﬁciency

of WSNs.

Boujelben et al., (Manel Boujelben and Youssef,

2009) have proposed a pairwise Key Management

protocol that is applied to two tiered Heterogeneous

Wireless Sensor Networks. They have proposed prob-

abilistic key predistribution which is used in the lower

tier of the network architecture and public key cryp-

tography in the upper tier. Our scheme provides a

paradigm to provide security through Link Strength

of the path.

3 MODEL AND PROBLEM

DEFINITION

3.1 System Model

The sensor network consists of static heterogeneous

nodes as shown in the Figure 1, with Unbalanced Key

Distribution and provides secure hop-to-hop commu-

nication. It minimizes the burden of less capable

nodes and routes the encrypted data through more ca-

pable nodes. Enhancement of security is an added ad-

vantage when Unbalanced Key Distribution is incor-

porated in Heterogeneous Network Scheme. We have

considered two types of nodes, more capable nodes

as Level1(L1) nodes and less capable nodes are repre-

ICEIS 2011 - 13th International Conference on Enterprise Information Systems

sented with circles as Level2(L2) nodes. The number

of L1 nodes is (1/8)th i.e., 12.5% of the entire net-

work(Traynor et al., 2006). The effect of node com-

promise is less when L1 nodes are (1/8)th of the net-

work.

The network communication is established by ex-

change of keys among the nodes. Communicating

nodes sharing a common key become trusted neigh-

bors. However, malicious nodes could manipulate

messages during transmission. This leads to secu-

rity breach. Depending on the data to be routed, it

would be appropriate to surpass the network trafﬁc

through L1 nodes, which inturn reduces the burden

on L2 nodes, providing increased level of security and

minimizing the effects of node compromise.

3.2 Problem Deﬁnition

WSNs are vulnerable to attacks due to broadcast na-

ture of transmission medium, resource limitation on

sensor nodes and uncontrolled environments where

they are left unattended. The chances of threats and

attacks are common with Homogeneous Networks.

Such risks can be minimized using the Heterogeneous

Networks. The main objectives of this work is to:

(i) Find maximum number of key matches between

the communicating nodes.

(ii) To select the path with higher degree of security.

3.3 Assumptions

In the heterogeneous model,

(i) L1 nodes are robust and have high processing ca-

pability. Based on the shared key, they take the

role of gateway in the network.

(ii) In addition to tamper resistant casings (F. L. Lewis

and Wiley, 2004)(Traynor et al., 2007), L1

nodes are assumed to be equipped with fast en-

cryption and decryption algorithms to protect

their additional keys from compromising if cap-

tured. Chances of L1 nodes getting compro-

mised/captured is minimum.

(iii) L2 nodes have less sensing capacity, memory and

number of keys deployed. L2 nodes sense and ac-

cumulate the data.

Link Strength for a given node in the network is

deﬁned as the ratio of total number of keymatches

to the total number of links. Based on the value of

Link Strength, an appropriate path(direct or indirect)

is chosen to route the data securely for a given

application.

Link Strength =

∑

i=1

(1)

= Common keys in the direct and indirect path,

where i varies from 1 keymatch to n keymatches and

L is the total number of links amongst the communi-

cating nodes in the network.

4 MATHEMATICAL MODEL

(i) THEOREM : In a Heterogeneous Wireless

Sensor Network. Let N be the total number of nodes

consisting of L1 and L2, with 12.5% of N being L1

based on capability, cost, efﬁciency and optimization

of security. Consider, a global key pool of size P.

Let m keys be deployed in L1 nodes and k keys be

deployed in L2 nodes such that P>>m>>k.

(ii) Statement : The Link Strength varies exponen-

tially with the threshold keys or number of common

keys after the direct phase.

Link Strength ∝ e

where, T

is the threshold keys or number of key

matches after direct phase and i varies from 1,2,3. . .

(iii) Proof : Consider the predeployment of m

keys in L1 nodes without replacement. Number of

ways in choosing m keys from global key pool P is,





m!(P−m)!

