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

Abstract—The wireless sensor network has become an importantarea and it is widely applied to military civilian application.There are easily prone to security attack because it handlingwireless media for transmission. Detection of clone in WSN isa tedious job. In this paper further focuses on network lifetimeand improving memory management. Energy and memory bothare most valuable parameter in WSN. Efficient use of memoryis necessary. In proposed paper an energy and memory efficientclone detection protocol is densely deployed WSN , which canguarantee successfully clone detection and mainly satisfactorynetwork lifetime by efficiently distributing the traffic load acrossthe network.Keywords—clone detection, energy efficiency, memory effi-ciency,Wireless sensor networks.

I. INTRODUCTIONA wireless sensor network is typically collection of sensorswith restricted computational, memory and communicationasset. Remote sensor network contains a few number ofsensor nodes which are distributed in an objective identifyingenvironment inside of its neighborhood, gathers the informationand processes it. Mobile nodes are comprised of basicprocessor, application particular sensors, wireless transceiverand low battery. Data aggregation is utilized because of limitedamount of power in sensor nodes and to decrease transmissionoverhead. A wireless sensor network is used for different kindsof applications e.g. Health care, Fire Detection, Air pollutionetc Compromised nodes are the nodes which are under thecontrol of attacker.

Best services for writing your paper according to Trustpilot

Premium Partner
From $18.00 per page
4,8 / 5
Writers Experience
Recommended Service
From $13.90 per page
4,6 / 5
Writers Experience
From $20.00 per page
4,5 / 5
Writers Experience
* All Partners were chosen among 50+ writing services by our Customer Satisfaction Team

Attacker selects any node for performingattack. When attack happens on specific selected node, thenthat node is completely under the control of attacker. Throughthe compromised node, attacker can alter/modify the data ordrop the data which is routed via it. Detection of compromisednodes is very important issue as the sensitive data may get lostwhile transmission.A. Existing SystemIn the existing system, energy efficient clone detection andlocation-aware clone detection is introduced.

Given protocolis deployed in the wireless sensor network and it providesclone attack detection in wireless sensor network as well asmaintaining and enhancing networks lifetime. It distributestraffic load among the network. The existing system gatherslocation information of all sensor node and it verifies legitimatesensor node based on the randomly selected sensor as a witnessin ring area. System transfer data to sink via witness selected inring area. Suppose one of the sensors in ring area is shut downthen data transmission in a wireless sensor node is disturbed.II. REVIEW OF LITERATUREThe paper offered by the Zhongming Zheng, Anfeng LiuJan 2015 proposed ERCD (Energy Efficient Ring Based CloneDetection) protocol. Due to the suggested system, the datacan be lead extra proficiently.

The ERCD protocol requiredsome additional data buffer comparing with RED and P-MPCprotocol. Only the ring structure is considered in this paper.The performance of the ERCD protocol evaluates in termsof clone detection probability, power consumption, networklifetime and data buffer capacity. Extensive simulation resultsdemonstrate that in the system clone detection probability andnetwork lifetime with reasonable data buffer capacity. By usingERCD protocol energy consumption of sensor close to the sinkhas a lower traffic of witness selection.1In this paper offered Zhongming Zheng, Anfeng Liu in 2013,Witness message stored in the buffer over n/w and ERCD is notconsidering memory management.

ERCD protocol achievesthe high probability of clone detection.Less energy consumptionas compared to LSM (Line-select Multicast protocol. ItImproves the lifetime of N/w2. Cesare Alippi, GiuseppeAnastasi, Mario Di Francesco, and Manuel Roveri Feb 2011.In this paper authors planned an adaptive sampling algorithmthat guesses online the ideal sampling frequencies for sensors.This method, which needs the scheme of adaptive measurementsystems, reduces the energy eating of the sensors and,incidentally, that of the radio though preserving a very greatprecision of gathered data.

It can accomplish parallel to a fixedratesystem where the sampling frequency is well-known inadvance. This method outcomes in a matching energy savingof together the sensor and the radio.Decision intensely rests on the exact sensor, whose powereating is knowingly superior to that of the radio 3. ATrigger Identification Service for Defending Reactive Jammersin WSN was introduced by Ying Xuan, Yilin Shen, Nam P.Nguyen, and My T.

Thai.The benefit of using this serviceis its low identification latency4. It provides a completetrigger identification service framework for unreliable WSN.It provides a complete trigger identification service frameworkfor unreliable WSN and enhances the robustness ofn/w. Rongxing Lu, Xiaodong Lin came up with BECAN: ABandwidth-Efficient Cooperative Authentication Scheme forFiltering 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 anddistributed authentication scenario for example mesh.Distributed Clone Attacks are happening in Wireless SensorNetworks which causes the security threat in the system6.Thispaper introduces RED which has better detectionprobability and converges faster than LSM for all practicalvalues of the N/w parameter.

A new approach for RandomizedCountermeasure Against Parasitic Adversaries in Wireless SensorNetworks which was introduced by Panagiotis Papadimitratos,Jun Luo, and Jean-Pierre Hubaux7. It has RKRGossiCryptscheme to ensure WSN data confidentiality in awide range of setting. This scheme ensures the WSN data confidentialitywith the simple and low-cost mechanism. Detectingnode replication attacks in Sensor Networks is challengingtask8.The local voting system in WSN is used for detectingdistributed node replication.

Randomized Dispersive Routesfor Secure Data Collection in Wireless Sensor Networks isused9.This protocol provides a security as well as energyconsumption in WSN for small scale. If adversary blocksevery path from sink to the source node, this protocol doesnot address this attack.III.

SYSTEM ARCHITECTUREFig. 1: Simulation Result.The nodes of network are partitioned into disjoint clusters,and every cluster has a cluster head which is known asan aggregator.

