Secure Route Selection Mechanism in the Presence of Black Hole Attack with AOMDV Routing Algorithm

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978-1-5386-5257-2/18/$31.00©2018 IEEE
Secure Route Selection Mechanism in the presence of
Black hole Attack with AOMDV Routing Algorithm.
Pravin R Satav
Research Scholar S. G. B. A. U.
Amravati
Lecturer in Computer Engineering
Government Polytechnic Arvi
prsatav@gmail.com
Dr. Pradeep M. Jawandhiya
Principal
Pankaj Ladhhad College of
Engineering Buldhana
pmjawandhiya@gmail.com
Dr.Vilas M. Thakare
Professor and Head of Department
of Computer Science, S.G.B.A.U,
Amravati
vilthakare@yahoo.co.in
Abstract— The research in MANET has been carried out for
the development of various techniques which will increase the
competency of the network only. A plenty number of proposed
routing protocols are magnificent in terms of efficiency.
However, proposed protocols were generally fulfilling the set of
trusted network and not considered for adversarial network
setting, hence there is no security mechanism has been
considered. MANET is widely used in sensitive fields like
battlefield, police rescue operation and many more in such type
of sensitive field an attacker may try to gather information about
the conversation starting from the origin node to the terminal
node. Secure route selection approach for route selection in
adverse environment is discussed in this article. The results
shows that proposed algorithm, will resolve the single &
collaborative attack by increasing the computational & storage
overhead and by improving the significant PDR, achieves a
noticeable enhancement in the end to end delay.
Keywords—AOMDV, blackhole attack, MANET, routing
I.
I
NTRODUCTION
Number of mobile nodes form a network is known as
MANET. Wifi enable nodes are used in this network are
capable to communicate with each other. Since for the
deployment of MANET no spatial infrastructure is required.
Due to the infrastructure fewer environments, there will be a
lot of security issues in MANET, which will impact on overall
network performance [01]. Nodes present in MANET are
categorized in the three categories 1) source node 2)
intermediate node 3) destination node. Each node has to do
some responsibility in the network because; no special
infrastructure is available in the network. Starting node will
broadcast the route request for creation of route between the
source node to the destination node. Iintermediate nodes has to
perform various roles, like which will send REEP to the
received RREQs in route discovery process, and forward the
RREQ as well as the packets are transmitted to its neighbor
nodes. Ddestination node will accept the RREQ, and packets
from its neighbor node which was sent by the source node.
Means the packets have to pass through the many nodes.
While passing the packets through the number of nodes, it is
expected that trusted nodes must present in the network. There
is a possibility that some nodes are not genuine. Some nodes
always take part in routing by propagating false route
information. These types of nodes may do different activities
like modification, fabrication, eavesdropping, redirecting, and
dropping the packets and many more [02] [03]. If any node
present in the network took part in any activity, it is a serious
threat for the network. Single or multiple nodes can perform
this packet dropping activity in the network. In single black
hole attack only one is node performs the packet dropping
activity while in collaborative attack, multiple nodes are took
part in packet dropping activity [04]. Due to this type of
malicious activity by single or multiple nodes in the network
is responsible to increase in the routing overhead. By using
multipath routing protocol it can minimize this overhead.
More than one path can be discovered by the multipath routing
protocols. These multiple paths will help to develop the
automated network which will choose the secured path for
communication. Use of multipath routing algorithm will
reduce the initiation of frequent route discovery process.
Route discovery process is initiated only when all available
paths in the network are not secured or not available due to
mobility of nodes or node die due to its limited battery. Many
multipath routing algorithms are proposed for MANET
amongst those AOMDV (Ad hoc on demand multipath
distance vector) is used by number of researchers [05].
II. R
ELATED
W
ORK
MANET has many more challenges, to overcome these
challenges various techniques are suggested. One of the
challenges of the MANET is the presence of malicious node in
the network. Various techniques for detection and prevention
of black hole attack to improve the network performance are
studied. These techniques are categorized as development of
new secure routing protocol, identification and its removal
technique. For identification and removal of malicious node as
blackhole from the network, some authors suggested the
certification based authentication techniques [06][07] , some
authors suggested the cross-layer authentication
technique[08][09], and some are suggested cluster architecture
based techniques[10]. Presence of blackhole node in the
network is the serious hazard for MANET [11][12][13].
