IRJET- Enhanced ID based Data Aggregation and Detection Against Sybil Attack using Challenge Response Authentication Protocol

International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 06 Issue: 03 | Mar 2019 www.irjet.net p-ISSN: 2395-0072
© 2019, IRJET | Impact Factor value: 7.211 | ISO 9001:2008 Certified Journal | Page 481
S. Syed Nawas Husain1, Dr. M. Mohamed Sathik2, Dr. S. Shajun Nisha3
1M.Phil Research Scholar, PG & Research Department of Computer Science, Sadakathullah Appa College,
Tirunelveli, Tamilnadu, India
2Principal, Sadakathullah Appa College, Tirunelveli, Tamilnadu, India
3Assistant Professor & Head, PG & Research Department of Computer Science, Sadakathullah Appa College,
Tirunelveli, Tamilnadu, India
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Abstract - In recent year’s security of wireless sensor
network attracted intensive attention in both research and
applications. Many aspect of wireless sensor network
applications are defense, industrial process monitoring and
control, machine health monitoring, etc. In this paper we
presented ChallengeResponseAuthentication protocol(CRAP)
between the transaction source to destination, which
generates unique key and match the response key to provide
unique encrypted communication for every transmission. In
the earlier system, coalition attack can be detected through
transaction details. Here, we are using Sybil attack, which
theft the information of identity nodes while data
transmission, The CRAP is used here to prevent such Sybil
attacks. The performance of analyzed detection scheme is
evaluated using performance detection ratio and provides
better result.
1. INTRODUCTION
Wireless Sensor Network (WSN) has been widely used in
military, industrial and medical applications during the last
decade. [1] The network is consisted of moreofthousandsof
sensor nodes. Usually the sensor nodes have limited power,
memory, and computing abilities, then energy conservation
become a very important problem of WSN researches. The
cluster based WSN is proposed for this purpose [2].The
cluster head (CH) is responsible for the management and
data process an aggregation of the cluster member nodes
(cluster member, CM). Selective Nodes send theirdata tothe
cluster head and the cluster head aggregates cluster head
data of all nodes within it and sends data to the Base Station.
Clustering process enables bandwidth and can increase
system capacity. Of course, it helps improve power control
and better of resource allocation.
This system attentive the cluster based on wireless sensor
network. Because of the rapid development of WSN, many
works have been presented in recent years. Theyincludethe
authentication field, efficient protocol routing and data
fusion algorithms. Also, there are few securityrelatedworks
which we will talk about in this system. Security problems
put many applications in the devil of a hole[5].Theattackers
could scout the network traffic easily and trace the data
information from any sensor node if the privacy such as
identity or location is lack of protection. Privacy has become
a critical issue for the WSN deployments. For traditional
network, anonymous communication is an important
method protecting the privacy of users. It includes
anonymity node, location privacy node, untraceability and
unlinkability. And, it can be split it into three anonymous
types which including sender anonymity, recipient
anonymity and unlinkability.
Many anonymous protocols have been proposed for the
traditional network in last decades. Chaum's mixnet and
DCnet are the original work about it. But both approaches
require public key cryptosystems and can't be used into
WSN due to power and resourcesconstrainsofsensornodes.
So it is essential to develop mechanisms that suitedfor WSN.
[3]In this system, we design a sensor anonymity
enhancement plan based on pseudonym for clustered WSN.
The scheme includes two phases. It can protect the privacy
both of the CMs and the CH nodes. [1] We thenusingentropy
based method to evaluate anonymity of the scheme and
implement the scheme using NS2 simulator to test the
performance of the scheme. Both the theoretical and the
empirical study imply thatourproposedschemecanprovide
good anonymity for both CMs and CHs.
1.1. ATTACK FREE NETWORK FORMULATION
A wireless sensor network consiststhousandsofsmall nodes
which are distributed over the network. These nodes sense
the sensitive data from the location and send the sensitive
message to the base station.[4] The base station will verify
the information and ID which is send by the sensor nodes.
These sensor nodes are position in hostile environment and
the nodes are unattended many replicas of which makes an
adversary to compromise the sensor nodes and make. In
robotics advances developing an variety of new
architectures for autonomous. In network communications
of mobile nodes are useful for network repair and event
detection. [2], [4] The mobile nodes are compromised inject
the forgery data and disrupt network operations and
eavesdrop on network communications. Software based
Attack using Challenge Response Authentication Protocol
Enhanced ID based Data Aggregation and Detection Against Sybil

