Distributed security system for mobile ad hoc computer networks

ISSN:2249-5789
Krutika K Chhajed et al , International Journal of Computer Science & Communication Networks,Vol 5(3),184-191

Distributed Security System for Mobile Ad-Hoc Computer
Networks
Ms.Krutika K. Chhajed
Department of Computer Science & Engg.
PRMIT & R, Badnera

Abstract—
Ad-hoc wireless networks are increasing in popularity,
due to the spread of laptops, sensor devices, PDAs and
other mobile electronic devices. These devices will
eventually communicate with each other and hence there
is a need of security in MANETS.This paper describes the
different types of attacks that are very common i.e. the
Distributed Denial of Service attack, the Blackhole attack
and the Wormhole attack, also provide the mechanism to
detect these attacks using the different techniques and the
relative comparison between these three attacks. It
provides a comparison of some of the common
parameters on the different nodes in these different types
of attack scenario. So that a novel and optimum solution
can be provided, this can secure the nodes from different
types of attacks.
Keyword: MANET, DDoS attack, Blackhole, Wormhole
attack.
INTRODUCTION
Ad-hoc wireless networks are increasing in popularity,
due to the spread of laptops, sensor devices, PDAs and
other mobile electronic devices. These devices will

eventually need to communicate with each other.
However there is a need to implement a secure ad hoc
network that might be used in emergency services,
disaster assistance, and military applications. The security
includes controls to limit access to the network, in order to
protect it from intruders or unwanted bystanders. Mobile
Ad hoc Networks are the networks formed for a
particular purpose. These networks assume that an end
to end path between the nodes exists. They are often
created on-the-fly and for one-time or temporary use.
They find their use in special applications like military,
disaster relief etc that are in a need of forming a new
infrastructure less network with all pre-existing
infrastructure being destroyed. [2]
The basic working of MANETS is such that every node is
independently working and only keeping the routing
information with respect to other node, it becomes
difficult for the node to keep track of each and every node
entering and leaving the MANET and hence it becomes
very easy for an unintended node to enter into the
MANET and attack the network to disrupt the normal
working. Implementing security in MANET is a
challenging task. Because here node itself will be acting
as a router node. So identifying neighbor node as a
legitimate node or malicious node is a difficult thing in
MANET. [3]Thus security of the data is the most
important aspect to be handled when dealing with
MANETS.
A Mobile Ad hoc Network (MANET) is a collection of
mobile node connected through wireless links.

Dr. M. S. Ali
Principal,
PRMCEAM, Badnera

[3].The MANETS are different from the traditional
infrastructure based networks in the way that there are
nodes which are mobile. And hence the challenges in such
networks are different from traditional infrastructure
based networks.
Security Challenges in MANETS:
a) Dynamic Topology: the nodes are moving and may
leave or join the network dynamically. Establishing
the trust among the network nodes is difficult.
b) Battery constraints: the nodes are mobile and work
on battery so power consumption must be less.
c) Lack of Central authority: In MANETS there will be
no central authority. So to implement security is a
challenging task.
d) Insecure Environment: the nodes are continuously
moving so it is difficult to find out the malicious
nodes which can attack and steal the data. [1]
In Ad hoc networks every node act as the sender receiver
and also as a router because it lacks the central authority.
The routing protocols are needed for transmitting the data
from source to destination using multiple hops.
There are two basic suggested approaches for
routing in MANETS. These are Topology Based Routing
and Position Based Routing. Topology-based routing
protocols use the information about the links that exist

in the network to perform packet forwarding. They can be
further divided into proactive, reactive, and hybrid
approach Position-based routing algorithms eliminate
some of the limitations of topology-based routing by
using additional information. They require that information
about the physical position of the participating nodes be
available. Commonly, each node determines its own
position through the use of GPS or some other type
of positioning service. A location service is used by the
sender of a packet to determine the position of the
destination and to include it in the packet’s destination
address.
Attacks in MANETS
Table1 gives a few examples of attacks at each layer.
Some attacks could occur in any layer of the network
protocol stack, e.g. jamming at physical layer, hello flood
at network layer, and SYN flood at transport layer are all
DoS attacks.
Table 1: Attacks occurring at different layers in protocol
stack
Layer
Attacks
Application Layer
Transport Layer
Network Layer

