Securing cluster based adhoc network through

IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308
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Volume: 02 Issue: 12 | Dec-2013, Available @ http://www.ijret.org 316
SECURING CLUSTER BASED ADHOC NETWORK THROUGH
BALANCED CLUSTERING WITH DISTRIBUTION AUTHORITIES OF
KEY DISTRIBUTION AND KEY MANAGEMENT USING DEPLOYMENT
KNOWLEDGE
Priyanka Manhas1
, Parminder Kaur2
1
Student, 2
Asst Prof, Department of Computer Science & Engineering, Chandigarh University (Gharuan, Mohali) India
priyankamanhas36@gmail.com, parminder.cu@gmail.com
Abstract
In this paper, we address key management in cluster-based mobile ad hoc networks (MANETs). We present a fully-distributed ID-
based multiple secrets key management scheme (IMKM). This scheme is implemented via a combination of ID-based multiple secrets
and threshold cryptography. Ensuring secure communication in an ad hoc network is extremely challenging because of the dynamic
nature of the network and the lack of centralized management. Our proposed analysis includes the effect of packet generation model,
random deployment of sensors, dynamic cluster head assignment, data compression, and energy consumption model at the sensors. a
new protocol called Equalized Cluster Head Election Routing Protocol (ECHERP), which pursues energy conservation through
balanced clustering, is proposed. Performance evaluation of ECHERP is carried out through simulation tests. We also present a novel
key predistribution scheme that uses deployment knowledge to divide deployment regions into overlapping clusters, each of which has
its own distinct key space. Through careful construction of these clusters, network resilience is improved, we focus on the management
of encryption keys in large-scale clustered WSNs. We propose a novel distributed key management scheme based on Exclusion Basis
Systems (EBS); a combinatorial formulation of the group key management problem. Initially, clusters are formed in the network and
the cluster heads are selected based on the energy cost, coverage and processing capacity. The sink assigns cluster key to every
cluster and an EBS key set to every cluster head. The EBS key set contains the pairwise keys for intra-cluster and inter-cluster
communication. During data transmission towards the sink, the data is made to pass through two phases of encryption thus ensuring
security in the network. Our results include performance evaluation in terms of security metrics in clustered WSN and a detailed
analysis of resource utilization.
Keywords: cluster, deployment knowledge, energy efficiency key predistribution, event-driven, exclusion basis systems,
hierarchical routing, ID-based cryptography, key agreement, key management, lifetime, location-aware protocols,
mobile ad hoc network, Network coding, , random deployment, Security, secret sharing, secret key distribution, sensor
networks, volatile environments, Wireless sensor networks secure group communications.
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1. INTRODUCTION
Recent literatures have sought to address the key management
issues in MANETs. AD hoc networks are subject to various
types of attacks ranging from passive eavesdropping to active
impersonation, message replay, and message distortion.
Moreover, it is difficult to deploy security mechanisms in
MANETs because of the absence of fixed infrastructure,
shared wireless medium, node mobility, limited resources of
mobile devices, bandwidth restricted and error-prone
communication links. Group key agreement (GKA) [3]-[4] is
another important challenge of key management in MANETs.