(2)

Similarly, deploy k keys from (P−m) keys in L2

nodes. Number of ways in choosing k keys from

(P−m) is,



P−m



(P−m)!

k!(P−m−k)!

(3)

The probability(M

) of not ﬁnding atleast one key

match is determined by the ratio of number of ways

of choosing keys for L1 followed by L2 to total con-

nections possible





which is given using Eq. 2 and

Eq. 3.

(P−m)!(P−k)!

P!(P−m−k)!

(4)

The number of keymatches between any two com-

municating nodes after direct or indirect keymatch

phase is represented in Eq. 4. Thus, the probability of

atleast one keymatch (M

) is,

= 1−

(P−m)!(P−k)!

P!(P−m −k)!

(5)

Next, the probability of exactly one key match is,

= 1−

k(P−m)!(P−k)!





P!(P−m −k + 1)!

(6)

KCSR: KEYMATCHES CONSTRAINED SECURE ROUTING IN HETEROGENEOUS WIRELESS SENSOR

NETWORKS

Table 1: Notations.

Symbols Definition

dst Destination Node

src Source Node

Rnd() Pseudo Random Generating

Function

Maximum possible value that

is generated

Maximum global keys list

size

lk1

Maximum number of keys

present in L1 node

lk2

Maximum number of keys

present in L2 node

GK[1−2][1...n

] List of global keys

LK1[1−2][1...n

lk1

] List of local keys present in

L1 nodes

LK2[1−2][1...n

lk2

] List of local keys present in

L2 nodes

N Total number of nodes in the

network

Number of common key

matches after direct phase

L Total number of links in the

network

Common key matches

through direct phase

IDC

Common key matches

through indirect phase

Exch[1..] List of exchangeable

key identiﬁers

L2Neigh[ j] Gateway node L2 with

node j

Neigh[ j] List of Next Hop node

Deploy one key from a pool of m keys to L1 (m ⊆ P).

Using Eq. 4 and Eq. 5, the probability of exactly x

keymatches is derived as to be:

k(P−m)!(P−k)!





P!(P−m −k + x)!

(7)

where, x = 1, 2, . . . n.

Total links in the network consists of direct links and

indirect links. Total connectivity in the network con-

sisting of N nodes is given by,

Total connectivity = N(N-1).

However, the total connectivity equation holds true if

the connection is one-to-one and ideal. In the real sce-

nario, the network connectivity may not be the same.

Hence, derive the probability of having indirect links

in the network. Probability of having no direct links

) or indirect links is deﬁned as summation of the

probability of having exactly i keymatches varying

over a threshold T

to T

. Substituting for x = 1, 2,

. . .,n in Eq. 7, P

d is,

k(P−m)!(P−k)!

∑

i=1





(P−m−k+ i)!

k(P−m)!(P−k)!(2

−1)

∑

i=1

(P−m−k+ i)!

(8)

Since P is very large, we use Stirling’s approxi-

mation for n!

n! ≈

√

2πn

−n

Finally, the expression obtained from Eq. 8 is,

k(P−m)!(P−k)!(2

−1)

√

2π

∑

i=1

β+

(9)

where, β is (P−m−k + i)!

Illustration : The key factor to determine the degree

of security while routing is Link Strength. Higher the

value of Link Strength, more secure is the path for the

data to be routed. In case of indirect communication

between the nodes, the value of Link Strength is

the average of common keys between L1 and L2.

Since the value of Link Strength is dependent on the

number of links, this is inturn a factor of number of

nodes in the network. Network being heterogeneous,

value of Link Strength is the total of the values in the

direct and indirect communication.

A B

Figure 2: Stage 1: Establishment of direct path. Where, 1-

Request sent for establishing direct path and 2-Key sent as

an acknowledgment, assuring secure link.

