S IMULATION B ASED S TUDY OF C OOPERATIVE B LACK H OLE A TTACK R ESOLUTION USING C ROSS - C HECKING A LGORITHM

International Journal on AdHoc Networking Systems ( IJANS) Vol. 5, No. 2, April 2015
DOI : 10.5121/ijans.2015.5202 17
SIMULATION BASED STUDY OF COOPERATIVE
BLACK HOLE ATTACK RESOLUTION USING CROSS-
CHECKING ALGORITHM
Garima Gupta1
and Atul Mishra2
1
Department of Computer Engineering, YMCA University of Science & Technology,
Haryana, India
2
Department of Computer Engineering, YMCA University of Science & Technology,
Haryana, India
ABSTRACT
An Ad hoc Network is a pool of wireless mobile nodes energetically forming a network without the use of
any pre-accessible network infrastructure or centralized administrator. These nodes communicate with
each other by hop-to-hop communication. This dynamic topology of mobile ad-hoc networks (MANETs)
allows nodes to get attached and leave the network at any second of time. Thus MANET can be used in a
variety of fields. Current MANETs are designed primary for military utility. This generic characteristic of
MANET has rendered its vulnerability to security attacks. Due to which unprotected attacks of the
malicious nodes can occur at any time. This paper focuses on one such attack known as “Black hole
attack” and the routing protocol being used here is AODV.
KEYWORDS
MANET, Black Hole Attack, AODV, Cross-Checking, Mobile Node.
1. INTRODUCTION
Irrespective to the infrastructure wireless networks [1], a mobile ad hoc network is a type of
wireless ad hoc network which is a self organizing network of mobile devices linked by wireless
links with no base station in between. Every mobile node in a network is autonomous. The mobile
devices are free to move and organize themselves. In other words, ad hoc network do not rely on
any fixed infrastructure. The Communication in MANET is take place by using multi-hop paths.
Nodes in the MANET share the wireless medium and the topology of the network changes
erratically and dynamically. In MANET, breaking of communication link is very frequent, as
nodes are free to move to anywhere. The density of nodes and the number of nodes are depends
on the applications in which we are using MANET.
However, due to their inbuilt feature of vibrant topology and lack of centralized management
security, MANET is open to various kinds of attacks. These include grey hole attack, warm hole
attack, black hole attack and the denial-of-service attack. The main protocols in MANETs include
the following ones.
a) Proactive or Table Driven like DSDV (Destination Sequence Distance Vector Routing)
b) Reactive or On Demand like AODV (Ad hoc On Demand Vector Routing)
c) Hybrid like ZRP ( Zone Routing Protocol)