data corruption, viruses and worms
TCP/UDP SYN flood
hello flood, blackhole

Data Link Layer

monitoring, traffic analysis

Physical Layer

eavesdropping, active interference

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ISSN:2249-5789
Krutika K Chhajed et al , International Journal of Computer Science & Communication Networks,Vol 5(3),184-191

The network layer attack on ad hoc networks can be
broadly classified into two categories one based on source
of attacks [17] i.e. External and internal attacks and the
other based on the behavior of attack i.e. active and
Passive attacks.
In external attack, attacker from outside the network tries
to get the access to the current network and once it
becomes the part of the network, interrupts the ongoing
transmission and performance. External attacker can flood
network bogus packets in the network to cause congestion
in the network. They can be prevented by implementing
the firewalls.
In Internal attack, the attacker node is already
the part of the network, and also contributes in normal
network activities, but after some time, it starts with the
malicious behaviour. It is more difficult to detect as

compare to the external attacks.

DPRAODV checks to find whether the RREP_Seq_No is
higher than the threshold value. M. Umaparvathi, and
D. K Varughese [24] proposes two tiers secure AODV
(TTSAODV) routing protocol which is an extension over
AODV protocol. In tier 1 security, the previous and the
next hop of any intermediate node exchanges the
verification messages to verify that the next hop of the
intermediate hop is also having the fresh path to the
destination.Similarly for detecting collaborative black
hole attack, tier 2 protocol is used.Jitendra kumar Rout
et al [25] proposed a Secure Fault- Tolerant Paradigm
(SFTP) which checks the Blackhole attack in the network.
The Wormhole Attack was introduced in [26],
[27], [28]. In this an attacker, or potentially multiple
colluding attackers, surreptitiously relay packets between
distant locations. This can give a node the impression
that it is the neighbor of a node that is far away. Y. C. Hu
et al [26] introduced Packet Leashes method in which
two types of methods have been considered: The
Geographic leashes and the temporal leashes. In
Geographic leashes, node location information is used to
bind the distance a packet can traverse. Lazos L, et al
[29] proposed a graph theoretic model to characterize
the wormhole attack and ascertain the necessary and
sufficient conditions for any candidate solution to
prevent wormholes. They used a Local Broadcast Key
(LBK) based method to set up a secure ad-hoc network
against wormhole attacks. J. Eriksson et al [30] proposed

a practical countermeasure to the wormhole attack that
presented as an extension to the IEEE 802.11 MAC
layer.

RELATED WORK
Wei-Shen Lai et al [11] have proposed a scheme to
monitor the traffic pattern in order to alleviate
distributed denial of service attacks. This mechanism
adopts the bandwidth allocation policy to assign normal
users to higher priority queue and the suspected attackers
to the lower priority queue.
S.A.Arunmozhi,
Y.Venkataramani [12] discussed the mechanism of DDoS
attack and proposed the defense scheme to detect the
DDoS attacks. In this scheme the proposed defense
mechanism uses the MAC layer information to detect the
attackers. Rizwan Khan, A. K. Vatsa [14] proposed a
clustering based prevention technique for the DDos attacks.
Niresh Sharma, Rajdeep Singh et al [15] proposed the
secure IDS to detect this kind of attack and block it. The
algorithm was proposed which uses the Anomaly based
Intrusion detection system which uses different intrusion
detection parameters such as packet reception rate, inter
arrival time. V.Priyadharshini and Dr.K.Kuppusamy [18]
proposed a new Cracking algorithm for detection of
DDOS attack.
The term “Blackhole” suggests a node which
absorbs all information passing through it by not
forwarding it to the destination node. As a result of the
dropped packets, the amount of retransmission needed

