USE OF JAMMER NETWORK TO DETECT DENIAL OF SERVICES ATTACK IN WIRELESS NETWORK

International Journal of Game Theory and Technology (IJGTT), Vol.1, 2015
41
USE OF JAMMER NETWORK TO DETECT
DENIAL OF SERVICES ATTACK IN WIRELESS
NETWORK
P.MOHANRAJ, A.MUMMOORTHY
1
Master of Computer Science and Engineering ,K.S.R. College of
EngineeringTiruchengode, India
2
Assisant Professor, Department of CSE,K.S.R. College of Engineering, Tiruchengode,
India
ABSTRACT:
The most important aspect of network is to share the data from one to another. It can either wired or
wireless. Both networks provides similar kind of security only. The internet users can have experience of
denial of services attack for hacking the data, to avoid the such a hacking provides many techniques to
resolve the problem. The jammer is an electronic device used to distrupt the communication. The jammer is
made of large number of tiny low power distributed jammer. Use of jammer to avoid the hacking of data. In
a network the node setup purpose uses they percolation concept. Based on the network, jammer,
performance are evaluated. Finally provides the results in simulation tool such as NS2.
KEY WORDS:
Network, Distrupt, DoS, Jammer, Percolation
1. INTRODUCTION
The wireless network can transfer the data threw the access point. The access point need not
reach all the nodes in the network.
FIG.1: Wireless network components
1.1 Security in Wireless Network
A.Confidentiality
B.Integrity
C. Availability

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1.2Denial of services attack
It is very common attack to wireless network. It may slow down or totally interrupt the service of
a system.
1.2 Distributed jammer network (DJN)
Jammer is an electronic device used to disrupt the communication.Jammers are used by military
and civilian applications because DJN can be deployed to form a low power (possibly air-born)
jamming dust to disrupt the communication.
1.3.1 Advantage of DJN
A. Robust
B.Low power
1.3.2 Types of jammer
A.Constant jammer
B. Deceptive jammer
C. Random jammer
2. PHASE TRANSITION USING PERCOLATION THEORY
We consider a random connection model where each pair of points(xi, xj ) of a Poisson point
process of density λ is connected with probability g(xi −xj ), for some given function g :R2→[0,
1]. All connections areindependent of each other.
It is well knownfor g that for any function g, H there is a critical value λc(g) that ensures
connectivity almost surely (a.s.), i.e., with probability one. This is defined as 0<λc(g)=inf {λ :
∃
infinite connected component a.s.}<∞.
When λ > λc we say that the random connection model percolates.The value of g(x) is 0 means
the nodes are said to be inside the network, if the value is 1 means the nodes are said to be
outside. To make inside the following two transformation methods used.
2.1 Squishing and Squashing Transformation
In this transformation technique used to transfer the data from one to another. Uses some
mathematical notations. G and H are they two functions have the probability value of (0,1). The
value is 0 means ready to transform if the value is 1make the adjustment to transform from one to
another.
2.2 Shifting and Squeezing Transformation
We call this transformation gshifts (x). Here we “shift” the function goutwards distance s,but
squeeze the function after that, so that it has the same effective area.

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3. JAMMER EFFECTIVENESS
There are two metrics used to measure the effectiveness of a jammer that is PSR and PDR. In
PDR the ratio of packet that are successfully delivered to a destination compared with number of
packets send by the source. In PSR the sender can the data threw the receiver successfully.
3.1 Detecting jamming attacks
Three ways to detect them jamming attacks signal strength, carrier sensing time(CST) and PDR.
In signal strength uses two approaches.In CST node A senes the channel by trying to send out a
beacon to the node B. It obtain the channel sensing time D by calculating the difference between
the time when beacon packets reach the destination sucessfully. In PDR has to be done in two
ways sender site or receiver site. In sender site the PDR can be calculated by keeping track of
how many acknowledgement it receiver from the receiver. In receiver site the PDR can be
calculated using the ratio of the number of packets the CRC with respect to the number of
packets received.
FIG 2. Over All System Architecture
4. RELATED WORK
Jamming assault on wireless networks was usually treated from the viewpoint of human being
jammers. We advocate a move toward based on the network viewpoint, and using this networked
approach we show that some attractive results can be obtained. We used show that DJN can
cause a stage transition in the presentation of the objective network. We employ percolation
assumption to explain such phase change, to analyze the impact of DJN on the connectivity of the
target network, and to give lower and upper bounds for the percolation of the objective network
to come about in the presence of DJN. To providing a large scaling examination of the jamming
in relation to the jammer node with density, we present simulation results recitation the impact of
DJN topology on the jamming efficiency. In proposed system to demonstrated that DJN can

44
cause a phase change in target network presentation even when the total overcrowding power is
held stable. We explained the stage changeover using percolation theory, analyzed scaling
performance of node thickness and numeral of nodes in DJN, and we also investigate the impact
of DJN topology on the overcrowding effectiveness. We believe awaiting the problem of
jamming in wireless networks from a set of connections perspective can broaden the investigate
scope significantly and can bring out some motivating results otherwise unachievable by focusing
on person jammers. Also using we think the interaction between DJN and DWN makes for
intriguing problems, which cut across system layers: device assignment, topology control,
authority control, medium access, routing, and data transport. Investigating those troubles can
result in deeper sympathetic of not only DJN but DWN as well. We believe a group more
interesting consequences can be obtain from this move toward and are currently operational in
this course.
4.1 Result analysis
In this figure the nodes are created with different distance. It also sets the attacker and source,
destination.

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The attacker can hack the information. After hacking the information the source can choose the
other path to receive the destination. The jammers aretaken the authenticated data.
5. CONCLUSION
The Reactive Defence Mechanism it’s used to moderate the DDoS attack and additional get better
system presentation in conditions of a smaller amount working out time. Supplementary the
reproduction product proves it to be an enhanced result leaning approach. Secondly we need a
systematic procedure for setting the parameters according to the network environment for our
proposed algorithm so that it shows effective results against real proof DDoS traffics. Using the
Reactive defence mechanism the data will be preventing for DDOS attack to the transmission of
networks.
REFERENCE
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