GKA protocols allow two or more parties to agree on a
common group key and exchange information among them
over an insecure channel. we propose an ID-based multiple
secrets key management (IMKM) protocol to address all the
above concerns. Our scheme is a comprehensive solution for
inter and intra-cluster key Management, including key
revocation, key update, and group key agreements. The main
focus of this work is on the lifetime analysis of randomly
deployed clustered networks. Clustered WSNs are suggested
for extending the network scalability and ease of data
processing, [1], [2]. In clustered networks, usually a
representing node, called cluster head (CH), is assigned to
each cluster. the lifetime of a randomly deployed clustered
network is modeled using a probabilistic approach. The

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probabilistic approach is motivated by the stochastic nature of
the network lifetime which is mainly due to the randomness of
the sensors deployment. Most of the protocols use clusters in
order to provide energy efficiency and to extend the network
lifetime. Each cluster first elects a node as the cluster head
(CH), and then, the nodes in every cluster send their data to
their own cluster head. The cluster head sends its data to the
base station. This data transfer can be performed in two
alternative ways. Either directly, in the case in which the
cluster head is located close to the base station, or via
intermediate cluster heads. In this paper, a novel energy
efficient protocol, named ECHERP, is proposed. ECHERP,
contrary to other existing cluster-based protocols that select a
random node or the node with the higher energy at a particular
time instance as the new cluster head, considers the current
and the estimated future residual energy of the nodes, along
with the number of rounds that can be cluster heads, in order
to maximize the network lifetime. The network is modeled as
a linear system. In this paper, we propose a novel key
predistribution scheme that makes use of region-based
deployment knowledge. Our scheme constructs a set of
clusters such that each cluster contains a small number of
deployment regions, all of which are neighbors of each other.
Furthermore, every pair of neighboring deployment regions
belongs to at least one cluster. Each cluster has its own distinct
key space, and it is from these cluster key spaces that nodes
are assigned their keys. In this manner, we guarantee that
nodes in neighboring regions share a key with a given overlap
probability, while nodes in non neighboring regions do not
share any keys. We make use of the result developed in [18],
which states that under certain conditions, maximizing the key
pool size used by the scheme also maximizes its resilience.
Our clustering scheme is designed to maximize the overall key
pool size, which results in greatly improved network resilience
without compromising network connectivity or
communications overhead. Confidentiality, authenticity,
availability, and integrity are typical security goals for WSNs.
Indeed, securing the network for applications, such as border
control and tactical defense operations is among the main
design objectives. An EBS consists of several subsets of the
member set collection. In the EBS, every subset is analogous
to a particular key and the nodes which possess the key
become the element of the subset.
The remainder of the paper is organized as follows: section 2
provide an (fully-distributed ID-based multiple secrets key
management scheme) IMKM protocol. in section 3,we
introduce proposed protocol that models the network as a
linear system in order to select the cluster head that minimizes
the energy consumption in the cluster, while in section 4,we
present our basic predistribution scheme with EBS, In the
EBS, every subset is analogous to a particular key and the
nodes which possess the key become the element of the
subset. Finally, we provide a conclusion with future directions
in section 5.
2. IMKM (ID-BASED MULTIPLE SECRETS KEY
MANAGEMENT SCHEME)
PROTOCLOS: This section presents our IMKM protocol. It
consists of five phases: network initialization, key revocation,
multiple secrets key update, member joining and eviction, and
group key generation.
Fig 1 IMKM Protocol Phases
2.1 Network Initialization
Network initialization comprise in 3 steps. these are shown as
below:
Fig 2 network initialization steps
The description of network initialization steps that is
generation of pairing parameters and key initiation followed
by generation of pair-wise keys with verifiable secret sharing
is We consider basic operations in the scenario where there is
an offline PKG center. These basic operations consist of
system setup and private key extraction. system setup and key
extraction is done in generation of pairing parameters and key
initiation. A pair-wise key agreement protocol allows two
parties to establish their session keys and use the keys to
encrypt the communications between them. McCullagh and
Barreto [31] proposed a two-party authenticated identity-based
key agreement using bilinear pairings. In order to provide
perfect forward secrecy, we modified their scheme to generate
IMKM
SCHEME
NETWORK
INITIALIZATION
KEY REVOCATION
MULTIPLE
SECRETS KEY
UPDATE
MEMBER
JOINING AND
EVICTION
GROUPKEY
GENERATION
Generation
of Pairing
Parameters
and Key
Initiation
Generation
of Pair-wise
Keys
Verifiable
Secret
Sharing

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our pair-wise keys. pair-wise key agreement protocol satisfies
all the following security properties [31]: implicit key
authentication, known session key security, no key-
compromise impersonation, perfect forward secrecy, no
unknown key-share and no key control. Therefore, it can be
securely employed in MANETs. This is done in generation of
pair-wise keys. And in verifiable secret sharing, In order to
establish a ( , ) threshold sharing, we require that all cluster
heads (CHs) participate in the construction of the master secret
key, and that the role of distributed PKG (D-PKG) be assigned
to the CHs of the network
2.2 Key Revocation
The key revocation scheme [34]-[36] is comprised of three
sub-processes: misbehavior notification, revocation generation
and revocation verification.
