bee -m imetic dsr based secure r outing in manet using ... · paper we have proposed the bee...

Bee-mimetic DSR Based Secure Routing in MANET using Artificial

Bee Colony Optimization

M.Vijay Anand

Professor, Department of Computer Science and Engineering

Saveetha Engineering College, Chennai, India

[email protected]

MuthukrishnanRamprasath

Sr. Assistant professor, Department of Computer Science & Engineering,

Madanapalle Institute of Technology & Science

Andhra Pradesh, INDIA

[email protected]

Shanmugasundaram Hariharan

Professor, Department of Computer Science and Engineering

Saveetha Engineering College, Chennai, India

[email protected]

Abstract:

Bee-mimetic algorithm is a emerging technique inspired by nature used in various

application, domains etc. In mobile ad hoc network (Self organized, infrastructure less network)

routing and security is a most challenging problem. This paper proposes a modified DSR routing

protocol with Bee-Mimetic algorithm to improve the performance of routing and to remove the

misbehaving nodes performing blackhole attacks. The implementation of the proposed protocol

is by using NS2 simulator. The performance evaluation is done by comparing with AODV, DSR

and Bee-Mimetic DSR (BM-DSR). The improved packet delivery ratio and decreased delay of

packet delivery is achieved The simulation result shows that it not only has improved

performance compared to AODV, DSR and Bee-Mimetic DSR (BM-DSR), but also achieves

stronger privacy protection by 20% to 30% of blackhole detection than existing schemes.

Keywords: Bio-Mimetic, Dynamic source routing (DSR), AODV

International Journal of Pure and Applied MathematicsVolume 119 No. 17 2018, 1337-1350ISSN: 1314-3395 (on-line version)url: http://www.acadpubl.eu/hub/Special Issue http://www.acadpubl.eu/hub/

1337

1. Introduction:

Mobile Ad hoc Networks (MANET) are utilized to set up wireless communication in

spontaneous environments without a predefined infrastructure or centralized administration.

MANET has been normally deployed in undesirable and aggressive environments where central

authority point is not necessary. One of the unique characteristic of MANET is the dynamic

nature of its network topology which would be frequently changed due to the volatile mobility of

nodes. In addition, each mobile node in MANET plays a router role while transmitting data over

the network. Any compromised nodes under an adversary’s control could cause significant

damage to the functionality and security of its network.

The main aim of routing in MANETs is to deliver the data to destination in optimal path

from source. A MANET routing algorithm is not only to identify the shortest path between the

source and destination, but it has also been adapted. The MANETs is also multi-hop in nature.

To reach the destination the packet should be relayed. MANET routing algorithm has two

necessary components such that route discovery and route maintenance.

2. AN OVERVIEW OF MANET ROUTING PROTOCOLS

Ad hoc On Demand Distance Vector (AODV):

The Ad hoc On Demand Distance Vector (AODV) routing algorithm is designed for

mobile ad hoc networks. Both unicast and multicast routing is possible in AODV. It is an on

demand routing algorithm. It maintains these routes as long as they are needed by the sources. It

uses sequence numbers to identify the routes. It is a loop-free and is scalable to more no of

mobile nodes.

DSR (Dynamic Source Routing):

The Dynamic Source Routing (DSR) protocol is a on-demand routing protocol. DSR

protocol maintains the route cache to store the route. Two major phases: route discovery and

route maintenance. Whenever any node has the data to send, first it checks the route cache for

the route to the destination. If it has the route, then path is utilized otherwise, a route discovery

process is initiated by broadcasting the RREQ (Route Request) packet. RREP (Route Reply) is

International Journal of Pure and Applied Mathematics Special Issue

1338

generated whenever RREQ reaches to destination node or intermediate node which has the route

to destination in its route cache.

Route maintenance phase uses the route error message. Route error (RERR) message is

generated when transmission error is recognized. DSR is suited for small scale networks .

2.1 Blackhole attack

A blackhole is a malicious node that replies for route requests without having the route to

the destination. It exploits the routing protocol to advertise itself as having a shortest route to

destination. The data is routed in that path, source station starts sending data through the

blackhole node .