The method described provides the ﬂexibility to use

any paths to route the data based on the degree of

security required for a particular application. When

different values of n are substituted in Eq. 9, we get

different values of P

. This value is used to calcu-

late T

, where, i varies from 1, 2, ...n. As an example,

consider three common keys are required for secure

communication. The value of T

is obtained by sub-

stituting 3 for i in Eq. 9. If this value suits for a

given application, then three keymatches are chosen

to route the data securely. Similarly, try for differ-

ent values of i, i.e., common keys matches. Accord-

ing to the theorem, as the value of T

increases with

ICEIS 2011 - 13th International Conference on Enterprise Information Systems

i, the Link Strength also increases exponentially and

increases the degree of security to route the data.

However, if more number of common keys are cho-

sen then, the data transfer becomes complicated and

therefore time required is more. Some applications

require the data to be routed quickly. In such a case,

the number of common keys required for communi-

cation is decreased and the data is routed at higher

speed. Thus, for any given application, the data can

be routed with assured security. The value of Link

Strength calculated becomes the theoretical value.

However, this method of calculating Link Strength is

computationally intensive since Eq.9 is complex.

5 ALGORITHM

A secured data routing must be established among the

various paths available that jeopardize the effects of

node compromise. Based on Link Strength, the pro-

posed method passes the data through an indirect link,

even though the direct link exists. This ensures higher

degree of security to the network. The notations used

in this paper are deﬁned in Table 1. The various stages

in the algorithm are:

3 4

Figure 3: Stage 2: Establishment of indirect path. Where,

1-Direct path establishment is not possible. X indicates its

failure, 2-Request sent to route data via L1(gateway) to B,

if path is secure and 3,4-Acknowledgment given by L1 to

request L2 nodes.

5.1 Unbalanced Key Distribution Phase

Unbalanced Key Distribution of keys depends on the

previous approach proposed by Gligor (Eschaenauer

and Gligor, 2002). In the balanced approach, out of

the total P keys in the pool, if k are randomly se-

lected without replacement, then the probability of

the two nodes having same common keys k, sharing

atleast one key is determined. However,if there exists

no keymatch, an alternate path is established through

one or more intermediate nodes having common keys.

Given, the same key pool of size P, store a pool of

keys of size m in L1 nodes and a key pool of size k in

L2 nodes where (m >> k).

An array of global key pool of size n

is generated. Local key pool is generated af-

ter the generation of global keys with unique

key identiﬁers LK1[1][1...n

lk1

] or LK2[1][1...n

lk2

All local keys are subset of global keys and

LK1[2][1...n

lk2

||n

lk2

]=GK[2][1...n

Once the keys are deployed both L1 and L2 nodes

learns its neighbors through HELLO messages. In

the given transmission range, each node broadcasts its

key identiﬁers to its neighbors and ﬁnds the node(s)

that share a common key, to communicate. The se-

cure path is established if there exists a key match.

However, the best secure path as per our scheme is

not yet chosen. In this method, we transmit the key

identiﬁers and not the key themselves, because sufﬁ-

cient information can be gathered as in trafﬁc analy-

sis attack (Haowen Chan and Song, 2006). Thus, the

neighboring L2 node in response sends the key identi-

ﬁer to the source as an acknowledgment, thus making

the link secure.

However, if no keymatch exists, then L2 nodes

establishes the link via L1. Since L1 nodes have

more keys, communication through L1 is safe and se-

cure. The communication process is initiated, when

L2 nodes wishing to communicate, sends its identi-

ﬁers to L1. L1 node(s) checks with its own set of key

identiﬁers. When there exists a keymatch between

L1 node and set of L2 nodes, L1 node sends an ac-

knowledgment message to the set of L2 nodes. Thus,

communication via L1 ensures trusted path. Differ-

ent stages in direct and indirect communication are

shown in the Figure 2 and Figure 3.

5.2 Selection of Path based on Link

Strength

The keymatch phase as described earlier, minimizes

the effects of node compromise, but not to a larger

extent. If the intruder overhears and successfully de-

crypts the shared key, the link becomes insecure. It

would disrupt the network and sabotages the efﬁcient

secure link that was established initially. In the pro-

posed method, Link Strength is a measure of degree

of security and is a factor of number of common keys.