Fig 3 key revocation steps
2.2.1 Misbehavior Notification
Upon detection of ’s misbehavior, generates an
accusation, { , } , , against and securely transmits
it to , where is a time stamp used to withstand
message replay attacks and , is the pair-wise key of
and (1 ≤ ≤ , ∕= , ). To prevent from
temporarily behaving normally (artificially), the accusation
should not be sent to that node.
2.2.2 Revocation Generation
Upon receipt of an accusation from , the message will
simply be dropped if the accuser itself has been revoked. The
accused is diagnosed as compromised when the number
of accusations against it reaches a predefined revocation
threshold, . In IMKM, generation of a revocation requires the
joint effort of CHs. We assume the D-PKG with the largest
ID acts as the role of revocation leader. Each of the
unrevoked , having the smallest IDs, generates a partial
revocation, = 1( ) , and sends it to the revocation
leader securely using the pair-wise key. The revocation leader
checks whether the equation 2( ) = 1( )
holds. If the partial revocation is not valid, the revocation
leader considers to be misbehaving and issues a signed
accusation against it. The revocation leader can construct a
complete revocation from these partials using Lagrange
interpolation. A complete revocation is derived as follows:
= Σ ∈ (0) = 1( ) . The revocation leader then
floods < , > throughout the network to inform others
that has been compromised.
2.2.3 Revocation Verification
Upon receipt of , each cluster head verifies it by
checking whether the equation 2( ) = 1( )
holds, where can be computed using the public keys of
the shares of any unrevoked CHs. If the equation holds, this
means that ′ has been correctly accumulated from all
other −1 unrevoked CHs. The cluster head then records in
its key revocation list (KRL) and declines to interact with it
thereafter.
2.2.4 Multiple Secrets Key Update Scheme
In IMKM, all CHs’ private keys, , will last for the entire
lifetime of the network, while the share keys, , used to
enable key revocation and key update, are refreshed
periodically for predefined regular phases, using a multiple
secrets key update scheme. Alternatively, they may be
refreshed in key eviction process when the number of
revocation CHs has reached a prescribed update threshold, .
In this way, key update is quite simple and efficient because
there is no need to exchange and sign any messages between
the CHs.
2.3 Key Joining
In this section we show how to add a new cluster head, ,
to the ad hoc network backbone.
2.4 Key Eviction
A cluster head eviction can happen as a result of
unavailability, communication failure or for security reasons,
such as revoked node. If the eviction of a CH is not considered
a security vulnerability, such as a power failure, then no action
is required. By using distributed key management schemes,
each CH can easily add or update its share key in a secure and
efficient manner, thus greatly reducing communication and
computation costs.
2.5 Group Key Agreement Protocol
In this section, we present an efficient, one round
authenticated group key agreement protocol (AGKA) for
cluster-based MANETs. We may use the multiple secrets key
update scheme.
Misbehavior
Notification
Revocation
Generation
Revocation
Verification

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2.6 Securing D-PKGs against DoS attacks
It has been suggested that wireless networks are highly
susceptible to malicious denial-of-service (DoS) attacks,
which prevent legitimate users from accessing the network.
One such target is the key management service. Proper
authentication can prevent injected messages from being
accepted by the network. The key eviction procedure in our
scheme is expected to be initiated very rarely. Therefore, if a
malicious node were to frequently initiate this procedure in a
short time window, then such an abnormality would be
detected very easily. The legitimate nodes would then record
the malicious node’s ID in their key revocation lists and
thereafter decline to interact with it.