replica detection plans have proposed for static sensor
networks. The nodes sensor also report the location state
that identify their positions and send to the base station. In
this system, the proposed compromised nodedetectionplan
based on the sequential probability ratio test
2. LITERATURE SURVEY
Noor et al. [1] proposed an identity based signature
aggregate scheme keeps data integrity with designated
verifier this scheme providing more secure and efficient
process we make use of Elliptic cryptography curve and
Diffie hellman assumption data transmitted compromised
aggregators to provide privacy.
Yingying et al. [2] proposed a method for detecting
indentity based attack including spoofing and Sybil attacks
RSS based methods of identity-oriented authentication and
detection problem In robust to detectattacksuseofdifferent
transmission in various power levels and built real-time
localization system.
Pengwenlong Gu et al. [3] proposed to support vector
machine based Sybil attack method for improving road
safety and driving experience in vehicle driving patterns are
mainly represented using Driving paterns matrices begin
variation of vehicle and Sybil nodes classify into SVM
methods during virtual nodes.
Kamdeo et al. [4]. Harsh operating environment areopen of
susceptible WSNs can many kinds of attacks has prevented.
Here using Sybil.one of the most dangerous attacksinWSNs.
here using Sybil attack Detection Algorithm (SDA) for
detecting and preventing Sybil attack in WSNs.SDA is more
secured for transmission data in any way avoid Sybil attack.
Bin Zeng et al. [5] recommended Ant Colony Optimization
(ACO) algorithm using third party initiate between honest
node if a malicious node successfully fools be trusting as
used to prevent significant protocol ones in this system
probability is high accuracy variants be evaluate fake
identities with trusted edges.
3. SYSTEM MODEL
3.1. Challenge Response Authentication Protocol:
In Challenge Response Authentication Protocol have three
phases. Detection accuracy in which increased when
compared to the previous phase Challenge-response
mechanisms based onsymmetric-keytechniquesrequire the
claimant and the verifier to share a symmetric key [5]. For
closed systems with a small number of users, each pair of
users may share a key a priori; in larger systems employing
symmetric-key techniques, identification protocols often
involve use on-line server trustedin whicheachpartyshares
a key. The online server effectively acts like the hub of a
spoke wheel, providing a common sessionkeytotwoparties
each time one requests authentication.
Fig 3.1
Phase 1
 Create a group of mobile nodes, Sybil node,and
normal node.
 According to the procedure nodes are taken from
base station
 The base station node A sends HELLOOO packetsto
all the node B and responsible node B sends
SUNDAY to node A for topology verification.
 The nodes with minimum packet drop are the
chosen as the trust nodes.
 The trust nodes now become the head nodes with a
combination of its own member nodes.
 The member nodes send their ID and then power
value to the head nodes.
 The head node checks for the nodes with a power
value below the threshold value
 Thus the power value is lesser than the threshold
value, then the nodes are detected as Sybil nodes.
Phase II
 Two nodes nearest to Sybil nodes are selected as
senders n1, n2.
 Two Sybil nodes are selected and the receivers are
s1, s2.
 Packets are sent to n1 and n2 to both receivers
 Since both identities are present at the same node,
there is collision of packets leading into the packet
drops.
 The distance between the receivers is found.
 The are nodes suffers from Sybil attack
 If the nodes are very close and then process.
Phase III
 If there occur a hop between the Sybil identities,
then the nodes are not Sybil nodes.

