Abstract—The of clone in WSN is a tedious job.

Abstract—The wireless sensor network has become an important
area and it is widely applied to military civilian application.
There are easily prone to security attack because it handling
wireless media for transmission. Detection of clone in WSN is
a tedious job. In this paper further focuses on network lifetime
and improving memory management. Energy and memory both
are most valuable parameter in WSN. Efficient use of memory
is necessary. In proposed paper an energy and memory efficient
clone detection protocol is densely deployed WSN , which can
guarantee successfully clone detection and mainly satisfactory
network lifetime by efficiently distributing the traffic load across
the network.
Keywords—clone detection, energy efficiency, memory effi-
ciency,Wireless sensor networks.
I. INTRODUCTION
A wireless sensor network is typically collection of sensors
with restricted computational, memory and communication
asset. Remote sensor network contains a few number of
sensor nodes which are distributed in an objective identifying
environment inside of its neighborhood, gathers the information
and processes it. Mobile nodes are comprised of basic
processor, application particular sensors, wireless transceiver
and low battery. Data aggregation is utilized because of limited
amount of power in sensor nodes and to decrease transmission
overhead. A wireless sensor network is used for different kinds
of applications e.g. Health care, Fire Detection, Air pollution
etc Compromised nodes are the nodes which are under the
control of attacker. Attacker selects any node for performing
attack. When attack happens on specific selected node, then
that node is completely under the control of attacker. Through
the compromised node, attacker can alter/modify the data or
drop the data which is routed via it. Detection of compromised
nodes is very important issue as the sensitive data may get lost
while transmission.
A. Existing System
In the existing system, energy efficient clone detection and
location-aware clone detection is introduced. Given protocol
is deployed in the wireless sensor network and it provides
clone attack detection in wireless sensor network as well as
maintaining and enhancing networks lifetime. It distributes
traffic load among the network. The existing system gathers
location information of all sensor node and it verifies legitimate
sensor node based on the randomly selected sensor as a witness
in ring area. System transfer data to sink via witness selected in
ring area. Suppose one of the sensors in ring area is shut down
then data transmission in a wireless sensor node is disturbed.
II. REVIEW OF LITERATURE
The paper offered by the Zhongming Zheng, Anfeng Liu
Jan 2015 proposed ERCD (Energy Efficient Ring Based Clone
Detection) protocol. Due to the suggested system, the data
can be lead extra proficiently. The ERCD protocol required
some additional data buffer comparing with RED and P-MPC
protocol. Only the ring structure is considered in this paper.
The performance of the ERCD protocol evaluates in terms
of clone detection probability, power consumption, network
lifetime and data buffer capacity. Extensive simulation results
demonstrate that in the system clone detection probability and
network lifetime with reasonable data buffer capacity. By using
ERCD protocol energy consumption of sensor close to the sink
has a lower traffic of witness selection.1
In this paper offered Zhongming Zheng, Anfeng Liu in 2013,
Witness message stored in the buffer over n/w and ERCD is not
considering memory management. ERCD protocol achieves
the high probability of clone detection.Less energy consumption
as compared to LSM (Line-select Multicast protocol. It
Improves the lifetime of N/w2. Cesare Alippi, Giuseppe
Anastasi, Mario Di Francesco, and Manuel Roveri Feb 2011.
In this paper authors planned an adaptive sampling algorithm
that guesses online the ideal sampling frequencies for sensors.
This method, which needs the scheme of adaptive measurement
systems, reduces the energy eating of the sensors and,
incidentally, that of the radio though preserving a very great
precision of gathered data. It can accomplish parallel to a fixedrate
system where the sampling frequency is well-known in
advance. This method outcomes in a matching energy saving
of together the sensor and the radio.
Decision intensely rests on the exact sensor, whose power
eating is knowingly superior to that of the radio 3. A
Trigger Identification Service for Defending Reactive Jammers
in WSN was introduced by Ying Xuan, Yilin Shen, Nam P.
Nguyen, and My T. Thai.The benefit of using this service
is its low identification latency4. It provides a complete
trigger identification service framework for unreliable WSN.
It provides a complete trigger identification service framework
for unreliable WSN and enhances the robustness of
n/w. Rongxing Lu, Xiaodong Lin came up with BECAN: A
Bandwidth-Efficient Cooperative Authentication Scheme for
Filtering Injected False Data in Wireless Sensor Networks5.
It achieves high routing filtering probability and high reliability.
It is simple, effective and can be applied to other fast and
distributed authentication scenario for example mesh.
Distributed Clone Attacks are happening in Wireless Sensor
Networks which causes the security threat in the system6.This
paper introduces RED which has better detection
probability and converges faster than LSM for all practical
values of the N/w parameter. A new approach for Randomized
Countermeasure Against Parasitic Adversaries in Wireless Sensor
Networks which was introduced by Panagiotis Papadimitratos,
Jun Luo, and Jean-Pierre Hubaux7. It has RKRGossiCrypt
scheme to ensure WSN data confidentiality in a
wide range of setting. This scheme ensures the WSN data confidentiality
with the simple and low-cost mechanism. Detecting
node replication attacks in Sensor Networks is challenging
task8.The local voting system in WSN is used for detecting
distributed node replication. Randomized Dispersive Routes
for Secure Data Collection in Wireless Sensor Networks is
used9.This protocol provides a security as well as energy
consumption in WSN for small scale. If adversary blocks
every path from sink to the source node, this protocol does
not address this attack.