3. PROPOSED PROTOCOL THAT MODELS THE
NETWORK AS A LINEAR SYSTEM
The main characteristic of ECHERP is the head selection
process. In this protocol, in order to elect a cluster head, the
routing information and the energy spent in the network are
formulated as a linear system, the solution of which is
computed using the Gaussian elimination algorithm.
Therefore, cluster heads are elected as the nodes that minimize
the total energy consumption in the cluster. In most of the
protocols proposed so far, the node with the highest residual
energy in a cluster is elected as the cluster head. This selection
may lead to inefficiencies, as can be seen by the following
example. Let us assume that node x in Figure has higher
residual energy than the other nodes belonging to the same
cluster. Then, this node is elected as the new cluster head.
However, this forces the rest of the nodes to send data in the
opposite direction to the base station, resulting in higher
energy consumption. In ECHERP, the BS is assumed to have
unlimited energy residues and communication power. It is also
assumed that the BS is located at a fixed position, either inside
or away from the sensor field. The longer the distance between
the BS and the center of the sensor field, the higher the energy
expenditure for every node transmitting to the BS. All the
network nodes, which are assumed to be located ithin the
sensor field, are dynamically grouped into clusters. One of the
nodes within every cluster is elected to be the cluster head of
this cluster. Therefore, the number of cluster heads is equal to
the number of clusters. The cluster heads, which are located
close enough to the network base station, are referred to as the
first level cluster heads. These cluster heads are capable of
direct transmission to the base station with reasonable energy
expenditure. The cluster heads that are located at more distant
positions from the base station are considered as second-,
third-, etc. level cluster heads. These cluster heads transmit
data to the upper level cluster heads. Moreover, in order to
achieve balanced energy consumption and extend the
network’s lifetime, the election of the cluster heads is
performed in turns.
Fig 4 WSN network model
Obviously, this is not an energy efficient process, and it can be
avoided by selecting cluster heads in a more energy efficient
manner. This is pursued by the proposed protocol.
In order to evaluate the performance of ECHERP simulations,
over 50 different 100 m × 100 m network topologies were
performed. The network architecture considered is the
following:
• A fixed base station is located away from the sensor
field.
• The sensor nodes are energy constrained with
uniform initial energy allocation.
• Each node senses the environment at a fixed rate and
always has data to send to the base station (data are
sent if an event occurs).
• The sensor nodes are assumed to be immobile.
However, the protocol can also support node
mobility.
• The network is homogeneous, and all the nodes are
equivalent, i.e., they have the same computing and
communication capacity.
• The network is location unaware, i.e., the physical
location of nodes is not known in advance.
• The transmitter can adjust its amplifier power based
on the transmission distance.

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Fig 5 Network life time versus average energy dissipation
4. BASIC PREDISTRIBUTION SCHEME WITH
EBS
There are 8 basic key distribution schemes that is described in
tabular form with its different steps and complete description
in front of one another. The basic 8 key pre-distribution
scheme is RANDOM KEY PRE-DISTRIBUTION SCHEME,
Q-COMPOSITE RANDOM KEY DISTRIBUTION
SCHEMES, MULTIPATH KEY REINFORCEMENT
SCHEME, Random pair wise key scheme, Polynomial pool-
based key predistribution. Random subset key predistribution,
Polynomial pool-based key predistribution, Random subset
key predistribution, Grid based key predistribution, Hypercube
key distribution scheme.
1. Random key predistribution
scheme (proposed by Echenauer
and Gligor). This is basic
scheme[1].
Key predistribution stage
Shared key discovery stage
Path key establishment stage
Key revocation
Anayses of basic scheme
Large key pool of S keys and their
identifiers are generated. From this key
pool, k keys are randomly drawn and pre-
distributed in to each node’s keyring,
including the identifiers of all those keys
When the keys are initialized with keys,
they are deployed in the respective places
where they are needed. After deployment
each node tries to discover its neighbors
with which it share common keys.
