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Proceedings of the 12th INDIACom; INDIACom-2018
5th 2018 International Conference on “Computing for Sustainable Global Development”, 14th – 16th March, 2018
Bharati Vidyapeeth’s Institute of Computer Applications and Management (BVICAM), New Delhi (INDIA)
BLACKHOLE ATTACK ON MANET AND ITS
EFFECTS
Abhilash Singh
M.Tech Student, Dept. of CS&IT,
Assam Don Bosco University
Guwahati, India
Kaustav Pratim Kalita
Assistant Prof., Dept. of CS&IT,
Assam Don Bosco University
Guwahati, India
Smriti Priya Medhi
Assistant Prof., Dept. of CS&IT
Assam Don Bosco University
Guwahati, India
Abstract – Mobile ad hoc network (MANET) is an
infrastructure less, temporary and dynamic network. MANET
is known to have large set of applications in the field of
computer networks. But, MANET is also prone to many
attacks due to the unavailability of centralized management
security, lack of security mechanism in routing protocol and
open media. Black hole attack is one of the most well-known
security threats in MANET. In black hole attack, a malicious
node attracts packets from source by advertising itself having
the shortest route to the destination and then discards all the
incoming packets. In this paper, we have discussed various
researches done on black hole attack on MANET and
produced a comparative study of the different researches. We
also performed the black hole attack on MANET and
analyzed the effects of the attack based on different
parameters like end to end delay, PDR, packet loss and
throughput. Our analysis is performed on NS2 simulator
where AODV is used as the routing protocol.
Keywords: Blackhole, MANET, AODV, Routing Protocol
.
I. INTRODUCTION
Mobile ad hoc network also known as MANET is a network
where there is no infrastructure and centralized management
system. The devices in MANET interact to each other without
any external routers or access points. The nodes in MANET
can act as a router, source and destination. MANET is either
single hop networks or multiple hop networks [1,2,3]. In single
hop the nodes can directly communicate to each other but in
multi hop network communication takes place through
intermediate nodes as shown in figure 1. Routing protocols are
used to find routes in MANET. Routing protocols in MANET
come under three categories Reactive, Proactive and Hybrid.
Reactive protocols are used only whenever sender wants to
communicate with receiver and then, route discovery procedure
is used to find the shortest route to destination [6]. In proactive
routing protocols on the other hand each node maintains
routing information which continuously gets updated
periodically. Hybrid protocol on the other hand is a mix of
both reactive protocol and proactive protocol. MANET has a
broad set of applications. MANET are used in military
purpose, during natural calamities, WSN, in various business
related work and many more.
Figure 1: Example of MANET
A. ATTACKS IN MANET
MANETs are prone to many attacks due to the unavailability
of centralized management security, lack of security
mechanism in routing protocol and open media. Attacks in
MANET are classified in two types [9]
a) External Attack: In this type of attack the attacking
node doesn’t belong to the network.
b) Internal Attack: The malicious node belongs to the
domain of the network.
Different Layer of MANET and their corresponding attacks
are shown in the below figure 2
Proceedings of the 12th INDIACom; INDIACom-2016
5th 2016 International Conference on “Computing for Sustainable Global Development”, 14th – 16th March, 2016
Figure 2: ATTACKS IN MANET
B. ADHOC ON DEMAND DISTANCE VECTOR (AODV)
AODV is an on demand/Reactive routing protocol in MANET.
AODV generally uses bidirectional links. AODV provides
unicast communication and Multicast communication. AODV
uses sequence number to prevent looping and as a criteria to
route freshness. AODV protocol discovers routes and maintains
the routes when necessary and it doesn’t maintain routes from
one node to other nodes. In AODV, sequence number is
maintained by every node and every time there is a change in
neighborhood network the nodes monotonically increases their
sequence number Routing tables are used in AODV to store
routing information. The routing table has parameters like
address of destination, sequence number of destination, address
of next hop and life time. Route discovery process in AODV
begins when a sender’s device wants to communicate with
receiver device. The sender first checks its routing table to find
any available route to destination, if the nodes find an existing
route it sends data to next hop and so on. And if the node does
not find any route its starts the route discovery procedure. In
route discovery process, the sender/source node first broadcast
a RREQ (Route Request) packet to all its intermediate nodes.
After receiving the RREQ packet the intermediates nodes
maintains a reverse route table which contains the sender’s
information. Using reverse route table a node can send back the
RREP (Route Reply) packet to the sender node. When RREQ
packet reaches the receiving/destination node and the IP
address of the destination node and other conditions are
matched with the RREQ packet then the destination node reply
by sending RREP packet. If all the conditions are not matched,
the node again broadcast that RREQ packet to its neighbor
node [8].