Its value varies for direct and indirect communication.

Security gets maximized if the number of common

keys increases.

Although there exists direct path for a set of L2

nodes, depending on the type of data, situation, topol-

ogy and application, encrypted data is communicated

in an indirect way. To ensure enhanced security, data

is routed via L1, since L1 has more keys. If the

number of common keys are more, it becomes dif-

ﬁcult for an intruder to decrypt all the common keys.

The value of Link Strength is computed in both the

KCSR: KEYMATCHES CONSTRAINED SECURE ROUTING IN HETEROGENEOUS WIRELESS SENSOR

NETWORKS

Table 2: KCSR Algorithm: Path Establishment.

Path Establishment()

for i = 0 to n

dst ← Neigh[i]

src ← presentnode()

for j = 0 to n

lk1

or n

lk2

Exch[ j] ←LK[1][ j]

j ← j+ 1

end for

i ← i+ 1

end for

for i = 0 to n

lk1

or n

lk2

for j = 0 to n

lk1

or n

lk2

if LK1[1][ j]Exch[i] or LK2[1][ j]Exch[i]

then

← DC

+ 1

else

IDC

← DC

[i] + DC

[ j]

end if

KeyDC

[i] ← LK1[2][ j]orLK2[2][ j]

j ← j+ 1

i ← i+ 1

end for

phase. After the direct communication phase, the

number of common keys to establish communication

and to route the data is increased. These values are

used in computation of threshold Link Strength and

are called as threshold keys. The probability of hav-

ing common keys for nodes communicating via L1 is

higher, when the common keys required for commu-

nication is not greater than threshold keys. The path

thus selected (direct or indirect) would provide more

resilience against compromise and active attacks.

Each node of the network explores the available

resources in its vicinity, before getting exposed to any

of the phases in the algorithm. Initially, before the de-

ployment of nodes a global pool of keys have to be

generated. This is done by using a random function,

the seed value has to be chosen so that each value

is unique. The size of global key chosen must be

much higher than local keys deployed in each node

>>n

lk1

>>n

lk2

After the global pool has been generated, random

selection of keys and key identiﬁers from the pool are

stored in the correspondingnode. The node is then de-

ployed in a grid location. The random selected keys

should not exceed n

lk2

. Randomness in the selection

process determines a probability of match, which lies

between 1 and 0. Suitable encryption and decryption

algorithm, have to be implemented to ensure that the

global key pool is resilient to any attack. The key pool

may be dropped after deployment of nodes.

The proposed KCSR algorithm uses important fea-

tures like unbalanced key distribution and predeploy-

ment of keys. The three distinct stages of the algo-

rithm are:

Table 3: KCSR Algorithm: Selection of Path Phase.

Path Selection Phase()

j ← 0

for i = 0 to n do

if DC

< IDC

then

dst ← L2Neigh[ j]

src ← presentnode()

else

dst ← Neigh[ j]

src ← presentnode()

end if

for i = 0 to N do

if DC

< L

or IDC

< L

then

Link between node j and i is not se-

cure

if DC

= L

or IDC

= L

then

Link between node j and i is

moderately secure

else

Link between node j and i is very

secure

end if

j ← j+ 1

i ← i+ 1

end for

(i) Direct Path Establishment Phase.

(ii) Indirect Path Establishment Phase.

(iii) Path Selection Phase.

(i) Direct Path Establishment Phase

Every node in the network sends a HELLO packet

to all the adjacent nodes. The nodes in the neigh-

borhood respond to the source by sending an ACK.

ACK contains corresponding node ID and its grid

positions. This information gets updated by the

source node. Every node maintains a neighbor table,

which includes various routing information. Two

essential ﬁelds are the next hop and matched keys,

which are widely used by the KCSR algorithm for

secure routing. The unique key identiﬁers stored in

the local key pool are broadcasted to the neighboring

nodes. The recipient node veriﬁes the set of key

identiﬁers with its own set of key identiﬁers. The

path establishment phase is illustrated in Table 2.