A link exist between two nodes only if they
share a key, but the path key establishment
stage facilitates provision of the link
between two nodes when they do not share a
common key.
Key revocation is conducted by the
controller node, when a node is revoked
then all the keys in that particular node
keyring have to be deleted from the
network.
Assume probability of a common key
existing between two nodes in the network
is p, and size of the network is n. then
degree of the node is derivable using both p
and n.
2. Q composite random key
predistribution scheme[2]
(proposed by Chan,perrigand
song)
As in basic scheme 2 nodes
share a unique key for
establishing a secure
communication link and in Q
composite random key
predistribution scheme does this
by requiring that two nodes have
atleast q common keys to set up
a alink.
As amount of key overlap between two
nodes is increased, it become harder for an
adversary to break their communication
link. To maintain the probability that two
nodes establish a link with q common keys,
it is necessary to reduce the size of key pool.
3. Multipath key reinforcement It offers good security with To solve the problem, the communication

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scheme[2-10] additional a communication
overhead for use where security
is more of a concern than
bandwidth or power drain.
The links formed between nodes
after the key discovery phase in
the basic scheme are not totally
secure due to the random
selection of keys from the key
pool allowing nodes in a
network to share some of the
same keys and thereby possibly
threaten multiple nodes when
only one is compromised.
key between the nodes must be updated
when one is compromised once a secure link
is formed.
This should not done for already established
link, but should be coordinate during
multiple independent paths for greater
security.
4. Random pairwise key
scheme[11]
Compared to the Q-composite
scheme and multipath scheme,
the random pair wise scheme
offers best security features in its
resilience to node capture .
The drawback of the random pair wise key
scheme is lack of scalability.
5. Polynomial pool-based key
predistribution[3] (proposed by
liu and Ning)
Any two sensors can definitely
establish a pair wise key when
there are no compromised
sensors.
Even with some nodes
compromised, the others in the
network can still establish pair
wise keys. A node van find the
common keys to determine
whether or not it can establish a
pair wise key and thereby help
reduce communication
overhead.
Polynomial pool based key pre-
distribution using random subsets offers
greater security and flexibility when
compared to other schemes until a
certain number of compromised nodes
assume 65% has been reached at which
point at any scheme would prove
ineffective.
Advantages: Sensors can be added
dynamically without consulting the
already deployed sensors while
dynamically deploying nodes in random
pair wise demands that the server has
pre designated un assigned space for
additional nodes which may never be
deployed.
6. Random subset key
predistribution[1-3]
This is an extension of the
polynomial pool based scheme
using a random subset key
assignment and the basic
scheme.
In this the pair wise keys
generated by each node are
unique and based upon each
node’s ID.
Random subset scheme works
similar to the polynomial pool
In key predistribution stage, the setup server
generates a set F of S-bivariate t-degree
polynomial and then initialize each node
with a subset of s polynomials from F.
In key discovery stage, each node attempt to
determine the nodes with which they share a
common key by employing the real time
discovery techniques information is not
preloaded in the nodes prior to the
deployment
.
In path key establishment phase, a source
node sends a message to its intermediate

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base4d scheme in three stages of
key establishment. If no more
than t shares of the same
polynomial have been disclosed,
it is very difficult to attack the
communication between two
nodes
nodes seeking to establish a connection with
a destination node and if an intermediate
node can share a common key with both the
source and destination node, then the
communication path is formed between the
two.
7. Grid based key
predistribution[3]
A polynomial pool based
scheme using a grid based key
assignment offers all the
attractive properties of the
polynomial pool based key
predistribution and guarantees
that two sensor can establish a
pair wise key, when there are no
compromised nodes and the
nodes can communicate with
each other.
Even if some nodes are captured , there will
still be a great chance for key establishment
between uncompromised nodes using this
approach, which also reduce network
communication overhead.
