International Journal of Engineering Trends and Technology (IJETT) – Volume 18 Number2- Dec 2014
Cluster Based Secure Communication through
Shamir Secret Sharing Technique
1
A.B. Vasavi,2KavithaKapala
1
1,2
Final M.TechStudent,2Sr.Assistant Professor
Dept.of IT, Aditya Institute Of Technology And Management,Tekkali.,A.P
Abstract:Secure transmission of data over cluster
based wireless sensor networks is one of
interesting research issues.In this paper we are
proposing an efficient cluster based secure
transmission technique in wireless sensor
networks with authenticated Shamir key
generation protocol with data confidentiality. In
this approach we initially cluster the nodes based
on coordinates of the node and we can choose
any cluster for experimental implementation on
nodes in cluster. Our experimental result shows
more efficient results than traditional approaches.
I. INTRODUCTION
In present days wireless sensor networks
are hugely increasing networks to communicate.
In these networks there are many applications
deployed in various locations controlled by
someone and they form adhoc networks. In this
messages are easily broadcasted using routers
and mobiles devices. There are many sensors
expected to provide fast and secure
communication. Generally there are different
types of sensor nodes which form adhoc
networks and it needs group of similar types so
called as clustering. By using clustering all nodes
are accurately divided and grouped for achieving
efficiency and extend the life time of the wireless
sensor networks. [1, 4]
The clustering algorithms in wireless
sensor networks there are cluster heads which
consists of clusters. In this there are some
parameters there are number of clusters, intracluster communication, nodes types and roles,
cluster head selection and mobility[2] [3].
Coming to number of clusters that is cluster
count is the number of clusters. The groups of
cluster heads are described and the number of
ISSN: 2231-5381
clusters is usually complexparameters which
consider the efficiency of the routing protocol. In
clustering methods the communication between a
sensor and its cluster heads are considered as
single hop communication.
In communication process the sensor
nodes are limited or the cluster count is very
huge and the number of cluster heads is bounded.
In mobility let us consider the base station sensor
nodes and the cluster heads are generally very
stable clusters and provide the intra-cluster
network management. In the cluster heads are
also themselves are assumed to be mobile and the
registration of cluster for each node dynamically
change and forcing clusters to involve in time
and need to maintain continuously. The cluster
heads selection is proposed in some algorithms
can be assigned previously[5]. In homogeneous
environment the cluster heads are selected from
the hosted group of nodes and their probabilistic
or completely random way based on more
particular situations for example residential
energy and connectivity etc.[6, 8]
In algorithm complexity the time
complexity is the rate of most cluster procedures
are proposed in presents is very constant. In the
traditional protocols the complexity time has
been allowed to base on the total number of
sensors in the wireless sensor networks and
focusing[7].
Overlapping: In several methods give also
very important on the topic of node overlapping
within various clusters and either for best routing
efficient or for faster cluster generation protocol
execution or for other reasons). Many of the
traditional protocols and tried to have minimum
merging or do not provide the merging at all.
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International Journal of Engineering Trends and Technology (IJETT) – Volume 18 Number2- Dec 2014
The Sensor Network Wireless is much
assumed as very important methods for the 21st
century. The sensor electronics scaled the
ambient situations related to surrounding the
sensors and transform them in to an electrical
signal. In many WSN applications and the
deployment of sensor nodes is performed in an
ad-hoc fashion without careful planning and
engineering. An intensive research that addresses
the potential of collaboration among sensors in
data gathering and processing and in the
coordination and management of the sensing
activities were conducted. The sensor nodes are
constrained in energy supply and bandwidth.
Energy conservation is critical in
Wireless Sensor Networks. Replacing or
recharging batteries is not adoption for sensors
deployed in hostile environments. The
communication electronics in the sensor utilizes
most energy. Stability is one of the major
concerns in advancement of Wireless Sensor
Networks(WSN). A number of applications of
WSN require guaranteed sensing, coverage and
connectivity throughout its operational period.
Death of the first node might cause instability in
the network. Hence all of the sensor nodes in the
network must be alive to achieve the goal during
that period. One of the major obstacles to ensure
these phenomena is unbalanced energy
consumption rate. Numerous techniques were
proposed to improve energy consumption rate
such as clustering, the efficient routing and the
dataaggregation. In a typical WSN application,
sensor nodes are scattered in a region from where
they collect data to achieve certain goals. Data
collection may be continuous, periodic or event
based process. WSN must be very stable in some
obits applications like security monitoring and
motion tracking[8].
II. RELATED WORK
In many techniques already proposed to
increase network time span wireless sensor
networks. The clustering techniques are used in
wireless ado networks, mobile ado networks with
sensor networks. Clustering is a method is hosted
ISSN: 2231-5381
in sensor networks are set into clusters. The
sensor node is responsible for base station in the
communication in a cluster. The sensor node is
also called as cluster head and the remaining
nodes in the cluster are known as followers.
There are various clustering methods are
established for wireless sensor networks. The
techniques cannot used in wireless sensor
networks because of the moderate the need
energy efficient than mobile networks and there
are very differences in energy of the sensor
nodes[2] [9].
In previous traditional algorithms the
routing algorithm merges hierarchical routing
that is performed in greedy habitats. The method
of data packet sending from the source peers and
the destination location to the base station have
two phases such as inter cluster routing and intra
cluster routing.
In inter cluster routing the greedy method
is apt to send data packets from the cluster heads
of the destination locations to the base station. In
intra cluster routing is to used pass the packet
inside the group of the cluster until nodes are less
than the threshold. In other approach packet in
destination cluster which means the cluster head
segregates the destination cluster into sub
locations and generates the similar number of
query packet and the global node in sub location.