(ii) Indirect Path Establishment Phase

In case the direct path establishment fails due to lack

of shared keys, the process of searching indirect path

is initiated. Most of such failed nodes are usually

observed to be L2 nodes, as the probability of a match

is much lower when compared to L1 nodes. L2 nodes

desiring to communicate, but having no common key

sends their key identiﬁers to their neighboring L1

nodes. L1 nodes check the sets of identiﬁers sent

with its own set. The common key identiﬁer is sent

ICEIS 2011 - 13th International Conference on Enterprise Information Systems

as a response indicating that it can play the role of a

router/gateway to communicate between requesting

L2 nodes, thus establishing an indirect link.

Owing to the fact that L1 nodes have more keys

deployed in them, this path assures more security.

Counters are set up at each node to keep track of

the number of common key matches obtained. This

phase may be used repetitively to ﬁnd secure path

between two nodes, which have low Link Strength.

(iii) Path Selection Phase

This phase is responsible for choosing the right path

between a given source and destination node. The

path chosen should have higher Link Strength and

ensure secure communication. Based on this value,

different links in the network are categorized as low,

moderate and high secure paths. Depending on the

requirements, selection of path is done and the data is

routed accordingly. Path Selection Phase allows data

to be routed at different levels of security or at the

same level of security in the network for a given ap-

plication. Path chosen once at a particular threshold

does not imply that selection should always be made

for the same threshold. Switching to different thresh-

olds is also permissible making all nodes participate

in the network. The path selection phase is given in

Table 3.

5.3 An Example

In the proposed scheme, the steps followed to select

the path are as follows:

(i) All the nodes during the direct path establishment

are ﬁrst identiﬁed and the value of Link Strength

is determined.

(ii) Link Strength is calculated for nodes communi-

cating in the indirect path.

In the ﬁrst stage, direct communication is established

if there exists one or more common keys(nodes are

not communicating via L2). The constraint for es-

tablishing direct communication is atleast 1. At the

last stage, after the direct path phase, we alter the

constraint for direct communication by changing the

common keys to be greater than 1, 2, 3 and so on. The

path is selected by comparing the old and new val-

ues of Link Strength and selecting the one which has

higher value. This process would assure resilience to

the network against node compromise and defend it-

self from the active and passive attacks. The graphs

for Link Strength for a given set of nodes vs the key

matches after the direct phase or threshold keys is

plotted and then analyzed.

Consider a network consisting of an L1 node and

two L2 nodes. If the direct path is established between

two L2 nodes the value of Link Strength depends on

the number of keys deployed in L2. If n keys are de-

ployed in L2 and all the keys are common, the maxi-

mum value of Link Strength is equal to (n/number of

links). Let us consider an indirect path to be estab-

lished inspite of a direct path. If there exists n com-

mon keys between L1 and L2, then Link Strength is

determined to be as [(n1+n2)/2]. Both the direct and

indirect path values are compared, it is observed that

the indirect path is better than a direct path. But, hav-

ing all the keys common is an ideal case.

The communication is open even if there exists a

single key match. The security of open path depends

on the number of common keys. Thus, if the threshold

for the communication increases as 1, 2, . . . so on

(common keys), then the value of Link Strength in-

creases ensuring enhanced security. Owing to the fact

that number of keys deployed in L1 is far greater than

L2, the probability of ﬁnding common keys between

L1 and L2 nodes is greater than ﬁnding common keys

between two L2 nodes. This is not true for all in-

stances. There may exist an indirect path, whose Link

Strength is low compared to direct path. In such a

case direct path is selected. Thus, based on the above

comparisons, the paths are distinguished as low, mod-

erate and high secure paths and the data is routed.