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The packet dropping attack thus described in this paper is Black Hole node attack in which a
malicious node absorbs the data packet in itself, similar to the black hole in the universe which
absorbs everything that comes to it. In this way, the packets in the network are either dropped or
absorbed. A malicious node that drops all the traffic in the network makes use of all the liabilities
of all the route discovery packets of the on demand protocol such as AODV [2].
A black hole node is a node that always replies affirmatively with a RREP message to every
RREQ, even though it does not have a genuine route to the destination node [2].When the data
packet reaches the black hole node, it drops them rather on forwarding them. It was quiet easy
and well simulated to work on a single black hole node but a method is needed to be finding out
to identify, avoid and drop the cooperative black hole nodes.
The rest of the paper is organized as follows. In section 2 the literature review related to black
hole attack has been presented. Section 3 comprises of the cooperative black hole attack with the
cross check algorithm to implement it and all the simulation scenarios. Section 4 consists of the
result having graphical outputs that shows the throughput and delay. Conclusion is then provided
in section 5.
2. LITERATURE SURVEY
There certainly have been several attempts available in the literature that aims at removing the
black hole attacks. We review them as follows.
Vipan et al. [3] discuss the problem of improving the security as in existing AODV there is no
provision against well known black hole attack. And the network degradation problem is also
discussed here. Solution so proposed here is the modification in working of source node by a
method called Prior Receive reply. Malicious node is identified by using two methods: 1. Route
table 2. Waiting Time. So a simple and efficient approach for defending against black hole attack
has been used. This method can be used to find out the secure routes and preventing the black
hole nodes in MANETs by identifying their sequence number. Check is done on the difference
between the sequence number of source or intermediate node who has sent the RREP back.
Sanjay Ramaswamy et al. [4] proposed the problem of coordinated black holes acting in group. It
proposed a solution by discovering the safe route avoiding these black holes. Modification is done
by using data routing information table (DRI) and cross checking. It thus identifies the multiple
black hole nodes acting in group, discovers secure path from Source to destination by avoiding
these. As a future work they need simulation technique for this.
Rajib Dasi et.al [5] thus addresses the problem of addressing and removing the black hole nodes
in beginning such that no packet is lost or retransmitted. An additional route to intermediate node
is discovered that replies the RREQ message to check whether the route from intermediate node
to Destination node exists or not is maintained. When source node receives FRp from next hop
node it extracts to check results from reply packet. If result is yes then a route is established else
discarded.
Marti et al. [6] proposed a scheme named Watchdog. It aims to improve the throughput when
malicious node is present in the ad hoc network. It mainly consists of two parts -Watchdog and
Path rater. Watchdog detects the misbehavior in the network while the Pathrater finds a new route
to the destination excluding that malicious node by cooperating with the routing protocol. It
listens to its next node transmission; it maintains a buffer which stores the packet in it and a
failure counter. If a node forwards the packet to its neighbor then that packet is deleted from its
buffer else it increases the value of its failure counter. If the value of the counter exceeds the pre

19
defined threshold then that node is declared as malicious and now Pathrater finds the new route to
the destination. It detects the malicious node in the network instead of malicious links. There are
six weaknesses that are mentioned by Marti [6]. They are:
1) Receiver Collision problem
2) Ambiguous collision
3) Limited Transmission power
4) False misbehavior
5) Collusion
6) Partial Dropping.
Liu et al [7] proposed the TWO ACK scheme. This scheme aims to resolve the limited
transmission power and receiver collision problem of the Watchdog. But it is not an improvement
or enhancement of the Watchdog scheme proposed by Marti. It detects the misbehaving links by
making the nodes send an acknowledgment packet to every third node down the route, which
means upon receiving the data packet every third node in the route from source to destination is
required to send an acknowledgment packet to the node two hops away down the reverse route.
Elhadi M. Shashuki et al [8] [9] proposed a new approach called EAACK that solves three
weaknesses out of six weaknesses of the Watchdog scheme. It solves false misbehavior problem,
limited transmission power and receiver collision problem. It makes use of the digital signature to
ensure the legitimacy of all the acknowledgment packets. By using the digital signature it
prevents the attacker from forging the acknowledgments.
Songbai Lu et at [10] [11] proposed SAODV that resolves the problem of security measures that
arises in AODV protocol. Here in it, a random number is generated by the source node and is
send in every RREQ message. If the same random number is received by destination from more
than two different paths than it sends a RREP message to source node that contains another
random number. Same process is followed by source node for verification. If the random number
is same as the previous one than the path is secure and data can be transmitted over that path.
Ms. Nidhi Sharma et al [12] proposed two possible solutions for prevention of black hole attack
in MANET. First solution suggests finding more than one route to destination node by finding the
authenticity of the node that initiates the RREP message. In it RREP packet has to be received
from at least more than two nodes. During this time the source node than buffer its packets until
the safe route is discovered. Main drawback in this approach is time delay.
The second approach suggests that every packet has a unique sequence number having the value
always greater than the precedence node. In it, every node has to maintain two small sized tables.
These tables are updated whenever any packet is arrived or transmitted. Packet authenticity is
checked by the higher sequence number and its comparison from the precedence one. It has
benefit of having more reliability and no overhead.
Shambhu Upadhyaya et al[13] addresses the problem of colluding and coordinating black hole
attack which then leads to the loss of all the necessary and critical information transmitted all over
the network. It thus provides a solution to overcome this problem by introducing multipath
routing schema. It uses the ACK (acknowledgement) packets being transmitted first to check for
the validity of the path. These packets thus establish the secure path and data can then be
transmitted successfully over that path. Furthermore, this approach is implemented on network
simulator with the graphs showing the data packets their mobility, control packets and the packets
lost and the packets routed to another node.

