airo national research journal volume xiv, issn: 2321-3914 ......wormhole attack, would be unable to...

Airo National Research Journal Volume XIV, ISSN: 2321-3914 April, 2018 Impact Factor 0.75 to 3.19 UGC Approval Number 63012

1


2

PERFORMANCE ANALYSIS OF AODV ROUTING PROTOCOL USING

MODIFIED ANT COLONY OPTIMIZATION UNDER BLACK HOLE

ATTACK

Nimisha Swami*1 , Amit Kumar Bairwa

2, Vijay Kumar Sharma

3

1 Research Scholar (M. Tech.), Department of CSE,

2,3Assistant Professor, Department of CSE

12Rajasthan Institute of Engineering and Technology, Jaipur

Declaration of Author: I hereby declare that the content of this research paper has been truly made by me including the title of the research paper/ research article,

and no serial sequence of any sentence has been copied through internet or any other source except references or some unavoidable essential or technical terms. In

case of finding any patent or copy right content of any source or other author in my paper/article, I shall always be responsible for further clarification or any legal

issues. For sole right content of different author or different source, which was unintentionally or intentionally used in th is research paper shall immediately be

removed from this journal and I shall be accountable for any further legal issues, and there will be no responsibility of Journal in any matter. If anyone has some

issue related to the content of this research paper’s copied or plagiarism content he/she may contact on my above mentioned email ID.

Abstract

As MANET (Mobile Ad-hoc Network) applications are deployed, security emerges as a central

requirement. We introduce the blackhole attack, a severe attack in ad hoc networks that is

particularly challenging to shield against. The blackhole attack is reflex even if all packets

sending communication provides authenticity and confidentiality and even if invader has not ruin

any hosts. In the blackhole attack, an intruder records packet (bits) at one location in the

network, tunnels them (possibly selectively) to another location, and retransmits them there into

the network. The blackhole attack can form a pensive threat in MANET, especially against many

Mobile Ad-hoc Network routing protocols and location based security systems. For example,

most existing MANET routing protocols, without some mechanism to defend against the

wormhole attack, would be unable to find routes longer than one or two hops, severely interrupt

communication. Here is a general mechanism, called packet watchdog, for detecting and

protecting against blackhole attacks, and a specific protocol that implements watchdog. In this

performance of Mobile Ad-hoc Networks (MANET) under blackhole attack is analyzed.

Multiple QoS parameters have been considered here such as throughput, delay, packet delivery

ratio, node energy and node density. The NS3 network simulator has been used and the reference

point group mobility model is considered to study the effect of node density and the initial

energy on the throughput.

1. INTRODUCTION

A Mobile Ad hoc Network (MANET) is a

virtual network which is created by set of

wireless mobile nodes. It does not use any

fixed infrastructure or centralized

administration. Nodes calculate on multi-

hop routing protocols to forward data

packets sent from a source node to a

destination node which is out of its

transmission range. Every node may

function as both a data source and a router

that forward data for other nodes.


3

1.1 MANET

Initially MANET is used only for battlefield

area so as to provide secure communication,

but now with the changing technology and

with the wireless communication,

development of group of organized devices

is made. This group collectively known as

MANET. It is decentralized network and

can detect any node automatically.

Pervasive computing is the technology

which is only supported by mobile

networking [1]. During the last decade,

advances in both hardware and software

techniques had resulted in mobile hosts and

wireless networking common and

miscellaneous. Generally there are two

distinct approaches for permissive wireless

mobile units to communicate with each

other:

Infrastructure: Wireless mobile

networks have traditionally been

based on the cellular concept and

relied on good infrastructure stay, in

which mobile devices communicate

with access points like base stations

connected to the fixed network

infrastructure. Typical examples of

this kind of wireless networks are

WLL, WLAN, GSM, UMTS, etc.

Infrastructure-less: As to infrastructure

less approach, the mobile wireless network

is commonly known as a mobile ad hoc

network (MANET). In MANET data is send

to one another by using dynamically design

network without using any pre-existing

fixed network infrastructure. This is a very

important part of communication technology

that supports truly common computing,

because in many contexts information

exchange between mobile units cannot rely

on any fixed network infrastructure, but on

rapid configuration of a wireless network

on-the-fly. Wireless ad hoc networks

themselves are an independent, wide area of

research and applications, instead of being

only just a complement of the cellular

system. In this dissertation, the major

problems of ad hoc networking is

distinguish by giving its related research

background including the concept, features,

status, and applications of MANET. Some

of the technical challenges MANET poses

are also conferred. Research issues that are

responsible for promote the development

and accelerate the commercial applications

of the MANET technology are discussed in

detail.

