Prevention of Malicious Nodes and Attacks in Manets Using Trust worthy Method

INTERNATIONAL JOURNAL FOR TRENDS IN ENGINEERING & TECHNOLOGY
VOLUME 5 ISSUE 2 – MAY 2015 - ISSN: 2349 - 9303
136
Prevention of Malicious Nodes and Attacks in
Manets Using Trust worthy Method
1
Amrutha Mohan
PG Student,
Department of ECE,
Dhanalakshmi Srinivasan College of Engineering,
Tamilnadu, India
amruthamohan@gmail.com
2
Siva Kumar K
Assistant Professor
Department of ECE,
Dhanalakshmi Srinivasan College of Engineering,
Tamilnadu, India
siva.jece@gmail.com
Abstract-In Manet the first demand is co-operative communication among nodes. The malicious nodes might
cause security issues like grey hole and cooperative attacks. To resolve these attack issue planning Dynamic supply
routing mechanism, that is referred as cooperative bait detection theme (CBDS) that integrate the advantage of each
proactive and reactive defence design is used. In region attacks, a node transmits a malicious broadcast informing
that it's the shortest path to the destination, with the goal of intercepting messages. During this case, a malicious
node (so-called region node) will attract all packets by victimisation solid Route Reply (RREP) packet to incorrectly
claim that “fake” shortest route to the destination then discard these packets while not forwarding them to the
destination. In grey hole attacks, the malicious node isn't abs initio recognized in and of itself since it turns
malicious solely at a later time, preventing a trust-based security resolution from detective work its presence within
the network. It then by selection discards/forwards the info packets once packets undergo it. During this we have a
tendency to focus is on detective work grey hole/collaborative region attacks employing a dynamic supply routing
(DSR)-based routing technique.
Keywords- Security, Trust, Fake request, Fake reply, Malicious, Dynamic source routing, Gray hole attack
1. Introduction:
Analysis of the precise attack
mechanism that evaluates misreporting channel
condition is completed here. During this setting, a
user will incorrectly report its channel condition
as over claiming (reporting its channel condition
as higher than actual measurement). In a very
mobile wireless network, mobile nodes will
expertise totally different channel conditions
betting on their different locations. Once a node
experiences a channel condition that's too poor to
receive packets from a supply node, a third node
might have an honest channel condition to receive
each of the supply and also the destination
information is distributed through that third node.
Aggressor will increase its likelihood of relaying
packets for the victim. During this system once a
node become egoistic the information is
distributed through another node and therefore
varies the trail and therefore decreases network
performance by packet dropping and delay.
In this system once a node is detected as an
egoistic node some packet is also lost that the
network goes for one more path. Knowledge lost
from egoistic node is extremely troublesome to
recover or it is not possible to recover. Supply
once more sends request to all or any nodes and
once more realize another path for knowledge
causation therefore supply seeks for a replacement
path whenever miscalculation or egoistic node is
detected within the network. This might increase
delay and overhead within the network and
reduces network performance.
1.1 Cooperative Relaying
In a mobile wireless network, mobile nodes
will expertise completely different channel conditions
counting on their different locations. Once a node
experiences a channel condition that's too poor to
receive packets from a supply node, a third node
might have an honest channel condition to each the
supply and therefore the supposed destination.
Cooperative relaying network architectures facilitate a
node that has poor channel condition to route its
packet through a node with an honest channel
condition, therefore up system outturn. so as to seek
out such routes, a cooperative relaying protocol
should distribute channel condition info for every
candidate path, realize the foremost applicable relay
path, and supply incentives to inspire nodes to
forward packets for different nodes.

137
The attacker’s goal during this simulation is
to cut back the victim’s output. The wrongdoer will
adopt two approaches. Within the conservative
approach, the wrongdoer doesn't forward packets for
the victim while not incorrectly reportage its channel
condition. Within the aggressive approach, the
wrongdoer over claims its channel condition so the
wrongdoer will increase its chance of relaying packets
for the victim. Once a node underneath claims its
channel condition, the node reduces its chance of
being chosen for forwarding; the underneath claiming
attack is therefore no worse than powering the node
off. As a result, underneath claiming isn't a good
attack against cooperative relaying. Through
simulation the impact of over claiming attack is
evaluated. If associate degree wrongdoer over claims
its channel condition, the wrongdoer is a lot of
possible to be chosen because the best candidate for
relaying. Designating the wrongdoer as a relaying
node provides the wrongdoer a chance to steal the
packets or to adversely impact network performance.