Successful active attacks allow the intruder to dis-

rupt the functioning of the network. Attackers can

masquerade the network by overhearing the messages

and cause malfunctioning in the network. If an at-

tacker compromises the node, then he can spy the

network and gains full control over it. Such cases

must be avoided and the network must ensure conﬁ-

dentiality and security. The analysis against secure

threats is dependent on Link Strength which is de-

ﬁned as a function of number of common keys. It

becomes more difﬁcult for the intruder to decrypt all

the keys that is open for communication with trusted

neighbors. Moreover,the constraint for the number of

common keys is again not disclosed. Therefore, the

intruder is not aware as to how many common keys

he needs to decrypt and the actual keys for communi-

cation. This ensures a double protected mechanism.

Therefore, security is ensured in both the ways and

proves to be more stable.

6 PERFORMANCE ANALYSIS

In order to implement the proposed Keymatches Con-

strained Secure Routing (KCSR) algorithm three mes-

sages are considered: Send message, Send Path mes-

sage and U pdate message. These messages are de-

KCSR: KEYMATCHES CONSTRAINED SECURE ROUTING IN HETEROGENEOUS WIRELESS SENSOR

NETWORKS

Table 4: Simulated values for a set of 10 nodes to determine

Link Strength.

Key matches after Link Strength(y)

direct phase (X)

0 20.14856

1 23.90492

2 26.38660

3 27.22280

4 25.21774

5 26.95550

livered to speciﬁc nodes in the network at different

phases of the algorithm. Send message is used to

build a neighbor table at every node since the algo-

rithm is executed in distributed fashion. After the ﬁrst

phase of the algorithm every node sends a Send mes-

sage updating its status based on the common key.

This updated information is further used by the al-

gorithm to establish indirect links. Send Path mes-

sage is given to the neighboring L1 nodes. Based

on the previous status information the indirect path

is established. U pdate message is used to cross ver-

ify the path chosen by a node. The next hop for the

Send packets are updated. It is used in Path Selection

Phase of the algorithm.The new Link Strength values

are calculated. The path is selected by comparing the

old and new values of Link Strength and selecting the

one which has the larger value. This process would

assure resilience to the network against node compro-

mise and defend itself from the active and passive at-

tacks. The graphs for Link Strength for a given set of

nodes versus the key matches a fter the direct phase

or threshold keys is plotted and then analyzed.

The graph is plotted for the value of Link Strength

versus key matches after the direct phase for a given

set of nodes in the network. The nature of the curve is

determined by the numerical and Mathematical anal-

ysis. The process of ﬁnding the curve of best ﬁt is

called as curve fitting. The method of least squares

is employed in our scheme for curve ﬁtting. The curve

analysis results in proper setting of number of com-

mon keys to achieve optimum security. Based on ex-

ponential behavior of the curve, as shown in Eq. 9

we can ﬁt the curves of the form y = ab

where, a, b

are the constants to be determined for the given set of

x and y points. Therefore, the given curve takes the

form,

Link Strength = ab

(10)

where, T

is number of keymatches after the direct

phase. i.e., taking natural logarithms on both sides,

Table 5: Computation of X and Y using Least Square

Method.

x=X y Y=ln y XY X

0 20.14856 3.00313 0 0

1 23.90492 3.17408 03.17408 1

2 26.38660 3.27285 06.54510 4

3 27.22280 3.30405 09.91215 9

4 25.21774 3.22754 12.91016 16

5 26.95550 3.29418 16.47090 25

0 1 2 3 4 5

Link Strength

Number of key matches after direct phase

5nodes

10nodes

15nodes

20nodes

25nodes

30nodes

Figure 4: Analysis of Link Strength for different nodes in

the network (simulation).

5 10 15 20 25

Link Strength

Number of nodes

LION

KCSR-2

Figure 5: Improvement in Link Strength vs number of

nodes.

we get

logy = loga+ xlogb (11)

u = A+ Bx (12)

where, A = log a and B = log b. Solving Eq. 11 and

Eq. 12 the normal equations that yield A and B are

∑

= nA+ B (13)

ICEIS 2011 - 13th International Conference on Enterprise Information Systems

∑

= A

∑

+ B

∑

(14)

where, u

= log y

. Consider the simulated values for

10 nodes as shown in Table 4. The zero value retains

the same value of Link Strength as in direct communi-

cation whereas, the other values shows the new Link

Strength value computed in indirect communication.