Fig 1. Detecting blackhole attack

3. WORKING PRINCIPLE OF ABCO:

ABCO(Artificial Bee Colony Optimization) is motivated by honey bees which comes under

swarm intelligence It was proposed by Karaboga [16 ] , many extensions have been made to

improve it. There are three agents in ABC algorithm,(i) scout bee (ii) onlooker bee (iii)

employed bee.

RREQ RREQ RREQ

RREP RREQ RREQ

S D

RREQ RREP

MALICIOUS NODE

SENDING FAKE RREP


1339

Scouts:

It discovers new route from the source node to the destination node. It starts from the

hive in search a food source randomly. When they return back to the hive they convey to the

foragers information about the odor of the food, its direction and the distance with respect to the

hive by performing dance.

Employee bees:

Each employee bees is assigned to one of the food source. If the new food source has

more nectar, the employee bees will replace the current food source with it. The employed bees

whose food source has been abandoned becomes a scout bee, they share the information about

the nectar amount and the position of food sources with onlooker bees by doing waggle dance.

Onlooker bees:

An onlooker bee watches the dance and selects a food source based on its nectar amount.

It does not participate in the route establishment.

Mimetic from nature:

The idea of this paper surrounds the application of Artificial Bee Colony Optimization to

the problem of MANETs. The Artificial Bee Colony Optimization mimics the behavior of Bees

in nature while they are searching for honey. Particle swarm optimization is inspired by the

behavior of flocks of birds as they fly in search of food. All these techniques are combined in

nature and when viewed in the perspective of optimization involve searching for the optimum

solution in a given search space. It has been observed that when these patterns, that are observed

in nature, are applied to complex engineering problems, they provide better solutions.

3.1 RELATED WORK

DPRAODV protocol [1] provides a very simple and effective way of providing security using

AODV against blackhole attack. The sequence number in the routing table is checked with the

threshold value. By comparing ABC and AntNet routing protocol BeeAdHoc [2] is efficient due

to less energy consumption. BeeAdHoc proves to be better than the above mentioned protocols.

Detection method for AODV routing protocol and blackhole attack performance are analysed in


1340

paper [3]. Attack detection module is implemented in AODV at source level. This method can

be used for other protocols to isolate malicious nodes in the network.

Optimized-AODV protocol [4] implements path accumulation during the route discovery process

in AODV. Optimized-AODV improves the performance of AODV under high load and high

mobility. A dendritic cell based distributed misbehavior detection system, BeeAIS-DC[5] for

BeeAdHoc. The Proposed system is inherited from the danger theory to detect the presence or

absence of danger. In [6] the VBOR protocol has two phases, Route maintenance and Route

discovery. The message authentication code is generated during route discovery phase then the

data are exchanged between the nodes.

In paper [7] survey is based on blackhole attack impact in ad hoc networks using DSR routing

protocol. It is divided into two phases: Detection before route establishment and avoidance of

malicious nodes during data forwarding. The feature of the proposed method is its simplicity and

it is effective in detecting malicious nodes. In [8] the different version in AODV is studied to

prevent and detect the blackhole attack. In paper [9] detection algorithm is proposed to detect the

blackhole attacks before the actual routing mechanism is started by using fake RREQ packets to

detect the malicious nodes.

In paper [10] modified Zone routing protocol (ZRP) is applied to detect the malicious node

which initiates blackhole attack. Paper [11] discusses about different types of attacks and in

particularly with active attacks .in Manet. In paper [12] proposes a new scalable routing protocol

NISR which is inspired by nature. In paper[13],proposed a new routing protocol ANT DSR by

using this protocol it increases the performance of network velocity and reduces delay. In this

paper we have proposed the bee mimetic algorithm using DSR routing protocol for optimized

secure routing in mobile adhoc network.

4. PROPOSED WORK

The working principles of nature inspired BM-DSR routing protocol. A source node broadcast a

route request (RREQ) to all the neighbor nodes and all routing information are stored in a routing

table. After receiving the RREQ, the destination node sends a RREP to source node based on

shortest path and the malicious nodes are interrupt the routing process and sends a fake RREP

with greatest sequence number.


1341

This paper proposes a new modified DSR, BM-DSR. In this protocol by using Bee-

Mimetic algorithm the new effective BM-DSR is proposed. The main objective of this protocol

is to provide security against blackhole attack with efficient routing from source to destination.

