Distributed security system for mobile ad hoc computer networks

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.

Distributed Security System for Mobile Ad-Hoc Computer

Networks

Department of Computer Science & Engg Principal,

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

[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 rout ing algorit hms 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

Application Layer data corruption, viruses and worms Transport Layer TCP/UDP SYN flood

Network Layer hello flood, blackhole Data Link Layer monitoring, traffic analysis Physical Layer eavesdropping, active interference

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

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,

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

The following table summarizes the different techniques discussed above

Table 2: Summary of different techniques for Detection and prevention of attacks in MANETS

Sr

Prevention

Method

1

Wei Shen Lai DDoS Detection

Priority Queue based schemes

2

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 Anomaly Based

Intrusion detection system

6

Laxmi Bala DDoS Detection &

Prevention

Quality Based Bottom Up Detection

7

Dr.K.Ku ppusamy DDoS Detection

New Cracking algorithm

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

Miranda

Blackh ole Prevention

Reputation based Friends and Foes

11

E.Padill

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

Blackh ole Detection

Secure Fault Tolerant Paradigm approach

15

Y C Hu

et al Wormh

ole Detection

Packet Leashes temporal and Geographic

16 Lazos L,

et al

Wormh ole Prevention

Graph Theoretic approach

17

J

Eriksson

et al

Wormh ole Prevention

Truelink, extension to the 802.11 MAC layer

18

Shang-Ming

Jen et al

Wormh ole Detection

Hop count Analysis scheme using MHA algorithm

19

Ritesh

Mahesh

wari,

Wormh ole Detection

Connectivity Graph information

20

Dr A

Francis

Devaraj

Wormh ole

Detection and Prevention

Multilayer detection approach

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 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

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:

1 Create number of nodes to form a network

2 Setup the links between these nodes

3 Setup the MANET environment for these nodes

4 Create files to trace the simulation as well as monitor

queue that stores packet

5 Start the simulation and note the values in the trace

files

6 Read the trace files in different awk files for different

nodes

7 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

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

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):

i 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)

ii Node u determines the maximal independent set

of the sub-graph on vertices Ck (u, v) by using a greedy approach

iii 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

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

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 5: The graph showing the total number of packets

received 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.6: The graph showing the entropy of node 4

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 DDoS attack scenario the Wormhole attack is

simulated with the different environment

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 After this the Blackhole attack is simulated

Fig 9 simulation of Blackhole Attack

RESULT ANALYSIS

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:

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

Table 3 Results obtained for Blackhole attack

Average energy 0.001246

Average end to end delay 0.418301

The different values obtained for throughput can be given

as

Table 4 Throughput of blackhole attack at different

conditions

Throughput

Before attack During Attack

The different parameter values obtained for the DDoS

attack can be given in the table 4.3 as follows:

Table 5 Results obtained for DDoS attack

Parameter Value

Average Energy 0.0055 Average packet sent 14.8425 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 Value

End to end delay 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

The comparative graph can be given between the three

attacks for the above table as below:

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

CONCLUSION

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

REFERENCES

[1] Adnan Nadeem, Michael P Howarth, “A Survey of MANET Intrusion Detection & Prevention Approaches for Network Layer Attacks”, IEEE Communications Surveys & Tutorials, Vol 15, No 4, pp 2027-2043,

2013

[2] Shikha Jain, “Security Threats in MANETS: A Review”, International Journal on Information Theory, Vol 3, pp 37-50, April 2014

[3] J Godwin Ponsam, Dr R.Srinivasan, “A Survey on MANET Security Challenges, Attacks and its Countermeasures”, International Journal of Emerging trends and Technology in Computer Science, Vol.3, issue

1, pp 274-279, Feb 2014

[4] Alex Hinds, Michael Ngulube, Shaoying Zhu and Hussain-Al-Aqrabi, “A Review of Routing Protocols for Mobile Ad-hoc Networks (MANETS)”, International Journal of Information Education and Technology, Vol.3, No.1, Feb 2013

[5] Amandeep Makkar, Bharat Bhushan, Shelja and Sunil Taneja, “Behavorial study of MANET Routing Protocols”, International Journal of Innovation,

Management and Technology, vol.2, No.3, 210-216, June

2011

[6] C Perkins, E B Royer, S Das, “Ad-hoc On-Demand

Distance Vector (AODV) Routing”, IETF Internet Draft,

2003

[7] C E Perkins and P Bhagwat, Highly Dynamic

Destination Sequenced Distance Vector Routing (DSDV)

for mobile computers”, proceedings of ACM SIGCOMM

94, pp 34-244, 1994

[8] B divecha, A Abraham, C Grosan and S Sanyal,

“Analysis of Dynamic Source routing and Destination

Sequenced Distance Vector Protocols for Different

Mobility Model”, in Proc Of First International

Conferene on Modelling and Simulation , Phuket,

Thailand, pp 224-229, March 2009

[9] D B Johnson and D.A Maltz, “Dynamic Source

Routing in Ad hoc Wireless Network”, Mobile computing

Academic publishers, Vol.5, pp 153-181,1996

[10] Kimaya Sanzgiri, Bridget Dahil, Brian Neil Levine,

Clay Sheilds and Elizabeth M Belding-Royer, “A Secure

Routing Protocol for Ad Hoc Networks”, in Proc Of 10th

IEEE International Conference of Network Protocols

(ICNP 02), Paris, France, Nov 12 - 15,2002

[11] Wei-Shen Lai, Chu-Hsing Lin, Jung-Chun Liu,

Hsun-Chi Huang, Tsung-Che Yang: Using Adaptive

Bandwidth Allocation Approach to Defend DDoS

Attacks, International Journal of Software Engineering

and Its Applications, Vol 2, No 4, pp 61-72 (2008)