increases leading to congestion. Several schemes have
been proposed for detecting preventing the black hole
attack some of the methods can be stated as follows.
H. Deng, W. Li and D. P. Agrawal, [19] have
proposed a solution to cope with the black hole attack in
AODV. First, they suggest disabling the ability of an
intermediate node to send a RREP and allow only the
final destination to do that. T hey have proposed
another solution which requires that the intermediate node
adds its next hop’s information to the RREP packet before
sending it. B. Sun et al [20] proposed a new scheme to
ascertain the safety of the established path to secure AODV.
H. Miranda and L. Rodrigues [21] proposed another
scheme based on reputation system so called Friend and
Foes. This scheme aims to prevent the selfish nodes
from disrupting the network operations by refusing to
participate correctly to the forwarding process. E.
Gerhards-Padilla et al [22] proposed a TOGBAD approach
to defend against colluding black hole attack in tactical
MANETs, in which a successful attack can lead to human
life loss. Raj PN et.al [23] discuss a protocol viz.
DPRAODV (Dynamic, Prevention and Reactive AODV)
to counter the Black hole attacks. Unlike normal AODV,

The following table summarizes the different techniques
discussed above.
Table 2: Summary of different techniques for Detection
and prevention of attacks in MANETS
Sr.

Attack

Detection/
Prevention

Wei
Shen Lai

DDoS

Detection

S.A.Arun
mozhi

DDoS

Detection

Status values
from MAC Layer

3

Minda
Xiang

DDoS

Mitigation

after attack

Using Load
Protection Node

4

Rizwan
Khan

DDoS

Prevention

Clustering based.

5

Niresh
Sharma

DDoS

Detection

6

Laxmi
Bala

DDoS

Detection &
Prevention

Quality Based
Bottom Up
Detection

7

Dr.K.Ku
ppusamy

DDoS

Detection

New Cracking
algorithm

No

Author

1

2

Method

Priority Queue
based schemes

Anomaly Based
Intrusion
detection system

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ISSN:2249-5789
Krutika K Chhajed et al , International Journal of Computer Science & Communication Networks,Vol 5(3),184-191

8

H. Den

Blackh
ole

Mitigating
after attack

Allow final
destination to
send RREP

9

B. Sun

Blackh
ole

Mitigate
after attack

Cryptography
based reaction
mechanism

10

H.
Miranda

Blackh
ole

Prevention

Reputation based
Friends and Foes

11

E.Padill
a

Blackh
ole

Detection

Topology graph
based anomaly
detection

12

Raj PN

Blackh
ole

Detection
and
prevention

DPRAODV
approach

13

M.
Umaparv
athi

Blackh

ole

Prevention

Two tier Secure
AODV approach

14

Jitendra
kumar
Rout et
al

15

Y. C. Hu
et al

16

17

Lazos L,
et al
J.
Eriksson
et al

18

ShangMing
Jen et al

19

Ritesh
Mahesh
wari,

20

Dr. A.
Francis
Devaraj

Secure Fault
Tolerant
Paradigm
approach

Blackh
ole

Detection

Wormh
ole

Detection

Wormh
ole

Prevention

Wormh
ole

Prevention

Wormh
ole

Detection

Wormh
ole

Detection

Connectivity
Graph
information

Wormh
ole

Detection
and

Prevention

Multilayer
detection
approach

Packet Leashes
temporal and
Geographic
Graph Theoretic
approach
Truelink,
extension to the
802.11 MAC
layer
Hop count
Analysis scheme
using MHA
algorithm

Fig 1 : Basic block diagram of the proposed system
Each of the three modules first creates the MANET
environment and then simulates the attack in that
environment. After attack simulation the system apply the
technique for detection and detects the attack and register
the values of different parameters of the node in the trace
files or the awk files which can be then used for
generation of graphs and studying the behavior of the
system. The basic steps of each of the module can be
shown a in the fig 3.2 below.