In this paper , the major problems of ad hoc

networking is distinguish by giving its

related research background including the

concept, features, status, and applications of

MANET.

1.2 Challenges of MANET

Regardless of the attractive applications, the

features of MANET introduce several

challenges that must be considered carefully

before a wide commercial deployment can

be expected. These include:

Routing: Since the topology of the

network is constantly changing, the issue

of routing packets among any pair of

nodes becomes a challenging task. Most


4

protocols should be based on reactive

routing instead of proactive. Multicast

routing is another challenge because the

multicast tree is once static due to the

random movement of nodes within the

network. Routes between nodes may

potentially contain multiple hops, which

is more complex than the single hop

communication between the nodes [4].

Security and Reliability: The security

problem face by ad hoc network after the

supplemental to the common liability of

wireless connection is due to e.g. nasty

neighbor broadcast packets. The feature

of distributed operation requires

different schemes of authentication and

key management. Another, reliability

problem face by the wireless link,

because of the limited wireless

transmission range, the broadcast nature

of the wireless medium (e.g. hidden

terminal problem), mobility-induced

packet losses, and data communication

errors.

Quality of Service (QoS): Providing

different quality of service levels in a

constantly changing environment will be

a challenge. The inherent stochastic

feature of communications quality in a

MANET makes it troublesome to offer

fixed guarantees on the services offered

to a device. An adaptive QoS must be

implemented over the traditional

resource reservation to support the

multimedia services [4].

Power Consumption: For lean power

consumption the communication-related

functions is optimize in most of the

light-weight mobile terminals..

Protection of power and power-aware

routing must be taken into consideration.

One of the most challenging goals in mobile

ad hoc network is the design of routing

protocols. The role of routing protocol is to

efficiently find the shortest path between the

source and the destination of a flow [4].

2. Routing Protocols In MANET

Routing protocols may generally be

categorized as two types:

Proactive

Reactive

Proactive protocols are also referred to as

table-induced while reactive protocols are

referred to as on-demand. Proactive

protocols attempt to maintain consistent, up-

to-date routing information from each node

to every other node in the network. On the

other hand, reactive protocols start route

discovery only in the existence of data for

transmission at the source.

3. Existing And Proposed Method

3.1 Existing System

In this section, we review different methods

for the detection of black hole attack in

AODV based mobile ad hoc networks.

Cauvery N.K. et al.26 proposed an efficient

algorithm that uses swarm intelligence to

produce all feasible paths between a source

and a destination node in a MANETs. In the


5

Ant colony based Routing Algorithm

(ARA), routing of data packets are made

only passing through the finest path created

by route discovery phase of. Route

maintenance is periodically done to maintain

the finest path using data packets. Because

of working nature of dynamic topology of

ad hoc networks, existing routes may fail or

new paths may be created. Therefore, route

refreshing is done periodically, when

topology is changing.

Raj et al. discusses a protocol viz. discusses

a protocol viz. DPRAODV (Detection,

Prevention and Reactive AODV) to counter

the black hole attack. It checks whether the

RREP_Seq_no is higher than the threshold

value. The threshold value is dynamically

updated in every time interval. If

RREP_Seq_no is higher than threshold

value, the node is malicious node and added

to black listed nodes. Finally, send an

ALARM message to neighbor nodes about

black listed nodes. Thus the neighbor nodes

know that malicious node and if any

message come from malicious node

automatically discarded the message. In the

simulation results, the packet delivery ratio

improved by up to 85% than normal AODV.

Sowmya et al. proposed some changes in ant

colony optimization. In this algorithm

provided a finest path efficiently since it is

fully distributed and so, there is no single

point of failure, moreover it is very easy to

perform the operations on all the nodes.

Detect and prevent black hole attack used

threshold value and it is added with the

ACO algorithm. It is based on asynchronous

and independent interaction of agents.

Separate these malicious nodes from the

data forwarding time with help of the alarm

message to all its neighboring nodes.

Sarita Choudhary et al. provides an efficient

approach for the detection of blackhole and

Gray hole attack in Mobile Ad hoc

Networks based on the AODV routing

protocol. In this approach malicious nodes

are listed locally by each and every node

when the nodes act as a source node. The

protocol uses the concept of Core

Maintenance of the Allocation Table. In the

Allocation table when a new node joins the

network, broadcast message for the request

to get the IP address as it want to be a part of

that network. The nodes, also called as the

backbone nodes which receive this message

chose a free IP address randomly and

unicast this IP address to the requesting

node. When the requesting node get this

allot-ted IP address sends back an

acknowledgement to the Black hole node.