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Kishor jyoti Sharma et al [14] presents a survey of various attempts and techniques that are
established till date for identification and removal of black hole and cooperative black hole nodes.
Such attempts are listed as:
1) DRI table and Cross Checking scheme
2) Time-based threshold detection scheme[15]
3) Detection, Prevention and Reactive AODV scheme[16]
4) Nital Mistry et al.’s method[17]
5) Hash based scheme[18]
6) Neighborhood-based and routing recovery scheme[19]
7) Trust table Method[20]
8) Secure AODV[13]
9) Optimized Black hole Detection and Prevention Algorithm[21]
3. SIMULATED STUDY OF COOPERATIVE BLACK HOLE ATTACK
RESOLUTION
3.1 BLACK HOLE ATTACK
A kind of denial of service where a malicious node can attract all packets by untruely claiming a
new route to the destination and then absorb them without forwarding them to the destination is a
black hole attack.
In fig. 1 the node 1 and the node 4 are source and destination nodes resp. while the node 3 is the
black hole node that absorbs the data packets. Here node 3 first of all sends the RREP (route
reply) so that all the data packets can be transmitted over that.
Fig. 1 Black Hole Attack in MANET

3.2 COOPERATIVE BLACK HOLE
Researchers have given many solutions to identify and eli
However, in case of multiple cooperative
been provided.
For example, [4] as shown in fig. 2, source node S wants to transmit data packets to destination
node D. It first broadcasts a RREQ to intermediate node IN. IN being a
with the RREP message and always refers to other
destination. Source node then checks for the reliability of that
further request Freq. to coordinated
another black hole it will always reply with a Further reply FRp. With that confirmation S starts
sending the data packets to H. However, in reality, the packets are consumed by node B1 and the
security of the network is on conciliation
3.3 CROSS- CHECKING ALGORITHM
The following task is being carried on
1. The source node (SN) broadcasts a RREQ message in conquest to discover a safe
destination node.(DN)
2. The Intermediate Node (IN)
(NHN) and its DRI entry for the NHN.
3. Now, the source node will check its DRI table for the reliability of IN.
4. If the result is yes, then the
message from NHN, source node checks whether NHN is a reliable node or not
LACK HOLE ATTACK
solutions to identify and eliminate a single black hole node.
in case of multiple cooperative black hole nodes no efficient and reliable solution has
Fig. 2 Cooperative Black hole node attack problem
as shown in fig. 2, source node S wants to transmit data packets to destination
. It first broadcasts a RREQ to intermediate node IN. IN being a black hole H replies first
EP message and always refers to other black hole H having the shortest path to
destination. Source node then checks for the reliability of that black hole node H via. Sending
to coordinated black hole via. Different route. As H is in coordination with
it will always reply with a Further reply FRp. With that confirmation S starts
However, in reality, the packets are consumed by node B1 and the
conciliation.
LGORITHM
task is being carried on [4] as shown in fig. 3.
SN) broadcasts a RREQ message in conquest to discover a safe
) generates the RREP which has to provide its Next Hop Node
(NHN) and its DRI entry for the NHN.
the source node will check its DRI table for the reliability of IN.
If the result is yes, then the source node sends Freq message to NHN. Based on the Fre
node checks whether NHN is a reliable node or not.
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node.
nodes no efficient and reliable solution has
as shown in fig. 2, source node S wants to transmit data packets to destination
H replies first
H having the shortest path to
black hole node H via. Sending
coordination with
it will always reply with a Further reply FRp. With that confirmation S starts
However, in reality, the packets are consumed by node B1 and the
SN) broadcasts a RREQ message in conquest to discover a safe route to the
has to provide its Next Hop Node
message to NHN. Based on the Frep