PROPOSED SYSTEM
The proposed system consists of three independent
modules each of which deals with one of the type of attack
the DDoS, Blackhole and the Wormhole attack. Each of
these modules works independently and creates different
trace files which can then be used to generate comparison
graphs.
The basic work of the system can be shown in Fig.1
below:

Fig 2: Basic flow of each of the attack detection
module
a) Design of the module to illustrate the DDoS attack:
The design of the module required for the illustration of
the DDoS attack consists of following basic steps:

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ISSN:2249-5789
Krutika K Chhajed et al , International Journal of Computer Science & Communication Networks,Vol 5(3),184-191

1.
2.
3.
4.
5.
6.
7.

Create number of nodes to form a network.
Setup the links between these nodes
Setup the MANET environment for these nodes.
Create files to trace the simulation as well as monitor
queue that stores packet.
Start the simulation and note the values in the trace
files.
Read the trace files in different awk files for different
nodes
Generate graphs based on the data at different node
before attack and after attack.

b) Design of the module for illustration of Black hole
attack:
For the illustration of the black hole attack the algorithm
can be given as follows:
1. Create the patch file for setting the AODV protocol
environment and patch it to the current network
simulator environment.
2. Create the nodes and assign the properties to these
nodes relevant to the MANET environment.
3. Set one node as the blackhole node.
4. Simulate the blackhole attack in the simulator using
the tcl file and record the output of the simulation in
the trace file.
5. Read the trace file to check the effect of blackhole
attack on the ad hoc network.
c) Design of the module for illustration and detection
of Worm hole attack:

The wormhole attack is simulated in the MANET
environment as follows:
1. Create the nodes and set the MANET environment
2. Create the node environment
3. Start the simulation and during the simulation run the
CPP code for the detection of the wormhole attack using
unit disk graph method.
4. Note the contents in the trace files to check the effect of
wormhole attack on the network.

i.

ii.

iii.

Node u determines the set of common k-hop
neighbors with v from their k-hop neighbor lists.
This is Ck (u, v) = Nk (u) ∩ Nk (v)
Node u determines the maximal independent set
of the sub-graph on vertices Ck (u, v) by using a
greedy approach
If the maximal independent set size is equal or
larger than fk , node u declares the presence of a
wormhole.

SYSTEM IMPLEMENTATION & TESTING
1)

Setting Environment

To implement the proposed smoothly, we need to
have one of the various versions of LINUX operating
system which can be either Red Hat or Fedora or Ubuntu
and we need to install the Network Simulator 2 version
2.2 or onwards software tool to support complete
functionality of the product.
In addition to NS-2, we developed a set of tools, mainly
Bash scripts and AWK filters, to post-process the output
trace files generated by the simulator. Some scripts were
also written to help with the configuration and running of
the multiple experiments we have carried out.
In order to evaluate the performance, we set up multiple
experiments. In every experiment, we run a NS-2
simulation for each type of attack and different scenarios.
The exact environment and parameters will be discussed.
System Execution Details
The system executes by simulating different attacks
individually and the tracing the values generated from
these simulations.

The algorithm used for the detection of the wormhole
attack is the Unit Disk Graph algorithm which uses the
connectivity graph Information for finding out the
forbidden nodes in the graph and thus detecting that the
attack has occurred.
The Unit Disk Graph algorithm can be stated as
follows:
1. In UDG each node is modeled as a disk of unit radius in
the plane.
2. Each node is a neighbor of all nodes located within its

disk
3. The basic idea in our detection algorithm is to look for
graph substructures that do not allow a unit disk graph
embedding, thus cannot be present in a legal connectivity
graph.
Inside a fixed region, one cannot pack too many nodes
without having edges in between. The forbidden
substructures we look for are actually those that violate
this packing argument.

Fig 3: The network simulation created for the DDoS
attack
The first screenshot shows the simulation of the network
for the with total 16 nodes distributed in the diferent
groups. The nodes 4 and 9 are the nodes which takes the
data coming from different distributed nodes for the other
part of the network.