Discovery of malicious node in the network, by intrusion
detection system (IDS) is proposed [14]. In this system,
authors assigned the unique identification code to the
malicious node present in the network and circulate this ID
code to the all the nodes present in the network. This ID node
will be blacklisted from the routing process. This methodology
identifies and produces the assumption against misbehavior in
routing through the malicious attack. Author created a network
with black hole attack. For validating the results of the

2018 Fourth International Conference on Computing Communication and Control and Automation (ICCUBEA)
proposed technique, proposed IDS scheme is applied and
calculated the performance of the network. This calculated
performance of proposed technique is compared with the
performance result after applying the existing AOMDV
routing algorithm on this network and found that the
performance of the network in both situations is same but the
malicious activities of malicious node are suspended and
recovers the 95 % of data as compared to normal routing
protocol. They suggested future work to apply this scheme to
another attack and also analyze the effect of an attack on
energy consumption of mobile nodes.
Impact of black hole attack on the network is studied [15]. To
resolve this impact from the network, feasible solution is
suggested in this article. For implementing this network they
use the AOMDV routing protocol in the network. Authors
simulate the result and found that packet delivery ratio varies
between high and low. This packet delivery ratio depends
upon the distinct security specifications like the presence of
blackhole attack and in absence of blackhole attack. They
developed the model for fixed topology and suggested to
develop the model for dynamic topology.
Black hole attack behavior and its impact on network with
AOMDV protocol is studied thoroughly in [16]. They studied
various approaches designed by researchers and found that
solutions suggested by researchers so far are suffered from one
or other hurdle. After analyzing the approaches designed so
far, authors developed the new techniques which will detect
and prevent the impact of black hole in network with
AOMDV routing protocol. After simulation of the developed
technique, they found that, this technique is not increasing the
routing or computation overhead and increases the network
performance features like throughput, packet delivery ratio by
a huge margin. This solution detects single and cooperative
black hole attack. They proposed the technique of removal of
all malicious nodes present in the network as a future work.
Removing malicious nodes from the network its saves the
energy deprived nodes from computation overhead of
implementing different approaches for a different attack.
The author studied the routing attacks in MANET [17][18].
Their study shows that impact of the presence of malicious
node in the network either in single path or multipath routing
algorithm. To overcome the impact of malicious node in
multipath AOMDV routing algorithm, proposed the approach
to select the route on which black hole node is not present.
They added a new factor to identify the faithfulness of node,
as a trusted node. By adding this factor in AOMDV routing
algorithm they planed the development of vigorous AOMDV
routing algorithm to preserve the black hole attack. They
added a new factor as a trust factor of a node.
The authors put the focus on security issues related to
designing a routing protocol are discussed [19] [20]. AODV is
very much popularly used routing protocol but it is vulnerable
to various types of attacks. Discussion of ongoing solutions
proposed for detection and removal of black, gray hole attacks
is carried out, and proposed a contemporary avenue to counter
these attacks which will fluently discover the shortest,
efficient and secure path towards the destination.
Detailed analysis of various techniques proposed by the
researchers earlier for detection and prevention of malicious
node in the network is done [21]. Their study shows the
different detection schemes fidelity, DRI, trust all are
detecting single as well as collaborative black hole attack but
each one may have a number of defects like increased storage
head, computational overhead , routing overhead and
increased in the end to end delay. For mitigating the impact of
single and collaborative black hole attack, authors proposed
the two algorithms. The proposed algorithm is implemented
and compared the results of it are compared with existing trust
schemes, fidelity, DRI, but there is no significant changes in
storage overhead, but observed that noticeable reduction in
routing and computational overhead.
After an overall study done by researchers all are stating
that no concrete solution is discovered for detecting and
preventing the presence of single & collaborative black hole
attack which will remove all defects of existing schemes.
Researchers will have the challenges to work in this area to
provide a concrete solution with minimal computational,
storage overhead, and end to end delay. Looking to this
challenge we tried to propose the new routing algorithm which
will effectively work to reduce all defects of existing scheme
and provide better performance.
III. S
ECURE ROUTE SELECTION MECHANISM
MANET has several security issues and these are
overcome by the many solutions. But there are some
limitations are not overcome. Several routing algorithms
presently working for MANET are suffers from black hole
attack. The performance of the network will be degraded in
presence of an attack. There will be more than one paths are
available on the network, amongst these paths some paths are
with malicious node and some are without malicious nodes.
For selecting an alternate path without malicious node, AODV
routing algorithms has to initiate new route discovery process
but there are many more chances that the malicious node took
part in this process and the issue of selecting secure path is not
solved [22][23]. This route discovery process may decrease
the battery power significantly. If an attack is detected in the
network then there should be some automated mechanism
which will choose the alternate path automatically which will
be reliable and secure. This will promote the use of multipath
routing algorithm for routing purpose. As the there are many
multipath routing algorithms are discovered for MANET.
AOMDV multipath routing algorithm is used to achieve &
solve the black hole attack problem by selecting an alternate
route [24]. There is a number of reasons why we are selecting
AOMDV those are as follows.