All nodes have specific energy in a very
network, which helps them to transfer the information
packets appointed to them. But, once sure
transmissions there happens decrease during this
energy of a node that causes the node to be a egoistic
node. They will even be outlined as nodes that don't
forward others packets, therefore maximising their
edges at the expense of others. Egoistic behaviour of
nodes will result in big selection of issues. These
nodes aim to save lots of its resources to most. They
discards the incoming packets supported their
individual energy, which ends in average end to finish
delay. The behaviour of egoistic nodes results in
decrease in overall knowledge accessibility of the
network. The most disadvantages of egoistic nodes
square measure, a egoistic node enjoys all the
resources of a network however it nerd offers away its
own resources. It uses away network resources like
battery power for its own profit. The egoistic nodes
build a network inactive. So measure the degree of
stinginess of nodes is incredibly vital.
2. Modules:
A. Network Formation
B. Route Discovery
C. Opinion Request Generation
D. Update malicious node in Route Cache
2.1 Network Formation:
Here, formation of nodes occurs and choose
the supply and destination. When choosing the supply
and destination, supply desires to send the
information to destination. Thus a route for
information forwarding is needed.
2.2 Route Discovery:
Initially supply broadcast its route request to
that square measure the neighbours accessible in
supply which may vary. Neighbouring nodes receive
the request and it will check destination address, if the
actual node may be a destination it will generate route
reply and it will send to supply through the
corresponding path. If the node not a destination it
will forward to next nodes. Once choose the route all
the nodes update its route cache.
2.3 Opinion Request Generation:
Whenever supply node sends route request,
it will watch for route reply. When obtaining the route
reply it validate the route cache like all malicious
nodes enter the network or not. If it's not, supply node
generates opinion message and it broadcast to all or
any the neighbours. Here all the neighbour nodes
update if the nodes sight any malicious nodes.
2.4 Update malicious node in Route Cache:
Source node update malicious node in its route
cache, it will not choose that specific path for data
forwarding.
Here in this network formation we are
choosing 50 nodes. Green nodes represents the source
and destination. Black colour node are intermediate
nodes that are available in the network for packet
transmission. Red node in the figure 1 indicate the
malicious node entering in to the network.
Fig.1: Entering of malicious node into the network.
The malicious node entering to the network
is shown in the figure 1. While entering to the

138
network all the normal nodes will send the fake
request to the node. Normally the fake node will reply
but some cases it will not reply for this request. To
avoid this all the nodes will send the fake request to
the malicious node. If any of the node detects, it will
broadcast to all the nodes in the network.
Fig.2: Malicious node entered in the network.
In the figure 2 the malicious node entered in
the network and all the nodes are checking and
sending the fake request to the malicious node
Fig. 3 : Malicious node identification.
In the figure 3 the malicious node is identified by all
nodes because of the broadcast message. Now all the
nodes will eliminate the malicious node from their
route. And it will eliminate the path with the
malicious node. Data is transmitted to the destination
without any failure by avoiding the malicious node in
the network.
3. Related Works:
[1] In this paper author analyze specific attack
mechanisms and measure the consequences of
misreporting channel condition on varied channel
aware wireless network protocols as well as
cooperative relaying protocols, routing metrics in
wireless circumstantial network and timeserving
schedulers. Here propose a secure channel
condition estimation rule which will be wont to
construct a secure channel-aware protocol in
single hop settings and analyze the rule within the
respects of performance and security, and perform
a simulation study to know the impact of rule on
system performance. The false channel condition
reportage attack that introduced during this paper
is troublesome to spot by existing mechanisms,
since attack is usually protocol compliant; solely
the channel condition menstruation mechanism
got to be changed. Attack will therefore be
performed victimization changed user
instrumentality illicitly registered to a network.