8. Hypercube keydistribution
scheme[19]
Guarantees that any two nodes
in the network can establish a
pair wise key if there are no
compromised nodes are present
as long as the two nodes can
communicate.
If two nodes cannot share the common
polynomial, then they have to use the path
discovery method to compute an indirect
key. It include: dynamic path discovery,
performance and overhead for the
hypercube scheme, security evaluation for
hypercube scheme.
Fig 6 EBS matrix
THESE are all key predistribution schemes and in EBS it can
be stated as:
4.1 EBS Construction
An EBS consists of several subsets of the member set
collection. In the EBS, every subset isanalogous to a particular
key and the nodes which possess the key become the element
of the subset.The dimension of the EBS is represented by (N,
K, M) and it depicts a condition of a N membered secure
group with numbering from 1 to N and a separate key is
maintained for every subset by the key server. In EBS, if there
exists a subset Ai, then every member of this subset will have
knowledge about the key Ki. In EMS, there are M elements
for every t € [1, N] and its union is equal to [1, N] – {t}.
Hence, any member t can be ejected by the key server. Then
re-keying is performed to enable every member to know the
replacement keys for the K keys. To perform this, the M
messages are multicast after encrypting them with the keys
which correspond to the M elements, which has a union equal
to [1, N] – {t}. To restrict decipherability to selected
M1 M2 M3 M4 M5 M6 M7 M8 M9
K1 0 0 0 0 1 1 1 1 1
K2 0 1 1 1 0 0 0 1 1
K3 1 0 1 1 0 1 1 0 1
K4 1 1 0 1 1 0 1 0 0
K5 1 1 1 0 1 1 0 1 0

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members, encryption of every key is performed by its
predecessor.A canonical enumeration technique is made use
of, for the construction of EBS subsets. In theformation of
subset of K objects out of K + M object set, every feasible
method is taken into consideration. Matrix A is formed in
order to develop a bit string sequence in its canonical (K, M),
in which the K and M are already known, C (K + M, K)
columns indicate the successive bit strings of which has a
length of K+M objects, where K ones are present in each. For
EBS (N, K, M), “A” is known as the canonical matrix. For
instance, the canonical matrix can be shown as:
1) No. of columns is equal to no. of nodes in the cluster.
2) No. of rows is equal to no. of keys used to manage
these nodes.
3) Total no. of keys K+M.
4) Out of Size of EBS depend upon no. of nodes and no.
of keys used to manage these nodes.
5) k+m keys,every sensor node know a distinct set of K
keys that is set of keys known to one of sensor nodes
can not be exactly identical to the set known to other
sensor nodes.
6) No. of nodes = (K+M)!/K!M!
7) Value of K and M adjusted according to network and
its security requirements
CONCLUSIONS WITH FUTURE DIRECTIONS
We have proposed a secure, efficient, and scalable distributed
ID-based multiple secrets key management scheme (IMKM)
for cluster-based mobile ad hoc networks. In order to address
the highly dynamic topologies and varying link qualities of ad
hoc networks, the master secret key is generated and
distributed by all clusterheads. As a result, not only are central
instances avoided, which constitute single points of attack and
failure, but this also leads to more autonomous and flexible
key update methods. According to our protocol analysis, we
believe that the proposed IMKM scheme improves on the
security and performance of previously proposed key
management protocols. After the key distribution, secure
channel is established between the nodes and the cluster head.
During the data transmission from the cluster members to the
sink, the data passes two phases. In the first phase the data is
encrypted and transmitted to the cluster head. In the second
phase, the data is encrypted by another key by the cluster head
and then transmitted to the sink. Thus this technique allows
inter cluster as well as intra cluster communication in a very
efficient manner with high security. The sink then provides the
cluster head with the cluster key and the EBS key set required
for the communication between the nodes. These keys are
distributed to the nodes by the cluster head prior
communication. ECHERP, an energy efficient protocol for
WSNs, was presented. ECHERP considers the current and the
estimated future residual energy of the nodes, along with the
number of rounds that can be cluster heads in order to
maximize the network lifetime. In future work, ECHERP can
be further enhanced by taking into consideration metrics
related to QoS and time constraints. We have presented a new
key predistribution scheme that uses region-based deployment
knowledge to assign keys to sensor nodes. Our simulation
results show a significant improvement in resilience over
existing schemes using region-based deployment knowledge.