Information are intermittently gathered andaggregated by the cluster head. In proposed system, we assumethat attack can happen on cluster member as well as dataaggregation node. Both can send false data to data aggregationnode and base station respectively. To detect the attack on dataaggregation node we use the concept clone detection. In theproposed 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 identificationof sensor node. Sensor data is encrypted and those data aresent to cluster head. It uses the star topology and cluster headwork as a hub.

This protocol is able to increase the efficiencyof energy in the network. The proposed system saves time andenergy than the existing system and improves the performance.1) Node Deployment:Randomly Generate number of sensor nodes. Those nodesare connected through the edges. It is process to generategiven the number of sensor node as well as it assign a uniquenumber 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. Thenumber of clusters is generated in the sensor network.3) Cluster Head Selection:Aggregator selection is done by using parameters like thehighest remaining energy of the nodes. This step is performedtwice, after initial formation of clusters and for selectionof new aggregator on detecting an attack on the old aggregator.4) Clone Detection:The Sensor node is responsible for sensing data from thesensor node and that sensing data is encrypted by usingPaillier homomorphic encryption algorithm. In the proposedsystem, we need to generate keys and these keys are usedfor encrypting sensed data as well as identity information.Later encrypted data is sent to the cluster head.

Cluster headalready maintained identity information of sensor node soit will check given sensor is legitimate or not. The clusterhead is nothing but one kind hub in particular cluster andstar topology uses the hub for maintaining all information ofanother node.IV. SYSTEM ANALYSISA.

AlgorithmInput: 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 maximumenergy and minimum distance to Base Station.Paillier Homomorphic AlgorithmEncryption:1. Randomly take two prime numbers p and q2. Generate public key and private key{PKeva, SKeva} ? keygeneration3.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 Model1. 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 ofall deployed sensor nodes.2. Cluster formation. C= { C1, C2, …, Cn} , C is a set of allclusters.3.

Select the Cluster Heads that is aggregator for EachClusters. CH= { CH1, CH2, ..

., CHn} , CH is a set of allcluster heads.4. Create Base Station.

B= { B1, B2, …, Bn} , B is a set ofall 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 systemFor Energy Calculation,E tx (k; d) = E elec * K+ amp * k * d nE Rx (k) = E elec * kd: Distance for neighboring sensor node.? amp : Energyrequiredforthetransmitteramplif ier.Eelec : Energyconsumedfordrivingthetransmitterorreceiver.V. CONCLUSIONWe proposed efficient clone detection system in wirelesssensor network which uses the star topology. In the existingsystem, ERCD protocol is used with ring topology networkwhich has limitations like when a particular node is disturbedthen the whole network is disturbed so we are using. Thecluster head is responsible for detecting clone in a wirelesssensor network.

In cluster head selection, we select clusterwhich is highest computation power and energy as well asnear to sensor network so there is no chance to disturbed wholenetwork.ACKNOWLEDGMENTMiss. Prema Kudale currently pursuing M.E (Computer)from Department of Computer Engineering, JayawantraoSawant College of Engineering, Pune, India.

Savitribai PhulePune University, Pune, Maharashtra, India – 411007. My areaof interest is network security, WSN.Prof. Madhav D. Ingle Pursuing PhD from K L University.

completed his M Tech. (Computer) Degree from DrBabasaheb Ambedkar Technological University, Lonere, Dist.Raigad-402103, Maharashtra, India. He has completed hisB.

E (Computer Engineering ) Degree from Govt College ofEngineering, Aurangabad, Maharashtra, India. He is currentlyworking as the M.E coordinator and Asso.Prof.

in Departmentof Computer Engineering, Jayawantrao Sawant College ofEngineering, Pune, India.SPPU, Pune, Maharashtra, India -411007. His area of interest is network security and WSN.REFERENCES1 G.

Mergen, Z. Qing, and L. Tong, Sensor networks with mobile access:Energy and capacity considerations, 2015, IEEE Transactions on MobileComputing.2 Zhongming Zheng, Anfeng Liu,, ERCD: An Energy-efficient CloneDetection Protocol in WSNs,2013,IEEE Transactions on Mobile Computing.3 Anfeng Liu, Ju Ren, Xu Li, Zhigang Chen,, DCFR: A Novel DoubleCost Function based Routing Algorithm for Wireless Sensor Networks ,IEEE ICC 2012 – Ad-hoc and Sensor Networking Symposium4 Ying Xuan, Yilin Shen, Nam P.

Nguyen, and My T. Thai, A Trigger IdentificationService for Defending Reactive Jammers in WSN 2012,IeeeTransactions on Mobile Computing5 Rongxing Lu, Xiaodong Lin, BECAN: A Bandwidth-Efficient CooperativeAuthentication Scheme for Filtering Injected False Data in WirelessSensor Networks , 2012,IEEE Transactions On Parallel And DistributedSystems.6 Mauro Conti, Member, IEEE, Roberto Di Pietro, Luigi VincenzoMancini, and Alessandro Mei , Distributed Detection of Clone Attacksin Wireless Sensor Networks ,IEEE Transactions On Dependable AndSecure Computing.7 Panagiotis Papadimitratos, Jun Luo, and Jean-Pierre Hubaux,A RandomizedCountermeasure Against Parasitic Adversaries in Wireless SensorNetworks,2010,IEEE Journal On Selected Areas In Communications.8 Bryan Parno, Adrian Perrig,Distributed Detection of Node ReplicationAttacks in Sensor Networks,Proceedings of the 2005 IEEE Symposiumon Security and Privacy.9 Tao Shu,Marwan Krunz,Secure Data Collection in Wireless Sensor NetworksUsing Randomized Dispersive Routes, 2010, IEEE TransactionsOn Mobile Computing