Thus the allocation is only done through the

Backbone node and it has the overall control

the malicious node can be easily detected.

M. Umaparvathi et al.30 proposed algorithm

is called as TTSAODV protocol to identify

single and collaborative black hole attack in

mobile ad hoc networks. This protocol

proves the trueness of the RREP message

through the verification messages sent by

neighboring nodes. The basic assumption in

this solution is that there is a strong

symmetric key distribution system in the

MANET. Thus, every pair of nodes in the

network has unique common secret key. In

the proposed protocol, two levels of security

are provided. One level is during the route


6

discovery process and the next is during the

data transfer. Even if the detection of Black

hole attack fails at the route discovers

process, in the next level, it will be

identified. So, the proposed protocol has

high degree of attack detection and

prevention.

More than resolutions for black hole attack

discussed above involve supplementary

overhead on either/both intermediate and

destination nodes in anyway. Because the

mobile nodes in ad hoc networks suffer from

limited battery life, processing power and

storage, it is necessary to devise a protocol

with the intention of to reducing the

overhead on neighboring and destination

nodes. In addition, the process of selecting

secure root, should involve minimum

possible augment in end-to-end delay.

3.2 Proposed System

In this previous section, existing algorithm

detect the black hole attack. ARA and

AODV are evaluated by so many authors

and identified ARA is always better than

AODV. In this section, we have proposed

AODV is modified to detect and prevent

black hole attack by using ant colony

algorithm such as ARA. Pheromone updates

play a significant role in the performance of

the ant algorithm. In ARA algorithm, initial

pheromone value is calculated by number

nodes during

the route discovery process. The working

principles of the algorithm are given below:

1. Establish a network with N number

of nodes.

2. Specify the properties of network.

3. Define the source and the destination

node over the network.

4. Place the ant at each node in the

network.

5. Define the m malicious nodes over

the network.

6. Route discovery process: Source

node broadcast the RREQ message

to neighboring nodes using FANT

forward technique and hop count is

initialized. It is an agent to establish

pheromone value to the source node.

7. Collecting replies:

Collecting the neighboring

nodes information stored in

routing table.

Neighboring nodes receive

the request then it will check

whether the node is

destination or not.

If yes then

FANT is sent to only

that neighbor

else

it’s forwarded to all the

neighbors.

A node is receiving a FANT

for the first time, will create a

record in its routing table and


7

fields such as destination

address, next hop and

pheromone value.

8. For each FANT (currently in node i)

Do

Choose the neighbor node,

probability value will be high

that route/neighbor needs to

be considered.

Add that node pheromone

value to neighbor-ing

pheromone table with the

node, pheromone value

between these nodes until the

ant has reached the

destination.

End

9. The full process is mention above to

get repeated until the Forward Ant

(FANT) reaches the destination

node.

10. When FANT destroy, it is reaches to

the destination and create Backward

Ant (BANT) send to along the path

to the source node. It is an agent that

establishes the pheromone value to

the destination.

11. Route maintenance: Once FANT and

BANT have established route path

between source to destinations and

data packets are send along the same

path. The pheromone track value is

strengthened means path is shortest

path between these two nodes.

4. Implementation And Results

Simulations have been carried out in order

to evaluate routing protocol. We focused our

attention on the evaluation of network

performance in terms of routing overhead,

throughput, packet delivery ratio and

normalized routing load of a mobile ad hoc

network where a number of nodes are

varying [13].

4.1 Simulation setup

TABLE 1

SIMULATION PARAMETER

General Parameters

Number of Nodes 10,20,30,40,50

Topology Dynamic

Simulation Time 1000 Sec


8

MAC Layer 802.11

Range 200 meters

Simulation Area 1000 x 1000 meter2

Routing Protocol AODV

Traffic Model Parameter

Traffic Model Constant Bit Rate

Packet Size 512 Bytes

Interval 1 Sec

a) Here topology specify overall square

area for network.

b) Traffic model suggest what kind of

traffic we are using.

c) Interval specifies time between

successive packets.

d) Range specifies wireless network

card signal propagation range.

4.2 Simulation Results on Routing

Protocols

The proposed methodology is compared

with the existing algorithm of safe route

method

based upon the ant colony based routing

algorithm on the basis of throughput, packet

delivery ratio, end-to-end delay and so on.