C. BLACKHOLE ATTACK
In blackhole attack a node is said to be blackhole node when it
attracts packet from source by describing itself having the
shortest route to destination and a fresh route to reach the
destination. Blackhole node also can impersonate itself to be
the destination node by sending a spoofed route reply packet
to a source node that initiates a route discovery
II. LITERATURE SURVEY
In this paper [1] the author has used an enhanced standard
AODV protocol for the detection of Blackhole nodes in the
network. The author in his proposed methodology has used
CRRT table at the source node. The main objective of the
CRRT table is to store the incoming route replies. The entries
in the table have the following fields: source address,
destination address, hop count, next hop, destination sequence
number and lifetime. Here, the author has applied threshold to
determine any blackhole attack. In the Proposed approach the
PDR value decreased by 94.1% when there is Blackhole node
in the network but the PDR value is found to be increased by
96.3% using the proposed algorithm. The throughput is
increased by 333.9 KBPS which was drop by 310.13KBPS in
the presence of Blackhole attack.
[2]In this paper the authors have used a modified DSR
protocol for the detection of Blackhole nodes. First a MANET
is setup. Source and destination node are selected and the
route is established. The proposed methodology will detect
multiple Blackhole nodes based on the packet loss of the
network. When number of packets dropped is exceeding
particular value and performance of network starts
deteriorating then the network will start detecting the
blackhole node and rest of the nodes present in the network
will be informed of the black hole nodes, thereby isolating
them from the network. It is observed that network load of the
network in presence of the black hole attack considerably
incremented and enhancing the performance of the network
and the packet loss is decreased.
[3] In this paper Aman saurabh et. al proposed a solution to
identify and isolate blackhole node in MANET. In the
proposed plan, the network is deployed with finite number of
mobile nodes. A source node is selected randomly. The source
node sends bogus RREQ message to all its neighbor nodes.
The fake RREQ message contains a bogus destination number.
If the source node receive reply from any node then it put that
node into its malicious node list. If the source node doesn’t get
any reply then it sends genuine RREQ message for route
establishment. After placing the malicious node into malicious
list, Knowledge based learning is applied to confirmed the
attacker. After the confirmation the malicious node is isolated.
[4]Rashmi et al. has perform a comparison study between
modified DSR approach and their proposed approach in
BLACKHOLE ATTACK ON MANET AND ITS EFFECTS
which the deployed nodes are divided into clusters such that
each cluster having a cluster head and the remaining nodes are
the members of that cluster. The cluster head is chosen
randomly from each cluster. Check-points are deployed in the
network to check whether the number of data packets received
by the nodes and number of packets sent by the nodes are
equal. Packets transmission can take place from within cluster
or from any cluster where source node is located. If the
probability of packets received at destination is more than
threshold the node is move to suspected list. The experiment is
performed over ns2. Detection rate is found to be 3 times that
of modified DSR approach. Through is also found to be
considerably high in cluster approach than that of modified
DSR approach. PDR was also improved.
[5] In this paper the author Amanpreet et. al has used scheme
called HOOSC scheme. This scheme uses six algorithms to
secure data before transmission. The six algorithms are SET-
UP, IBC-KG, PKI-KG, On sign crypt, off sign crypt, unsign
crypt. These algorithms will encrypt the data before sending to
destination node. The intruders will fail to read the content of
the packets. Using HOOSC scheme [9] a sender in Identity
based cryptography sends the data to the destination which is in
Public key infrastructure.
Table 2 Comparison table of above research papers
Scheme
Routing
Protocol
Detection
Type
Results
Defects
Enhanced
AODV
protocol [1]
AODV
Single,
multiple
Blackhole
nodes
detection
PDR increased
by 96.1% and
Throughput
increased by
333.5kbps
Failed to detect
collaborative
Blackhole attack
Modified
DSR
protocol [2]
DSR
Multiple
Blackhole
nodes
detection
Packet loss is
decreases with
the new scheme
Network load
increases with
Blackhole attack is
observed.
Knowledge
based
Learning [3]
AODV
Single,
multiple
blackhole
detection
End-to-End
delay and packet
loss is less
Failed to detect
collaborative
Blackhole attack
Simple
acknowledge
ment scheme
[4]
AODV
Single,
Multiple
detection
PDR and
Throughput are
increased
considerably
Failed to detect
collaborative
Blackhole attack
HOOSC
Scheme[5]
AODV
Single,
Multiple
Detection
Encrypted Data.