Future work can be done to characterize the effects of
localized network attacks, as well as the effects of different
deployment distributions.
REFERENCES
[1] J.M. Kahn, R.H. Katz, and K.S.J. Pister, “Next
Century Challenges: Mobile Networking for Smart
Dust,” Proc. Ann. ACM/IEEE MobiCom, pp. 483-
492, 1999.
[2] G.J. Pottie and W.J. Kaiser, “Wireless Integrated
Network Sensors,” Comm. ACM, vol. 43, no. 5, pp.
551-558, 2000.
[3] L. Eschenauer and V. Gligor, “A Key Management
Scheme for Distributed Sensor Networks,” Proc.
Ninth ACM Conf. Computer and Comm. Security,
pp. 41-47, Nov. 2002.
[4] H. Chan, A. Perrig, and D. Song, “Random Key
Predistribution Schemes for Sensor Networks,” Proc.
IEEE Symp Security and Privacy, pp. 197-213,
May 2003.
[5] A.K. Das, “An Identity-Based Random Key Pre-
Distribution Scheme for Direct Key Establishment to
Prevent Attacks in Wireless Sensor Networks,” Int’l
J. Network Security, vol. 6, no. 2, pp. 134-144, 2008
[6] J. Lee and D.R. Stinson, “Deterministic Key
Predistribution Schemes for Distributed Sensor
Networks,” Proc. Ann. Symp. Selected Areas in
Cryptography, pp. 294-307, 2004
[7] S.A. C¸ amtepe and B. Yener, “Combinatorial Design
of Key Distribution Mechanisms for Wireless Sensor
Networks,” Proc. Ninth European Symp. Research
Computer Security (ESORICS), pp. 293-308, 2004
[8] J. Lee and D.R. Stinson, “A Combinatorial Approach
to Key Predistribution for Distributed Sensor
Networks,” Proc. IEEE Wireless Comm. and
Networking Conf., 2005. CD-ROM, paper PHY53-
06.
[9] W. Du, J. Deng, Y.S. Han, P.K. Varshney, J. Katz,
and A. Khalili, “A Pairwise Key Pre-Distribution
Scheme for Wireless Sensor Networks,” ACM Trans.
Information and System Security (TISSEC), vol. 8,
no. 2, pp. 228-258, May 2005.
[10] I.F. Akyildiz, W. Su, Y. Sankarasubramaniam, and E.
Cayirci, “Wireless Sensor Networks: A Survey,”
Computer Networks, vol. 38, no. 4, pp. 393-422,
Mar. 2002.
[11] S. Tilak, N.B. Abu-Ghazaleh, and W. Heinzelman,
“A Taxonomy of Wireless Microsensor Network
Models,” ACM Mobile Computing and Comm. Rev.,
vol. 6, no. 2, pp. 1-8, 2002

__________________________________________________________________________________________
[12] H. Yang et al., “Security in Mobile Ad-Hoc Wireless
Networks: Challenges and Solutions,” IEEE Wireless
Comm. Magazine, vol. 11, no. 1, pp. 38-47, Feb.
2004.
[13] L. Zhou and Z.J. Haas, “Securing Ad Hoc
Networks,” IEEE Networks, vol. 13, no. 6, pp. 24-30,
Nov./Dec. 1999.
[14] D. Carman, P. Kruus, and B. Matt, “Constraints and
Approaches for Distributed Sensor Networks
Security,” Technical Report 00- 010, NAI Labs, Sept.
2000.
[15] G. Jolly, M. Kuscu, P. Kokate, and M. Younis, “A
Low-Energy Key Management Protocol for Wireless
Sensor Networks,” Proc. Eighth IEEE Symp
Computers and Comm. (ISCC ’03), June 2003.