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5. If IN is not a black-hole and NHN is a reliable node, the route is secure, and source node will
update its DRI entry for IN with 01, and starts routing data via IN.
6. If IN is a black-hole, the source node identifies all the nodes along the reverse path from IN to
the node that generated the RREP as black hole nodes. Source node ignores any other RREP
from the black holes and broadcasts the list of cooperative black holes.
Algorithm to prevent cooperative black hole attack in MANETs
Notations:
SN: Source Node IN: Intermediate Node
DN: Destination Node NHN: Next Hop Node
Freq: Further Request Frep: Further Reply
Reliable Node: The node through which the SN has routed data
DRI: Data Routing Information
ID: Identification of node
1 SN broadcasts RREQ
2 SN receives RREP
3 IF (RREP is from DN or a reliable node) {
4 Route data packets (Secure Route)
5 }
6 ELSE {
7 Do {
8 Send Freq and ID of IN to NHN
9 Receive Frep, NHN of current NHN, DRI entry for
10 NHN's next hop, DRI entry for current IN
11 IF (NHN is a reliable node) {
12 Check IN for black hole using DRI entry
13 IF (IN is not a black hole)
14 Route data packets (Secure Route)
15 ELSE {
16 Insecure Route
17 IN is a black hole
18 All the nodes along the reverse path from IN to the node
19 that generated RREP are black holes
20 }
21 }
22 ELSE
23 Current IN = NHN
24 } While (IN is NOT a reliable node)
25 }
Fig. 3 Cross-Checking Algorithm
3.4 SIMULATION SCENARIO
In the simulation scenario, the following design issues are considered.
a) Simulation Environment
b) Simulation Metrics
c) Simulation Scenarios

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3.4.1 SIMULATION ENVIRONMENT
The simulator used here is NS2 i.e. the working environment is NS2. Protocol used here is
AODV. Rest of the parameters are shown in tabular form as in Table 1.
Table 1: Simulation Parameters
S.No. Parameters Value
1. No. Of nodes 20
2. Simulation area 900X900 meter
3. Simulation Time 30 sec
4. Mobility Model Random waypoint 0
5. Packet size 1000 byte
6. Traffic Type CBR
7. Packet rate 4/sec
8. Protocol used AODV
The simulation here is conducted on NS2 platform with number of nodes being used is
20(variable). Simulation area is 900X900 meter with the core of Ubuntu 10.4.
3.4.2 SIMULATION MATRICES
The simulation here is done on the basis of the following parameters:
1) Throughput: It basically describes the ratio of total packets sent to the total packets received
in prescribed simulation time depending on the no. of malicious nodes present here.
2) Delay: Here, in this parameter the delay factor is taken under consideration in which the total
time is calculated. Total extra time the packet takes to reach to the destination is termed as
delay.
3) Overhead: It provides all the information that tells about the routing just like the route reply
and route request.
4) Packet Delivery Ratio: PDR tells the ratio of total number of packets sent from the source
node to the destination node via. Intermediate node.
3.4.3 SIMULATION SCENARIOS
The simulation of following scenarios has been done.
1) Network Simulation with No Black hole
In this case no black hole has been taken. So maximum packets send are received by the
destination. Thus no packet is dropped or lost in the midway. This then leads to maximum
throughput and almost zero delay.
2) Network Simulation with Single Black hole
In this scenario a single black hole is introduced. Keeping the other parameters same. Now due to
the single black hole some packets are lost and dropped. This then leads to packet retransmission.
Here in this case the threshold is reduced to some extent and so the delay is increased.
3) Network Simulation with Cooperative Black hole
In this scenario a cooperative black holes are introduced. Keeping the other parameters same.
Now due to the single black hole some packets are lost and dropped. But due to cooperative black

24
holes more packets are dropped and lost. They thus can’t reach the destination. This then leads to
the energy lost and packet retransmission. In this case the threshold is further more reduced and
so the delay is increased.
4) Cross Checking Algorithm Implementation
Now to improve the throughput and lessen the delay cross checking algorithm as provided in [4]
is implemented in NS2.
In this the simulator continuously checks for the black hole node and when satisfied by the route
sends the data packets else discards the route. This algorithm thereby, increased the throughput
value and lessens the delay furthermore.
4. RESULTS
The graphical representation and simulation scenario is shown below:
SCENARIO 1: NETWORK SIMULATION WITH NO BLACK HOLE
Fig. 4 Simulation Screen Fig.5 Nam Window
Fig.6 Throughput graph Fig.7 Delay graph