The values

∑

XY,

∑

are determined from

Table 5 by using method of least squares. Substitut-

ing the above computed values in Eq. 13 and Eq. 14,

the values of A and B are 3.095007 and 0.047513 re-

spectively. The values of a and b are 22.08740 and

1.04866 respectively using, a = e

and b = e

. The

Link Strength obtained is

Link Strength = (22.08740)(1.04866)

(15)

16 18 20 22 24

Link Strength

Number of nodes

KCSR-0

KCSR-1

KCSR-2

Figure 6: Variation in Link Strength for different key

matches in the network.

where, T

is the number of i key matches after direct

phase in which i varies from 0, 1, 2, . . . 5. Computa-

tions are done for 5, 15, 20, 25 and 30 nodes.

6.1 Simulation Setup

The simulation is performed in NS-2.31 simulator.

The topological area is considered to be 50mx50m.

The transmission range is set to 50m. A set of nodes

with 12.5 percent of the entire network being L1 is

deployed as in (Traynor et al., 2006)(Traynor et al.,

2007). The deployment is random and uniformly

distributed. L1 nodes are assumed to have more

energy and processing capabilities than L2.

6.2 Simulation Results

The graph is plotted for the value of Link Strength vs

key matches after the direct phase for a given set of

nodes in the network. The behavior of curve analysis

show that Link Strength varies exponentially with the

threshold key. The variation in Link Strength for dif-

ferent number of key matches which are also known

as threshold keys for different nodes in the network

is shown in Figure 4. The value of Link Strength

increases for different nodes in the network. When

the number of key matches increases, Link Strength

also increases, but becomes constant after three key

matches. This shows the exponential behavior of Link

Strength.

In Figure 5, the values of Link Strength for dif-

ferent nodes in the network is analysed. The two

results indicate that one is for zero key matches

(LION)(Traynor et al., 2007) and the other is for two

key matches (KCSR). An improvement of 60%-70%

on an average, exists in Link Strength value. The pro-

posed scheme yields 65% better results as compared

to other scheme. The results indicate that the path se-

lected is 65% more secure.

The results of Link Strength for a variable number

of common keys is shown in Figure 6. As the num-

ber of nodes increases, the value of Link Strength in-

creases. More nodes are selected for communication,

increasing the connectivity and making all nodes par-

ticipate in the network. The percentage increase in

the value of Link Strength by changing the threshold

from 0-1, 1-2 and 2-3 keymatches is about 30%, 7%

and 7% respectively. In other words, as the threshold

keys increase, the security increases.

7 CONCLUSIONS

In this paper,Unbalanced Distribution of Keys in Het-

erogeneous Networks is considered. Data routing in

L1 and L2 nodes are determined. Link Strength is a

factor of common keys that categorizes the paths as

low, moderate and high secure path. The proposed

Keymatches Constrained Secure Routing, KCSR al-

gorithm discovers the secure and stable path which

minimizes the effects of node compromise. Given the

value of threshold security for a particular application,

appropriate path may be chosen. Various degrees of

security is seen in the same network. Switching to

different paths during routing is permissible.

Mathematical analysis and Simulation results

proved that Link Strength vs threshold keys has an

exponential behavior. The new approach of rout-

ing provides enhanced resilience against node cap-

ture/compromise and allows us to select the required

path. The performance of KCSR algorithm are justi-

ﬁed by our extensive analysis and simulations.

KCSR: KEYMATCHES CONSTRAINED SECURE ROUTING IN HETEROGENEOUS WIRELESS SENSOR

NETWORKS

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ICEIS 2011 - 13th International Conference on Enterprise Information Systems