[12] S.A.Arunmozhi, Y.Venkataramani “DDoS Attack

and Defense Scheme in Wireless Ad hoc Networks”

International Journal of Network Security & Its

Applications (IJNSA), Vol.3, No.3, May 2011,

DOI:10.5121/ijnsa.2011.3312

[13] Minda Xiang,Yu Chen,Wei-Shinn Ku, Zhou Su, “

Mitigating DDoS Attacks using Protection Nodes in

Mobile Ad Hoc Networks”, Dept of Computer Science &

Software Engineering, Auburn University, Auburn, AL

36849

[14] Rizwan Khan , A K Vatsa, “Detection and Control

of DDOS Attacks over Reputation and Score Based

MANET”,Journal of Emerging Trends in Computing and

Information Sciences, VOL 2, NO 11, October 2011

[15] Prajeet Sharma,Niresh Sharma,Rajdeep Singh,” A

Secure Intrusion detection system against DDOS attack

in Wireless Mobile Ad-hoc Network”, International

Journal of Computer Applications,Volume 41– No.21,

March 2012

[16] LaxmiBala, A K Vatsa, “Quality based

Bottom-up-Detection and Prevention Techniques for DDOS i n

MANET”,International Journal of Computer Applications,

Volume 55– No.2, October 2012

[17] Gagandeep, Aashima, Pawan Kumar, “Analysis of

Different Security Attacks in MANETs on Protocol Stack

A – Review”, International Journal of Engineering and

Advanced Technology (IJEAT) ISSN: 2249 –8958,

Volume -1, Issue -5, June 2012 PP 269-275

[18] V.Priyadharshini, Dr.K.Kuppusamy, “Prevention of DDOS Attacks using New Cracking Algorithm”,

International Journal of Engineering Research and Applications, Vol 2, Issue 3, May-Jun 2012,

pp.2263-2267

[19] Deng H Li W and Agrawal, D.P., "Routing security

in wireless ad hoc networks,” Communications Magazine,

IE EE , vol.40, no.10, pp 70- 75, October 2002

[20] B Sun, Y Guan, J Chen and U W Pooch, Detecting

black- hole attack in mobile ad hoc networks, In Proc 5th European Personal Mobile Communications Conference, Glasgow, UK, April 2003

[21] H Miranda and L Rodrigues, Friends and Foes: Preventing Selfishness in Open Mobile Ad hoc networks,

In Proc 23rdInternational Conference on Distributed Computing Systems Workshops (ICDCSW’03), Providence,

RI, USA, May 2003

[22] E Gerhards-Padilla, N Aschenbruck, P Martini, M Jahnke and J Tolle Detecting Black Hole Attacks in

Tactical MANETs using Topology Graphs, In Proc of the 33rd IEEE Conference on Local Computer Networks (LCN), Dublin, Ireland, October 2007

[23] Payal N Raj and Prashant B Swadas,

“DPRAODV: A Dynamic Learning System against Blackhole Attack in AODV based MANET”, IJCSI International Journal of Computer Science Issues, Vol 2,

2009

[24] M Umaparvathi, and D K Varughese "Two Tier Secure AODV against Black Hole Attack in MANETs," European Journal of Scientific Research 72.3 (2012):

369-382 [25] Jitendra Kumar Rout , Sourav Kumar Bhoi, Sanjaya kumar Panda, “SFTP: A Secure and Fault-Tolerant Paradigm against Blackhole Attack in MANET”, International Journal of Computer Applications (0975- 8887) Vol 64 – No 4, pp 27-31, Feb-2013

[26] Y C Hu, A Perrig, and D Johnson, “Packet leashes:

a defense against wormhole attacks in wireless networks,”

in INFOCOM, 2003

[27] P Papadimitratos and Z J Haas, “Secure routing for mobile ad hoc networks,” in SCS Communication Networks and Distributed Systems Modeling and Simulation Conference (CNDS 2002), 2002

[28] K Sanzgiri, B Dahill, B Levine, and E Belding-Royer, “A secure routing protocol for ad hoc networks,”

in International Conference on Network Protocols (ICNP), Nov 2002

[29] Lazos, L.; Poovendran, R.; Meadows, C.; Syverson, P.; Chang, L.W Preventing Wormhole Attacks on Wireless Ad Hoc Networks: A Graph Theoretic

Approach In IEEE WCNC 2005, Seattle, WA, USA,

2005; pp 1193–1199

[30] J Eriksson, S Krishnamurthy, and M Faloutsos,

“Truelink: A practical countermeasure to the wormhole attack,” in ICNP , 2006

[31] Shang-Ming Jen , Chi-Sung Laih and Wen-Chung

Kuo, “A Hop-Count Analysis Scheme for Avoiding

Wormhole Attacks in MANET”, Sensors 2009, 9,

5022-5039; doi:10.3390/s90605022

[32] Maheshwari, R.; Gao, J.; Das, S.R Detecting

Wormhole Attacks in Wireless Networks Using

Connectivity Information In IEEE INFOCOM,

Anchorage, AK, USA, 2007; pp 107–115

[33] Vandana C.P, Dr A Francis Saviour Devaraj, “A

MultiLayered Detection mechanism for Wormhole attack

in AODV based MANET”, International Journal of

Security, Privacy and Trust Management ( IJSPTM) Vol

2, No 3, June 2013

[34] online link http://www.isi.edu/nsnam/ns/

[35] online link available mohittahiliani.blogspot.com/

[36] Aliff Umair Salleh, Zulkifli Ishak , Norashidah Md

Din, Md Zaini Jamaludin “Trace Analyzer for NS-2”, 4th

Student Conference on Research and Development

(SCOReD 2006), Shah Alam, Selangor, MALAYSIA, 27-28

June, 2006,IEEE