ALGORITHM:
1. Find the forbidden parameter Fk based on value of k
selected
2. Each node u determines its 2k-hop neighbor list, N2k
(u), and executes the following steps for each non
neighboring node v in N2k (u):

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ISSN:2249-5789
Krutika K Chhajed et al , International Journal of Computer Science & Communication Networks,Vol 5(3),184-191

Fig.4: Service denied at node 16 due to dropping of
legitimate packets
Fig. 4 shows the actual DDoS attack scenario where the
actual legitimate packets are dropped at node 15 and are
not sent to the destination node due the congestion in the
link and queue overflow .some of the packet may be sent
further to the actual destinations.

Fig 7: simulation of Wormhole Attack
Fig 7 shows the simulation of the wormhole attack. Here
the unit disk graph method is used to detect the forbidden
nodes.

Fig. 8: Result of wormhole attack detection
Fig 5: The graph showing the total number of packets
received

After this the Blackhole attack is simulated.

Fig. 5 shows the total no of packet received by the
destination node. From the graph it is clear that initially
the received packet number is zero but when the attacker
nodes starts attacking the number of packets starts
increasing and after some time it continues to the
maximum capacity.

Fig. 9 simulation of Blackhole Attack
Fig.6: The graph showing the entropy of node 4

RESULT ANALYSIS

Fig 6 shows the entropy of node 4 In this the red line
indicate the ratio of the normal packets received to the
total packets received at node and the green line indicates
the ratio of the attack packets received to the total packets
received at a node.

After the simulation of the attacks the trace files generated
after the simulation of each of the attack is considered and
the values of different parameters are calculated as
follows:

After the DDoS attack scenario the Wormhole attack is
simulated with the different environment.

The different parameter values obtained for the Blackhole
attack in attack condition can be given in the table 4.1 as
follows:

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ISSN:2249-5789
Krutika K Chhajed et al , International Journal of Computer Science & Communication Networks,Vol 5(3),184-191

Table 3. Results obtained for Blackhole attack
Parameter

Value

Average energy

0.001246

Average end to end delay

0.418301

PDR

0.040323

The different values obtained for throughput can be given
as
Table 4. Throughput of blackhole attack at different
conditions.

Throughput

Before attack

During Attack

89.96538

7.3096

The different parameter values obtained for the DDoS
attack can be given in the table 4.3 as follows:

Fig 10.Comparative graph for packet delay in each of the
attack

From the above results it is clear that the throughput of the
network decreases when the attack occurs. Also the attack
decreases the throughput to a large extent. The average
delay and the Packet delivery ratio also decreases when
there is an attack in the system.

Table 5. Results obtained for DDoS attack
Parameter
Average Energy
Average packet sent

Value
0.0055
14.8425

CONCLUSION

The different parameter values obtained for the Wormhole
attack can be given in the table 4.4 as follows:
Table 6. Results obtained for Wormhole attack
Parameter
Average
End to end delay

Value
2.63

0.014

The values of the packet delay for each of the attacks can
be given as follows:
Table 7. Comparison table for the packet delay of the
network
Packet delay
attcker

DDoS

Blackhole

Wormhole

2

0.4138

0.4132

0.10056

3

0.42533

0.4192

0.12833

4

0.43133

0.4212

0.28

The comparative graph can be given between the three
attacks for the above table as below:

From these discussions we can say that even if there are so
many techniques for detection and prevention of different
types of attacks, no methodology provides the complete
protection from the attacks and also the each of these
methodologies has some or other type of loophole in it.
Thus the system can detect and analyze the different
attacks and then provides a comparative study of these
attacks which proves that the wormhole attack provide
less delay as compared to other two attacks, as the
detection technique used in the system restrict the attacker
nodes to disrupt the normal working of the system. This
system can provide a overview of the different types of
attacks that can occur in the ad hoc networks
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