[2] In this paper, author introduces Janus, a
framework for ascendible, secure, and economical
routing for hybrid cellular and Wi-Fi networks.
Janus uses a ascendible routing algorithmic rule
with multiple channel access, for improved
network outturn. Additionally, it provides
protection against self-loving nodes through a
secure crediting protocol and protection against
malicious nodes through secure route institution
and knowledge forwarding mechanisms. This
paper value Janus by experimentation and show
that its performance is eighty five % of the
optimum algorithmic rule, up with an element
larger than fifty % over previous work. This value
the safety overhead of Janus against 2 varieties of
attacks: less aggressive, however spare for a few
applications, self-loving attacks and strictly
malicious attacks
[14] 3G cellular networks, like High Speed
Downlink Packet Access (HSDPA) and Evolution
knowledge Optimized (EV-DO), give broadband-
like downlink speed to modify applications, like
VoIP. The specification for 3G cellular
knowledge services recommends implementing
associate degree expedient computer hardware.
Expedient computer hardware uses multiuser
diversity the weakening and shadowing of cellular
users inside one cell to optimize information
measure potency. Each HSDPA associate degreed
EV-DO use expedient computer hardware within
the downlink to exploit multiuser diversity. To
realize this goal, several networks need mobile
devices to participate in managing network
services. However, since mobile devices square
measure outside the management of the network
directors, networks shouldn't trust them to manage
network operations. sadly, this principle is
commonly desecrated, as within the case of the

139
favoured expedient planning algorithms, we tend
to discovered 2 vulnerabilities:
(1) PF and TF schedulers trust channel
condition reports from mobile devices
while not verification.
(2) Both schedulers guarantee fairness
solely inside one cell.
[4] In this paper author describes the planning and
implementation of ETX as a metric for the
Destination Sequenced Distance Vector (DSDV)
and DSR (Dynamic supply Routing) routing
protocols, moreover as modifications to DSDV
and DSR which permit them to use ETX.
Measurements taken from a twenty 9 node
802.11b test-bed demonstrate the poor
performance of minimum hop count, illustrate the
causes of that poor performance, and make sure
that ETX improves performance. For long
methods the outturn improvement is commonly an
element of 2 or additional, suggesting that ETX
can become additional helpful as networks grow
larger and methods become longer.
[7] In this paper implementation results show that
the SUCAN system will give substantial
performance will increase and protects against
performance degradation even within the presence
of malicious behaviour. trendy cellular knowledge
services, like CDMA2000 (Code Division
Multiple Access), adaptively opt for modulation
schemes and writing rates supported the signal to
noise quantitative relation between the bottom
station and therefore the mobile user, permitting a
lot of economical communications with mobile
users that area unit nearer to the bottom station,
whereas still providing lower-speed coverage to
users that area unit farther removed from the
bottom station.
4. Conclusion
In this paper the routing security issues of
MANETs, are discussed. One type of attack, the black
hole, which can easily be deployed against the
MANET, is described. The percentage of packets
received through the proposed method is better than
that in AODV in presence of cooperative black hole
attack. The solution is simulated using the Network
Simulator and is found to achieve the required
security with minimal delay & overhead. Future
works may be concentrated on ways to reduce the
delay in the network.
5. References
[1] Dongho Kim and Yih-Chun Hu, (2014),
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[2] Carbunar. B, Ioannis. I, and Nita Rotaru.
C, (2009), “Janus: A framework for
scalable and secure routing in hybrid
wireless networks”, IEEE transactions on
Dependable Secure Computing, Vol. 6,
No. 4, pp. 295–308.
[3] Dongbin Wang, Mingzeng Hu and Hui
Zhi, (2008), “A survey of secure routing in
ad hoc networks”, The Ninth International
Conference on Web-Age Information
Management, IEEE DOI
10.1109/WAIM.2008.79.
[4] Douglas, De Couto D.S., Aguayo. J,
Bicket. J, and Morris. R, (2003), “A high
throughput path metric for multi-hop
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[5] Draves. R, Padhye. J, and Zill.B, (2004),
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140
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