Encryption leads to
increased overhead
III. EXPERIMENTAL SETUP AND RESULTS
To analyze the impact of Blackhole attack in MANET, we have
used NS-2 network simulator. The simulations are carried out
on Xubuntu. AODV is used as routing protocol. Slight
modification has been done on AODV protocol in order to
give 3 nodes the blackhole properties. In total 25 nodes are
used. The simulation topology is show in figure 3.
Figure 3: Simulation Topology
In our topology there are 3 blackhole nodes ( 1, 7, 13) 1 source
node (21) and a destination node (17). We ran the simulation
for 5 seconds.
Figure 4: Nodes communicating to each other
End-to-end delay is the time taken for a packet to be
transmitted across a network from source to destination. The
end to end delay graph clearly shows the delay suddenly
increasing as soon as the blackhole attack started [11].
Proceedings of the 12th INDIACom; INDIACom-2016
5th 2016 International Conference on “Computing for Sustainable Global Development”, 14th – 16th March, 2016
Figure 5: End to End Delay
Packet Delivery Ratio (PDR): Total number of packets
received by the destination node with respect to total number of
packets originated by source node is defined as the Packet
Delivery Ratio.
Figure 6: Packet Delivery Ratio
When one or more packets of data fail to reach their
destination, the phenomenon is termed as packet loss. [10].
Figure 7: Packet Loss
Throughput: In a given simulation time, the number of
packets delivered to destination is known as throughput [1].
Figure 8: Throughput
IV. RESULTS & DISSCUSSION
From the generated graph after the experiment we can see the
impact of blackhole attack on our simulated MANET
topology. In figure 5 we can see that initially there was no
delay but after some point of time there was a constant rise in
the end to end delay due to the blackhole attack. In figure 6
the PDR value was initially was very high but again as soon as
BLACKHOLE ATTACK ON MANET AND ITS EFFECTS
the malicious node started attracting packets the PDR falls to
zero. In figure 7 a high packet loss is detected due to blackhole
attack. In figure 8, throughput also can be seen falling to zero
level when the malicious node started working. So from all
these different performance matrices we can get some idea of
the impact of blackhole attack on MANET.
V. CONCLUSION AND FUTURE SCOPE
A lot of researches have already been done on detecting and
preventing the menace of blackhole attack in wireless network.
But due to the lack of security mechanism in MANET,
blackhole attack is still a huge challenge for both researchers
and users. In this paper we have studied many research works.
In the comparison table, we found out that many detection
algorithms failed to detect collaborative blackhole attack in
MANET. In this paper we also analyze the impact of blackhole
attack in MANET based on different performance matrices. In
our future works, we will try to come up with an approach to
detect and prevent collaborative blackhole attack in MANET.
REFERENCES
[1] Vimal Kumar, Rakesh Kumar “An Adaptive Approach for
Detection of Blackhole Attack in Mobile Ad hoc Network”.
International Conference on Intelligent Computing,
Communication & Convergence (ICCC-2014) Procedia
Computer Science 48 (2015) 472 – 479
[2] Barleen Shinh, Manwinder Singh “Detection and Isolation
of Multiple Black Hole Attack Using Modified DSR”
International journal of Emerging Trends in Science and
Technology IJETST- Volume 01 Issue 04 Pages 540-545 June
ISSN 2348-9480 2014
[3] Aman Saurabh ,Rakesh Yadav , Harjeet Kaur “Identifying
& Isolating Multiple Black Hole Attack on AODV protocol in
MANET” International Journal of Innovative Research in
Science, Engineering and Technology (An ISO 297: 2007
Certified Organization) Vol. 4, Issue 5, May 2015
[4] Rashmi , Ameeta Seehra “Detection and Prevention of
Black-Hole Attack in MANETS” International Journal of
Computer Science Trends and Technology (IJCST) – Volume 2
Issue 4, Jul-Aug 2014
[5] Mehak Kaushal, Gunjan Gandhi“Detection Prevention and
Mitigation of Blackhole Attack for MANET” International
Journal of Engineering Research & Technology (IJERT) ISSN:
2278-0181 IJERTV4IS041484 Vol. 4 Issue 04, April-2015
[6] Nital Mistry, Devesh C Jinwala, Mukesh Zaveri “Improving
AODV Protocol against Blackhole Attacks” International
MultiConference of Engineers and Computer Scientists, Hong
Kong, 17-19 March, 2010
[7] https://www.ietf.org/rfc/rfc3561.txt
[8] https://www.cs.jhu.edu/~cs647/aodv.pdf
[9] https://www.slideshare.net/sunitasahu101/attacks-in-manet
[10] https://en.wikipedia.org/wiki/Packet_loss
[11] https://en.wikipedia.org/wiki/End-to-end_delay