[16] TinySec, http://www.cs.berkeley.edu/nks/tinysec/,
2006.
[17] L. Eschenauer and V. Gligor, “A Key Management
Scheme for Distributed Sensor Networks,” Proc.
Ninth ACM Conf. Computing and Comm. Security
(CCS ’02), Nov. 2002.
[18] H. Chan, A. Perrig, and D. Song, “Random Key
Predistribution Schemes for Sensor Networks” Proc
IEEE Symp. Security and Privacy, May 2003.
[19] G. Gupta and M. Younis, “Load-Balanced Clustering
in Wireless Sensor Networks,” Proc. Int’l Conf.
Comm. (ICC ’03), May 2003.
[20] O. Younis and S. Fahmy, “HEED: A Hybrid, Energy-
Efficient, Distributed Clustering Approach for Ad
Hoc Sensor Networks,” IEEE Trans. Mobile
Computing, vol. 3, no. 4, pp. 366-379, Oct.-
Dec.2004.
[21] K. Langendoen and N. Reijers, “Distributed
Localization in Wireless Sensor Networks: A
Quantitative Comparison,” Computer Networks, vol.
43, no. 4, pp. 499-518, Nov. 2003.
[22] A. Youssef, A. Agrawala, and M. Younis, “Accurate
Anchor-Free Localization in Wireless Sensor
Networks,” Proc First IEEE Workshop Information
Assurance in Wireless Sensor Networks (WSNIA
’05), Apr. 2005
[23] Lina M. Pestana Leão de Brito and Laura M.
Rodríguez Peralta, “An Analysis of Localization
Problems and Solutions in Wireless Sensor
Networks”, Polytechnical Studies Review, 2008, Vol
VI, ISSN: 1645-9911.
[24] Huang Lee and Hamid Aghajan, “Collaborative Self-
Localization Techniques for Wireless Image Sensor
Networks”, In Proc. of Asilomar Conf. on Signals,
Systems and Computers, Oct. 2005.
[25] D.Saravanan , D.Rajalakshmi and D.Maheswari
“DYCRASEN: A Dynamic Cryptographic
AsymmetricKey Management for Sensor Network
using Hash Function”, International Journal of
Computer Applications (0975 – 8887) Volume 18–
No.8, March 2011
[26] Yoon-Su Jeong, and Sang-Ho Lee “Secure Key
Management Protocol in the Wireless Sensor
Network”, International Journal of Information
Processing Systems, Vol.2, No.1, March 2006.
[27] Mohammed A. Abuhelaleh and Khaled M. Elleithy
“SECURITY IN WIRELESS SENSOR
NETWORKS: KEY MANAGEMENT MODULE IN
SOOAWSN”, International Journal of Network
Security & Its Applications (IJNSA), Vol.2, No.4,
October 2010.
[28] P. F. Oliveira, R. A. Costa, and J. Barros, “Mobile
secret key distribution with network coding,”
presented at the Int. Conf. Security Cryptography,
Jul. 2007.
[29] P. F. Oliveira and J. Barros, “Network coding
protocols for secret key distribution,” in Proc. Int
Symp Information Security, Nov. 2007, pp. 1718–
1733
[30] W. Du, J. Deng, Y. S. Han, P. K. Varshney, J. Katz,
and A. Khalili, “A pairwise key predistribution
scheme for wireless sensor networks,” ACM Trans.
Inf. Syst. Secur., vol. 8, no. 2, pp. 228–258, 2005.
[31] D. Malan, M. Welsh, and M. Smith, “A public-key
infrastructure for key distribution in tinyos based on
elliptic curve cryptography,” presented at the 1st
IEEE Int. Conf. Sensor and Ad Hoc Communications
and Networks, Santa Clara, CA, Oct. 2004. [Online].
Available: citeseer. ist.psu.edu/malan
04publickey.html.

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