The performance and results of the routing

algorithm as below:

4.2.1 Throughput

The throughput is the number of bytes

transmitted or received per second. The

throughput is denoted by T,

Throughput = received node/simulation time

T=

Where,

= average receiving node for the ith

application,

= average sending node for the ith

application, and

n = number of applications.

In Figure 10 shows that the proposed

algorithm improved good throughput

compared to AODV with black hole attack.


9

Fig. 1: Throughput

4.2.2 Packet Delivery Ratio

It can be measured as the ratio of the

received packets by the destination nodes to

the packets sent by the source node.

PDR = (number of received packets /

number of sent packets) * 100

T=

Where, Ns , N

r node sent by the sender and

the number of application data node

received by the receiver, respectively for

the ith application, and n is the number of

applications. In Figure 11 shows that packet

delivery ratio of the pro-posed algorithm is

more than AODV routing algorithm with

black hole attacks. If we are talking about

the original AODV working it decreases

delivery of packet with increase in number

of nodes.


10

Fig. 2: Packet Delivery Ratio

4.2.3 End-to-End Delay

Fig. 3: End to End Delay

It represents the time required to move the

packet from the source node to the

destination node.

E-2-E delay [packet_ id] = received time

[packet_ id] – sent time [packet_ id]

The average end-to-end delay can be

calculated by summing the times taken by


11

all received packets divided by its total

numbers.

D=

Where, di = average end to end delay of

node of ith

application and n = number of

application. In Figure 12 shows that the

proposed algorithm provided minimum end-

to-end delay compared with original AODV

with black hole attack.

4.2.4 Dropped Packets

It represents the number of packets that sent

by the source node and fail to reach to the

destination node.

Dropped packets = sent packets– received

packets.

T= -

Where, Ns, N

r node sent by the sender and

the number of application data node

received by the receiver, respectively for the

ith

application, and n is the number of

applications. In this proposed system, get

better performance to deliver the data

packets. It easy to analysis packet dropped

rate in the routing process.

Fig. 4: Dropped Packets

5. Conclusion & Future Work

5.1 Conclusion

In this section, the paper summarized for

study about Mobile Ad Hoc Networks; we

initiate that most repeated attack is a black


12

hole in MANETs. To discover a resolution

for that various algorithms are available. But

to decide security and performance issues

some improvements on the routing

technique is implemented. We are analyzed

the effects of black hole attack in the light of

network load, throughput and end-to-end

delay in MANETs and simulating the black

hole attack using reactive routing protocols

(e.g. AODV). Compared and observed that

AODV without attack gives better result in

all situations.

After analysis by different method the

results it is found that under attack case

system has more packet drop ratio it is

always greater to threshold. Design and

implement a security algorithm for detection

of black hole attack based on Ad hoc On-

Demand Distance Vector routing protocol

and Ant Colony Algorithm.

Implementation of proposed method is quite

efficient for network and able to detect

attack. In addition, the performance of the

network is improved effectively. The

summary of performance is packet delivery

ratio, end-to-end delay and throughput can

be improved. The proposed protocol can

able to improve two main problems such as

security and performance, into one place,

but this concept is able to detect only one

attack and effective for black hole. In future

a framework for security is required, where

more than one attack are handled.

5.2 Future Work

In this work, simulation of more Static and

Dynamic routing protocols using Bayesian

Filtering and Collaborative Message Passing

Interface. Future work involves the study of

certain attacks on network under stochastic

modeling for nodes participating in the

routing path, and its effect on routing

protocol by comparing various network

parameters. It is also aimed to find the

analytical expression for the same.

REFERENCES

[1]. Yanxia Rong, S. K. Lee, and H. A.

Choi, "Detecting stations cheating on

back off rules in 802.11 networks

using sequential analysis," In Proc.

IEEE INFOCOM '06, 15-jun-2006.

[2]. Cenker Demir and Cristina Comaniciu

, “An Auction based AODV Protocol

for Mobile Ad Hoc Networks with

Selfish Nodes”, IEEE International

Conference on 24-28- June- 2007.

[3]. Zahara Safaei , Mohammad Hossein

Anisi an Fatemeh Torgheh, “ A

Reputation-Based Mechanisms to

enforce Cooperation in MANETs”,

Software, Telecommunications and

Computer Networks, ( SoftCOM 2008)

16th International Conference on 25-

27 Sept.- 2008.

[4]. C. K. Toh, D. Kim, S. Oh, and H. Yoo,

“The controversy of selfish nodes in ad

hoc networks,” in Proceedings of the

Twelveth International Conference on

Advanced Communication

Technology, pp.20-26, 20-June- 2010.