In another algorithm is ACE is distributed
clustering method which creates clusters into two
stages such as swapping and migration. There are
much iteration in every phase and the distance
between two successive iterations uniform
distribution. In the spawning stage the novel
clusters are generated in elective manner and as
nodes predicts to become its followers. In ACE
result in cluster creations with packets efficient is
very closure to packing. It does not consider the
energy of the nodes until the selecting cluster
heads.
Distributed algorithms are also called as
HEED [1] the residual energy of sensor nodes
which outputs in the generation of clusters by
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International Journal of Engineering Trends and Technology (IJETT) – Volume 18 Number2- Dec 2014
statistically distributing the cluster heads across
the network. It selects cluster heads according to
a hybrid parameter and which consists of primary
parameter the energy of a node and a secondary
parameter such as propinquity of a node to its
neighbors or node degree. HEED converges in 0
(1)iterations using low messaging overhead and
achieves uniform cluster head distribution across
the network. It chooses the initial percentage of
cluster heads randomly. This random choice
remains as a severe limitation of this algorithm.
Optimal energy aware clustering [2]
solves
the
balanced-clustering
problem
optimally, where k signifies the number of master
nodes that can be in the network. The algorithm
is based on the minimum weight matching. It
optimizes the sum of spatial distances between
the member sensor nodes and the master nodes in
the whole network. It effectively distributes the
network load on althea masters and reduces the
communication overhead and the energy
dissipation. However, this research work does not
consider of residual energy level while choosing
anode as the master.
A number of research attempts to improve
network stability period by various techniques
like routing, scheduling, aggregation etc.
However, in this paper we attempt to improve the
network stability period using clustering as it can
serve as a better platform for upper layer
functionality such as broadcasting, aggregation
etc. In previous approach ESRPSDC exploits the
underlying method of Energy-Efficient Level
Based Clustering Routing Protocol [5]. In our
proposal, we have incorporated the security
methods as specified in [6] [10].
III. PROPOSED WORK
We are proposing an empirical model of secure
cluster based data transmission technique with
authenticated Shamir secret sharing and IDEA
cryptographic algorithm. Initially nodes can be
clustered with K means algorithm, to group the
similar type or nearest objects based on geo
parameters of nodes, and then we can perform
ISSN: 2231-5381
cluster based secure transmission between any
nodeswithin the cluster. Data can be encrypted
with IDEA algorithm to maintain data
confidentiality along with key generated by
Shamir secret key generation algorithm.
Nodes clustering:
Nodes can be clustered based on
Euclidean distance between nodes, based on
geocodlings
of
nodes.
In
k
means
clustering,initially k number of centroids selected
from dataset and compute Euclidean distance
between k centroids and other data points, place
the data point or node which is nearest tocentroid
and continue the same process until maximum
number of iterations reached.
K Means Clustering
Step1: Select K points as initial centroids for
initial iteration
Step 2: until Termination condition is met (user
specified maximum no of iterations)
Step 3: Measure Euclidean distance data point
and centroid
Step 4: Assign each point to its closest centroid
to form K clusters
Step 5:
Recomputed the centroid within
individual clusters
Step6 .Continue steps from 2 to 5
Secure Key Generation:
A secure session key can be generated
between the required clusters based on
destination node, Shamir secret sharing one of
the efficient group protocols for generation secret
key. All users request at key generation center
with Random challenge, in turn it forwards a
secret share to the respective user .Every Group
Member forwards a random challenge (Ri) to
group manager, in turn it forward a secret share
(xi,yi),data member computes (xi, (yi XOR Ri)) and
forwards the verification share to group manager
and group manager verifies the user
authentication with reverse XOP operation with
random challenge, if it generates the
corresponding member secret share ,then member
is an authorized member
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International Journal of Engineering Trends and Technology (IJETT) – Volume 18 Number2- Dec 2014
Key generation centergenerates the
key randomly it can be treated as a0 and
generates a quadratic equation ,so generate two
constant values ,with all these parameters ,find
the points which satisfies the equation, these
points can be forwarded to users to reconstruct
the key input to construct the Lagrange’s
polynomial equation f(x).
key cannot be exchanges directly in proposed
architecture ,transmits indirectly in terms of
points to reconstruct the key,it leads to much
security because security depends on key which
is used to encrypt the data packets.
10
8
6
4
2
0
Traditional
The main objective is to divide secret key S
into pieces of data D1,…Dn
in
such a way that:
1. Aware of any k points from D can
compute the secret key k
2. Details of k-1 shares cannot determine the
secret key S
This mechanism is called (k,n) threshold scheme
or Shamir secret share technique. If
then
all users are required for reconstruction of the
secret key.
Rch ----Random_challenge
Sshare---Secret_share
Vshare----verification_share
P={p1,p2…pn}-------points for construction of
Lagrange’s equation
After generation of the secure session key
data can be transmitted through clustered nodes
by encrypting the data with IDEA cryptographic
algorithm to maintain data confidentiality
For
experimental
analysis
we
implemented in java and compare with various
factors in both traditional and proposed approach
with time complexity i.e time taken to transmit
data packets from source to destination, in
traditional approach and cluster based proposed
approach. Transmission speed varies from
traditional approach, because data packets need
not transmit through all nodes ,transmits only
through cluster based nodes. For secure
transmission of data packets between the nodes
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Proposed
Fig: Performance Evaluation
IV. CONCLUSION
We are concluding our current research work
with efficient and secure Cluster based data
transmission technique. K means clustering
algorithm groups the nodes based on geo
parameters, Clusters can be selected based on
destination node availability. A secure key can be
generated between the nodes in selected cluster,
for secure transmission and to maintain data
confidentiality, it can be encrypted with IDEA
cryptographic algorithm
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