III. SYSTEM ARCHITECTURE
Fig. 1: Simulation Result.
The nodes of network are partitioned into disjoint clusters,
and every cluster has a cluster head which is known as
an aggregator. Information are intermittently gathered and
aggregated by the cluster head. In proposed system, we assume
that attack can happen on cluster member as well as data
aggregation node. Both can send false data to data aggregation
node and base station respectively. To detect the attack on data
aggregation node we use the concept clone detection. In the
proposed system, there are four modules are: node creation,
cluster head detection, send data to sink and clone detection.
Cluster head has the ability to maintain unique identification
of sensor node. Sensor data is encrypted and those data are
sent to cluster head. It uses the star topology and cluster head
work as a hub. This protocol is able to increase the efficiency
of energy in the network. The proposed system saves time and
energy than the existing system and improves the performance.
1) Node Deployment:
Randomly Generate number of sensor nodes. Those nodes
are connected through the edges. It is process to generate
given the number of sensor node as well as it assign a unique
number of identification number.
2) Cluster Formation:
The clustering process is performed in the network system;
the mobile nodes are divided into the group of clusters. The
number of clusters is generated in the sensor network.
3) Cluster Head Selection:
Aggregator selection is done by using parameters like the
highest remaining energy of the nodes. This step is performed
twice, after initial formation of clusters and for selection
of new aggregator on detecting an attack on the old aggregator.
4) Clone Detection:
The Sensor node is responsible for sensing data from the
sensor node and that sensing data is encrypted by using
Paillier homomorphic encryption algorithm. In the proposed
system, we need to generate keys and these keys are used
for encrypting sensed data as well as identity information.
Later encrypted data is sent to the cluster head. Cluster head
already maintained identity information of sensor node so
it will check given sensor is legitimate or not. The cluster
head is nothing but one kind hub in particular cluster and
star topology uses the hub for maintaining all information of
another node.
IV. SYSTEM ANALYSIS
A. Algorithm
Input: no of sensor node with cluster head.
Output: clone detection.
Process:
1. Initialize energy to each sensor node.
2. Calculate the energy of each node.
3. Compare energy and distance of all nodes.
4. Select maximum energy and minimum distance node.
5. Cluster head selection = node whose having maximum
energy and minimum distance to Base Station.
Paillier Homomorphic AlgorithmEncryption:
1. Randomly take two prime numbers p and q
2. Generate public key and private key
{PKeva, SKeva} ? keygeneration
3.EncryptdatabyusingPKeva(publickey)
Encryptdata = (M, PKeva)
Decryption:
1.DecryptdatabyusingSKeva(Secretkey)
2.Decryptdata = (M, SKeva)
Clone Detection:
1.Readallsensoridentitynumbers.
2.M atchidentityofoverallclusterwithsendersensornode.
3.If(legitimatesensor)thentrueotherwisef alse.
B. Mathematical Model
1. Set Theory:
Let, S be a system, S= {N, C, CH, B, CN, A} , where,
1. Deploy Sensor nodes.. N= { N1, N2, …, Nn} , N is set of
all deployed sensor nodes.
2. Cluster formation. C= { C1, C2, …, Cn} , C is a set of all
clusters.
3. Select the Cluster Heads that is aggregator for Each
Clusters. CH= { CH1, CH2, …, CHn} , CH is a set of all
cluster heads.
4. Create Base Station. B= { B1, B2, …, Bn} , B is a set of
all base stations.
5. Find out compromised nodes CN= CN1, CN2, …, CNn} ,
where CN is a set of compromised nodes.
6. Robust data aggregation at aggregator node.
A= { A1, A2, …, An } , A is a set of all aggregated data files.
2. Mathematical model for proposed system
For Energy Calculation,
E tx (k; d) = E elec * K+ amp * k * d n
E Rx (k) = E elec * k
d: Distance for neighboring sensor node.
? amp : Energyrequiredforthetransmitteramplif ier.
Eelec : Energyconsumedfordrivingthetransmitterorreceiver.
V. CONCLUSION
We proposed efficient clone detection system in wireless
sensor network which uses the star topology. In the existing
system, ERCD protocol is used with ring topology network
which has limitations like when a particular node is disturbed
then the whole network is disturbed so we are using. The
cluster head is responsible for detecting clone in a wireless
sensor network. In cluster head selection, we select cluster
which is highest computation power and energy as well as
near to sensor network so there is no chance to disturbed whole
network.
ACKNOWLEDGMENT
Miss. Prema Kudale currently pursuing M.E (Computer)
from Department of Computer Engineering, Jayawantrao
Sawant College of Engineering, Pune, India. Savitribai Phule
Pune University, Pune, Maharashtra, India – 411007. My area
of interest is network security, WSN.
Prof. Madhav D. Ingle Pursuing PhD from K L University.
completed his M Tech. (Computer) Degree from Dr
Babasaheb Ambedkar Technological University, Lonere, Dist.
Raigad-402103, Maharashtra, India. He has completed his
B.E (Computer Engineering ) Degree from Govt College of
Engineering, Aurangabad, Maharashtra, India. He is currently
working as the M.E coordinator and Asso.Prof. in Department
of Computer Engineering, Jayawantrao Sawant College of
Engineering, Pune, India.SPPU, Pune, Maharashtra, India –
411007. His area of interest is network security and WSN.
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