[5]. J.-K. Lee and J. C. Hou, “Modeling

Steady-state and Transient Behaviors


13

of User Mobility: Formulation,

Analysis, and Application,” in Proc. of

ACM MobiHoc 06, vol.08, pp. 85–96,

May- 2006.

[6]. S. Marti, T. J. Giuli, K. Lai, and M.

Baker, “Mitigating Routing

Misbehavior in Mobile Ad hoc

Networks,” in Proc. of ACM

MobiCom’, pp. 255–265, 2010.

[7]. D. Chen, S. Garg, and K. S. Trivedi,

“Network Survivability Performance

Evaluation: A Quantitative Approach

with Applications in Wireless Ad-hoc

Networks,” in Proc. of the ACM

International Workshop on Modeling,

Analysis, and Simulation of Wireless

and Mobile Systems, pp. 61–68, Sep.-

2002.

[8]. D. Goyal and J. J. Caffery,

“Partitioning Avoidance in Mobile Ad

Hoc Networks Using Network

Survivability Concepts,” in Proc. of

the 7th International Symposium on

Computers and Communications,

May- 2012.

[9]. P. Snow, U. Varshney, and A. D.

Malloy, “Reliability and Survivability

of Wireless and Mobile Networks,”

IEEE Computer Magazine, vol. 33, pp.

449–454, Jul.-2011.

[10]. F. Xing and W. Wang, “Modeling and

Analysis of Connectivity in Mobile Ad

Hoc Networks with Misbehaving

Nodes,” in Proc. of IEEE Conference

on Communications, pp. 179–184,

Jun.-2006.

[11]. H. Kawahigashi, Y. Terashima, N.

Miyauchi, and T. Nakakawaji,

“Desiging Fault Tolerant Ad Hoc

Networks,” in Proc. of IEEE/AFCEA

Military Communications Conference,

pp. 115–121, Jan.-2005.

[12]. L. Buttyan and J.-P. Hubaux,

“Stimulating Cooperation in Self-

Organizing Mobile Ad Hoc

Networks,” Mobile Networks and

Applications, vol. 8, no. 5, pp. 579–

592, Oct.-2003.

[13]. M. Zhao and W. Wang, “A Unified

Mobility Model for Analysis and

Simulation of Mobile Wireless

Networks,” ACM-Springer Wireless

Networks, vol. 6, no. 4, pp. 184–191,

September -2007.

[14]. N. Sadagopan, F. Bai, B.

Krishnamachari, and A. Helmy,

“PATHS: Analysis of PATH Duration

Statistics and their Impact on Reactive

MANET Routing Protocols,” in Proc.

of ACM MobiHoc ’,03-Jun.- 2010.

[15]. Ian D. Chakeres and Elizabeth M.

Belding-Royer, "AODV Routing

Protocol Implementation Design"

Proceedings of the International

Workshop on Wireless Ad Hoc

Networking, Tokyo, Japan, March-

2004.

[16]. J. Hortelano, C.T. Calafate, J.C. Cano,

M. de Leoni, P. Manzoni, and M.

Mecella, “Black-hole attacks in p2p

mobile networks discovered through

bayesian filters,” in Proceedings of


14

OTM Workshops, pp. 543–552, Jun.-

2010.

[17]. David B. Johnson, David A. Maltz and

John Broch, “DSR: The Dynamic

Source Routing Protocol for Multi-

Hop Wireless Ad hoc Networks” in Ad

hoc Networking edited by Charles E.

Perkins, Chapter 5, pp. 139-172, Oct.-

2001.

[18]. L. Buttyan and J. P. Hubaux,

“Stimulating Cooperation in Self-

Organizing Mobile Ad Hoc

Networks”, in ACM Journal For

Mobile Networks (MONET), Special

Issue On Mobile Ad Hoc Networks,

Jan.-2003.

[19]. Y. Li, G. Su, D. Wu, D. Jin, L. Su, and

L. Zeng, “The impact of node

selfishness on multicasting in delay

tolerant networks,” Vehicular

Technology, IEEE Transactions on,

vol. 60, pp. 2224 –2238, jun 2011.J. P.

Sterbenz, R. Krishnan, and et. al,

“Survivable Mobile Wireless

Networks: Issues, Challenges, and

Research Directions,” in Proc. of ACM

Workshop on Wireless Security pp.

31–40, Sept.-2002.

airo national research journal volume xiv, issn: 2321-3914 ......wormhole attack, would be unable to...

Documents