 If no hops, then the nodes are confirmed to be
above the attack and they will be removed from
the network two nodes closer to Sybil nodes are
selected as sender’s n1 and n2.
 Two Sybil nodes hop between the Sybil identities
and then the nodes are not Sybil nodes has been
detection.
 If no hops, then the nodes are confirmed to be
under attack and then they process will be
removed from the network
4. OUTLINE OF PROPOSED WORK
 The nodes were formed in WSN.
 There were three types of nodes: Source Node,
Static Node and Mobile Node[4].
 Each node were assigned with ID for aggregation
network traffic data.
 CRAP technique implemented for analyzing node
identity.
 Sybil Attack Detection through Genetic Algorithm.
 Performance can be evaluated through PDR,Energy
Efficient, Attack Detection Ratio, etc.
Fig 4.1
5. Result
Fig 5.1
Fig 5.2
Fig 5.3
Graph Representation
Fig 5.4 (Attack Detection Ratio)
6. CONCLUSION
This system concludes that the malicious nodes in wireless
sensor networks are detected by using a new statistical
testing technique called sequential probability ratio testing.
Using this technique the compromised sensor nodes are
detected efficiently in mobile sensor networks.Ourwork has

focused on the privacy problem of cluster based on wireless
sensor network and using anonymous methodtoprotectthe
privacy of the nodes. We designed a novel sensor anonymity
enhancement scheme for WSN. In order toprovethe efficacy
of the scheme, we used entropy based method to evaluate
the degree of anonymity our scheme achieved. For all the
above mentioned strategies demonstrates that our scheme
can protect the privacies of both the sensor nodes and the
cluster heads, and can use in any cluster based on wireless
sensor network
7. FUTURE SCOPE
The proposed system is done on the evaluation parameters,
in scheme of proposed able to identify and Sybil attack in
those networks and very efficiently. Also the mitigation
scheme works effectively. The experimental results show
that works better in terms of good detection rate, low false
positive rate and low false negative rate. The future scope of
this work may include making scheme more cost efficient
and easy to implement in any type of network. The main
focus will be on detection rate and false positive rate.
REFERENCES
1. Noor Basha, Kavya N, Manjushree K, Arogyasheela
A and Bhavana T, “ ID-Based Aggregate Signature
Scheme for Wireless Sensor Networks UsingSecure
and Efficient Data Transmission ”, International
Research Journal of ComputerScience(IRJCS),Issue
05, Volume 4 (May 2017)
2. Yingying Chen, Yang, Wade Tappe and Richard
P.Martin, “ Detecting and Localizing Identity-Based
Attacks in Wireless and Sensor Networks ”, IEEE
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VOL. 59, NO. 5, JUNE 2010.
3. Pengwenlong Gu, Rida Khatoun, Youcef Begriche
and Ahmed Serhrouchni, ” Support Vector Machine
(SVM) Based Sybil Attack Detection in Vehicular
Networks ”,IEEE Wireless Communications and
Networking Conference (WCNC),2017.
4. Kamdeo Prasad and Chandrakant Mallick,” A
Mobile Agent based Sybil Attack Detection
Algorithm for Wireless Sensor Network”, in
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Computing and Communication (ETCC 2015)
5. Bin Zeng and Benyue Chen, ” SybilACO: Ant colony
optimization in defending against Sybil attacks in
the wireless sensor network ”, International
Conference On Computer and Communication
Technologies in Agriculture Engineering,
2010(IEEE)
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BIOGRAPHIES
S. Syed Nawas Husain received the
B.sc degree in Computer Science
from MS University in 2016 and
M.sc degree in Computer Science
from MS University in 2018.He is
currently pursuing the M.phil
degree in Computer Science. Her
research interest mainly include
domain of Network Security.

“Dr. M. Mohamed Sathik M.Tech.,
M.Phil., M.Sc., M.B.A., M.S., Ph.D has
so far guided more than 35
research scholars. He has
published more than 100papersin
International Journalsandalsotwo
books. He is a member of
curriculum development
committee of various universities
and autonomous colleges of Tamil
Nadu. His specializations are
VRML, Image Processing and
Sensor Networks.
Dr. .S.Shajun Nisha AssistantProf&
Head of PG and Research
Department Of Computer Science,
Sadakathullah Appa College. She
has completed M.Phil. (Computer
Science) and M.Tech (Computer
and Information Technology) in
Manonmaniam Sundaranar
University, Tirunelveli. She has
completed her phd in .She has
involved in various academic
activities. She has attended so
many national and international
seminars, conferences and
presented numerous research
papers. She is a member of ISTE
and IEANG and her specialization
is Image Mining.

IRJET- Enhanced ID based Data Aggregation and Detection Against Sybil Attack using Challenge Response Authentication Protocol

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