The shortest path routing in BM-DSR is based on hop count. During routing process the

misbehaving node may advertise itself as a shortest path using greatest destination sequence

number. To detect and remove the misbehaving node the cryptographic technique is used.

Mobile node RREQ

RREP

Malicious node

Fig 3.BM-DSR Routing

Destination source

RREQ

RREQ

RREQ

RREP

RREP

FAKE RREP


1342

4.1 Proposed algorithm:

4.1.1 Route Selection:

Si-Scouts(source)

Ei-Employee bee

Fi-foragers(destination)

(i) Si node broadcasts RREQ packets.

(ii) If the node`s cache has one or more routes, it selects the recent short route in its

route cache.

(iii) If the node`s cache does not possess a route to the foragers (Fi) route discovery is

initiated

(iv) The Employee bee (Ei) receives new RREP and forwarded to source node.

(v) The source node initiates to transmit data packets.

4.1.2 Identification and removal of misbehaving nodes:

(i) Set the destination sequence number in routing table.

(ii) Scouts (Si) broadcasts the RREQ packets to all the Employee bees(Ei).

(iii) Based on RREP the foragers(Fi) sends back the RREP packet to scouts.

(iv) If (DSN > threshold value)

(v) malicious node detected

a. If (node==malicious)

Create Dictator node

Dictator node: (it can share the key at initial time)

Normal node: (normal mobile node)

b. Dictator node initially sends the Group ID key to all the mobile nodes.

If node has GroupID

d. If node (x) wants to communicate with another node

Node x generates the hash code

Encrypting code using RSA algorithm, transmit.

e. Destination node verifys the encrypted message using group ID


1343

if match found

node y can send data to source node x

else ignore

(vi) After finding the trusted node, data packet will be transmitted securely.

5. SIMULATION ENVIRONMENTIMPLEMENTATION

The experiments for the evaluation of the scheme that validate the malicious node

detection and packet delivery ratio of the proposed scheme against blackhole nodes have been

carried out using the network simulator NS-2 with VMware based back-Ground.

6. RESULT ANALYSIS & DISCUSSION

Performance were analysed based on packet delivery ratio(PDR) and End to End delay.

Packet delivery ratio(PDR): The ratio of the number of delivered data packet to the destination.

This illustrates the level of delivered data to the destination.

PDR=∑ Number of packet receive /∑ Number of packet send

Network space :1200*1200

No of nodes :50

Simulation time :100s

Traffic model :CBR

Packet size :512Bytes

Mobility model :Random way point

Medium access protocol :IEEE 802.11

Maximum speed :30m/s


1344

Table 1.Time Vs Packet Delivery Ratio

TIME(s)

AODV(Packets)

DSR(Packets)

BM-DSR(Packets)

20 45 55 60

40 42 50 59

60 40 60 80

80 38 57 74

100 39 55 60

Fig.4 Time Vs Packet Delivery Ratio

Table 1 and fig.4 shows the performance of proposed BM-DSR routing protocol with existing

routing protocols AODV and DSR. The proposed BM-DSR approach has 5% - 15% increase in

packet delivery ratio when compared to the existing routing protocols.

End to End delay: The average time taken by a data packet to arrive in the destination. It

also includes the delay caused by route discovery process and the queue in data packet

transmission. Only the data packets that successfully delivered to destinations that counted.

0

10

20

30

40

50

60

70

80

90

20 40 60 80 100

pac

ket

de

live

ry r

atio

Time(s)

COMPARE WITH AODV,DSR,BM-DSR

AODV

DSR

BM-DSR


1345

Delay=∑ ( arrive time – send time ) / ∑ Number of nodes

Table 2.Time Vs Packet Delivery Ratio

Delivery

time(sec)

AODV

(Delay in ms)

DSR

(Delay in ms)

BM-DSR

(Delay in ms)

20 120

27 0

40 85

30 26

60 240

28 0

80 110

35 17

100 145

38 12

Fig.5 Delivery time Vs Delay

Table 2 and Fig 5 shows the End to End delay for existing routing protocol with proposed BM-

DSR protocol.

VI.CONCLUSION & FUTURE WORK

0

50

100

150

200

250

300

20 40 60 80 100

De

lay

(ms)

Delivery Time(s)

End to End Delay for AODV,DSR and BM-DSR

AODV

DSR

BM-DSR


1346

Secure routing protocol is proposed for improving the performance in terms of packet

delivery ratio and reduced delay. As the network topology in MANETs constantly changes over

time due to the node mobility, the simple use of a static profile is not efficient.