1. Less Inter-nodal coordination overheads in
AOMDV.
2. Multiple routes are disjoint.
3. Minimal extra overhead over AODV to
compute the alternate path computes.
4. All paths are a loop-free and disjoint.

2018 Fourth International Conference on Computing Communication and Control and Automation (ICCUBEA)
5. Frequently initiation of new route discovery
is not required in AOMDV required only
when all the existing paths are a break.
6. This reactive routing protocol which
establishing the paths as per requirement, by
transmitting packets to its neighbors.
7. AOMDV selects the ultimate ideal path
amongst all available paths. Optimal path
can be selected on the basis of path property
shortest and least congested path.
A. Secure Route selection algorithm in adverse environment:-
While developing, a proposed approach route reliability
parameter is added. While source node start route discovery
between sources to the destination, this proposed approach
will categories the paths as a reliable or unreliable. Routing
table structure of AOMDV contains various parameters like
destination nodes IP address, destination sequence number,
advertisement hop count, path list, expiration route. The path
list contains information on the path with its hop-count and IP
addresses. Path list consists of the combination of next hop IP
and its count. Routing table structure of existing AOMDV is
shown in table1.
Table1. Routing Table of existing AOMDV
Destination IP address
Destination sequence number
Advertisement hop count
Path list (next hop IP 1, hop-count 1),
(next hop IP 2, hop-count 2),
Expiration Route
Fig1 contains a four node network and the table 2 sows
the path list table of this network. In this existing routing
tables path list table only preliminary information is
available. For idle condition consider network does not
contain any malicious node, for such situations the
existing path list will work properly, but if any malicious
node is present in the network , then it is necessary to add
a parameters which will indicate the status of a path.
Table 2 shows the path list without stating path status.
Fig1. Four node network without any attack
Table2. Path List of fig.1
Addition of a new parameter, in the path list, ensures that the
path is reliable or not. Various paths are discovered at the time
route discovery process. Path status is reliable or not is
updated at the time of route discovery. Presence of Malicious
node in the path decides the reliability of path. If the malicious
node is discovered then the route discovery using that node is
avoided, hence only the reliable paths are discovered and
remain present in the routing table. Status of path is reliable or
not is updated in routing table by adding new parameter
path_sataus. Table 3 shows the structure of AOMDV routing
table with additional parameter.
Table.3 routing table of AOMDV with added parameter
Destination IP address
Destination sequence number
Advertisement hop count
Path list
(next hop IP 1, hop-count 1, path_status
/Reliability, Establish Time),
(next hop IP 2, hop-count 2, path_staus
/Reliability, Establish time),
Expiration Route
After adding this parameter considers that, in above network
shown in fig.1, node B will act as a malicious node then the
network structure will be shown in fig2.
Fig.2.Four node MANET with black hole attack
Table.4 Path List of Fig.2
Node Next
Hop IP
Hop
Count
S A 1
S B 1
S-A-D A, D 2
S-B-D B-D 2
Node Next
Hop IP
Hop
Count
Reliability
/Path Status
S A 1 Reliable
S B 1 Un Reliable
S-A-D A, D 2 Reliable
S-B-D B-D 2 Un Reliable

2018 Fourth International Conference on Computing Communication and Control and Automation (ICCUBEA)
S is source node, D is destination node, and B is marked as a
malicious node, in fig2. In this only one node acts as a
malicious. While discovering paths using AOMDV routing
algorithm it discovers all paths. These paths may or may not
pass through the malicious node. In above network scenario,
paths with malicious node B are also discovered in route
discovery process. Table 4 shows the discovered all routes
with and without malicious nodes. Routing table shows both
reliable and unreliable paths. Black hole detection algorithm
will mark the node B as malicious. The routes pass through
the malicious nodes are labeled as unreliable and the routes
passes excluding malicious node are labeled as reliable as
shown in table 4. These unreliable paths are never used for
secure communication. Only reliable paths are used for
communication in which malicious node is not present. But
while doing this addition of one parameter i.e path_sataus
include in the routing table, it increases the computational and
storage overhead. But it reduces the PDR and end to end
delay. Malicious nodes are responsible for dropping packets so
the PDR in such networks are very less. In above discussed
scenario, routes with malicious node are not used for
communication, since it promises the improvement in PDR is
up to the 100% , which was degraded earlier by only
malicious node and not by other reasons like queue overflow
or node mobility.
Fig.2. network having only single node acts as malicious,
Fig3 considers node B and C nodes are acting as a malicious
nodes.