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The graphs show that with no black hole we get a maximum value of throughput and almost no
delay. In this case all the packets send by the sender reaches the destination accurately i.e. there is
no packet loss.
Fig. 4 shows the simulation screen in which 50 packets are sent and received properly. Here, in
this the packets are transmitted between the source and destination with no malicious node. Fig. 5
shows the NAM window for the above simulation showing the absence of any malicious node i.e.
black hole. Fig. 6 shows the variance between the throughput and time. As there are no black
holes present so the throughput value reaches to 100% in this scenario. Thus, all the packets reach
the destination properly and fig. 7 shows variance between the delay and time. With little
environmental factors such as noise or distortion the delay variance is approx. 0.2%.
SCENERIO 2: SINGLE BLACKHOLE
Fig.8.Simulation screen
Fig.9 Nam Window
Fig. 10 Throughput graph Fig.11 Delay graph

26
The graphs show that with a single black hole some of the packets reaching the destination are
lost. As a result, a variation in value of throughput is seen and delay is somewhat increased also.
In this case all the packets send by the sender does not reaches the destination accurately. That
leads to dropping of throughput value.
Fig. 8 shows the simulation screen in which 50 packets are sent but, all packets are not received
properly. Fig. 9 shows the NAM window for the above simulation showing the presence of single
malicious node i.e. black hole. Fig. 10 shows the variance between the throughput and time. As
there is single black hole present so the throughput value decreased to 97% in this scenario. Fig.
11 shows variance between the delay and time. With more retransmissions delay is increased upto
2%.
SCENERIO 3: COOPERATIVE BLACK HOLE
Fig.12 Simulation Screen Fig.13 Nam Window
The graphs show that with cooperative black hole more packets reaching the destination are lost.
As a result, a variation in value of throughput is seen and delay is somewhat increased also. Here,
in this case, all the packets send by the sender does not reaches the destination accurately. That
leads to more dropping of throughput value. Value almost decreased to 70%.

27
Fig. 12 shows the simulation screen in which 50 packets are sent but, all packets are not received
properly. Fig. 13 shows the NAM window for the above simulation showing the presence of
single malicious node i.e. blackhole. Fig. 14 shows the variance between the throughput and time.
As there are cooperative blackholes present so the throughput value decreased to 70% in this
scenario i.e. more packets are lost and more retransmissions are required. Fig. 15 shows variance
between the delay and time. With more retransmissions delay is increased considerably.
SCENARIO 4: CROSS-CHECKING ALGORITHM IMPLEMENTATION
This graph shows that value of the throughput is decreasing and increasing because it searches for
the best route avoiding the black holes.
Using the above strategy the delay also lessens and we get less value of delay. Fig. 16 shows the
variance between throughput and time. This variance is a bit irregular because this algorithm tries
to find the safe route on the basis of DRI entry of each node. So the throughput value is increased
upto a considerable amount by using this approach i.e. 80%. Fig. 17 shows the variance between
delay and time. Due to this better approach, delay variance comes out to be approx. 0.01565%.
5. CONCLUSION AND FUTURE WORK
In this paper, the detailed study about the cooperative black hole attack is done. When black holes
attack in a group they decrease the throughput value and increase the delay. So for this, certain
scenarios are implemented. First of all, a neutral case is taken where there is no black hole , then a
single black hole is introduced in the network and lastly multiple black holes are introduced
which work in coordination with each other. Simulation of all these cases is taken graphically. As
a solution to this problem, cross- checking algorithm is implemented, which in return results in
increase throughput and lower delay value. But the major drawback with the above implemented
algorithm is that the delay value is always constant whatsoever the case. Moreover, throughput
value is not very much increased.

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As a future work we intend to develop an algorithm that will enhance the throughput and will be
more efficient and feasible than the given algorithm.
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