Fig.3.Six node MANET with two malicious nodes
In this network scenario multiple nodes are acts as a malicious
node. While discovering paths using AOMDV routing
algorithm it discovers all paths. Discovered routes with and
without malicious nodes are shown in table 5. Routing table
shows both reliable and unreliable paths, with node B &C.
Detection algorithm marks the node B & C are malicious
nodes. Route passes with these nodes are labeled as unreliable
and the routes are not passing through nodes B& C are labeled
as reliable as shown in table 5.
Table 5 Path list of fig 3.
These unreliable paths are never used for secure
communication. Reliable routes are selected for
communication since the impact of presence of multiple
malicious nodes in the network is nullified. Routing and
computational overhead is increased due to this additional
path_sataus parameter.
B. Secure Route Selection Mechanism Algorithm
1 Build a network of N Nodes (Design of Manet with
sufficient node)
2Design of Proposed AOMDV Routing Protocol with
added parameter
Step1:
Firstly source node will check the availability
of reliable and recently updated path from
available paths the routing table.
if (path_status ==RP && PET = = Recently)
then
{
Select the path form routing table and transfer
the packet through that route.
}
else
{
Initiate the route discovery process for
discovering new reliable routes
}
Step:2 Creating, validating & updating the reliability
of all the paths by applying various techniques
for attack detection of single/multiple co-
operative black hole attack on the trajectory.
for( i:=1 :i<Path_List;i++)
{
Validate_path_Reliabilty (path[i])
{
For validating and updating the reliability
status of trajectory between source node to
Destination node sends a dummy packet.
If (RACKSFD = = Yes) then
Update the path status = reliable
else
Update the path status = UN_reliable
}
}
Step 3 In this step, proposed AOMDV routing
algorithm selects a more secure and reliable
efficient path amongst the available paths.
RP:- Reliable Path
PET:- Path Establishment Time
RACKSFD: Receives_ACK_to_Source_from Destination
Node Next
Hop IP
Hop
Count
Reliability
/Path Status
S A 1 Reliable
S B 1 Unreliable
S-A-C-D A-C-D 3 Unreliable
S-A-E-D A-E-D 3 Reliable
S-B-E-D B-E-D 3 Unreliable

2018 Fourth International Conference on Computing Communication and Control and Automation (ICCUBEA)
C.Flow Chart Of Secure Route Selection Mechanism
Algorithm.
Fig.4 shows the detailed flow of route selection algorithm
Fig4. Flow chart for Secure Route Selection Mechanism
IV.
SIMULATION RESULTS
This current research work is simulated on multipath routing
protocol AOMDV with single and collaborative black hole
attack in ns2. Number of nodes used here are 10,20,30,40 and
5o. Simulation parameters are shown in Table 6.
Table 6. Simulation parameters.
Parameter Value
Chanel type Chanel/Wireless Channel
radio-propagation model Propagation/TwoRayGround
network interface type Phy/WirelessPhy
MAC type Mac/802_11
interface queue type Queue/DropTail/PriQueue
link layer type LL
antenna model Antenna/OmniAntenna
max packet in ifq 50
number of mobile nodes 10,20,30,40,50
routing protocol AOMDV
X routing protocol
dimension of topography
500
Y dimension of topography 500
time of simulation end 100.0
Comparative study of secure rote selection mechanism with
multipath routing algorithm AOMDV with and without
blackhole attack shows in fig.5. Additional parameter
path_status will helps the network to select only secure route
from source to destination. This additional parameter added to
the routing table increases the routing and computational
overhead. Selection secure route for communication achieves
noticeable improvement in the PDR. PDR is affected by
various parameters like presence of malicious node in network
mobility of nodes, end to end delay and queue overflow.
Fig.5 Impact of single and collaborative Blackhole Attack on
Packet Delivery Ratio Attack
V.
CONCLUSION
Nowadays MANET is globally accepted due to it is
easy to implement anywhere and having additional features.
MANET helps the user to create an ad-hoc network anywhere
instantly, but creating and working smoothly with these
MANET is a challenging task. To overcome these challenges
this paper proposed modification in the structure of AOMDV
routing table. Additional parameter path_status is added for
labeling the paths status. Simulation results show that, only
reliable multiple paths are used for communication. This
scheme significantly resolves the impact of single and
collaborative black hole nodes. It achieves the up to the 100%
PDR at the same time it increases the computational & storage
overhead.
VI.
FUTUREWOR K
As a future work we are going to apply the same
algorithm for detection of one & various another kind of
attack individually and in combination too, to resolve all types
of attacks from the MANET and provide a robust solution for
secured routing algorithm. By Adding another parameter in
the routing table we can discover the energy efficient routing
algorithm with security measure with and without considering
the various factors like mobility, etc.
VII.
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