In this paper, we presented a dynamic approach based on Bee-Mimetic algorithm using

AODV and DSR routing protocol. This paper focused on secure data transmission and to detect /

remove blackhole attacks.

AODV has better scalability and its header size is relatively constant. However, AODV

maintains only one route per destination. One of the major issues in AODV is whenever a link

failure occurs, a route discovery has to be discovered. It leads to more overhead, delays and

packet loss. The DSR protocol is stable and it has reduced overhead. DSR uses multiple paths

and it does not send the packet as AODV in same route. It stores all routing information

extracted from neighboring packets.

The modified Bee-Mimetic DSR achieves higher packet delivery compared to AODV

and DSR and also the data packets are transmitted in a secured manner.

The proposed scheme suffers from overhead that it would affect the performance of

packet delivery ratio when the size of the network is increased. Hence in future the proposed

scheme has to be implemented by increasing the number of node beyond 100 and also the size of

the network should be scalable , without compromising the black hole detection process for

secured routing .

REFERENCES

[1] Payal N. Raj & Prashant B. Swadas, “DPRAODV: A DYANAMIC LEARNING SYSTEM

AGAINST BLACKHOLE ATTACK IN AODV BASED MANET” , International Journal of

Computer Science Issues, Vol. 2, 2009.

[2] Deepika Chaudhary, “Bee-Inspired Routing Protocols for MobileAd HOC Network

(MANET)”, Journal of emerging technologies in web intelligence, vol. 2, no. 2, 2010.

[3] Vipin Khandelwal & Dinesh Goyal, “BlackHole Attack and Detection Method for AODV

Routing Protocol in MANETs”, International Journal of Advanced Research in Computer

Engineering & Technology, Vol. 2, Issue 4, 2013.


1347

[4 ] Dr. Aditya Goel & Ajaii Sharma, “ Performance Analysis of Mobile Ad-hoc Network Using

AODV Protocol”, International Journal of Computer Science and Security, Vol.3, Issue 5.

[5] Nauman Mazhar Muddassar Farooq, “A Sense of Danger: Dendritic Cells Inspired Artificial

Immune System for MANET Security”, GECCO, page.12–16, 2008.

[6] K.Pazhanisamy & Lathaparthiban, “Secure Route Discovery in Mobile Ad-Hoc Network

Using MAC Based Group Key Management Protocol”, International Journal of Advanced

Research in Computer Science & Technology, 2014.

[7] K.Mahamuni & C.Chandrasekar, “Mitigate BlackHole Attack In Dynamic Source

Routing (DSR) Protocol By Trapping”, International Journal of Computer Science Issues, Vol.

10, Issue 4, 2013.

[8] Sakshi Jain, “Review of Prevention and Detection Methods of BlackHole Attack in AODV-

based on Mobile Ad Hoc Network”, International Journal of Information and Computation

Technology.ISSN 0974-2239, Vol. 4, No. 4, pp. 381-388, 2014.

[9] Chander Diwaker & Sunita Choudhary, “ Detection of blackhole attack in dsr based manet”,

International Journal of Software and Web Sciences, 2013.

[10] Himani Yadav & Rakesh Kumar, “ Identification and Removal of Black Hole Attack for

Secure Communication in MANETs”, International Journal of Computer Science and

Telecommunications, Vol. 3, Issue 9, 2012.

[11] K.Udhayakumar, T. Prasanna venkatesan & R.Ramkumar, “Security Attacks and Detection

Techniques for MANET”, International Journal of Computer Applications, page no. 0975 –

8887, 2014.

[12] Sajjad Jahanbakhsh Gudakahriz , Shahram Jamali & Esmaeel Zeinali, “NISR: A Nature

Inspired Scalable Routing Protocol for Mobile Ad Hoc Networks”, Vol. 1, Issue 4, page no.178-

182, 2011.

[13] Thiyam Romila Devi, Rameswari Biswal, Vikram Kumar & Abhishek Jena,

“Implementation of dynamic source routing in mobile ad hoc network”, International Journal of

Research in Engineering and Technology, Vol. 02 Issue. 11,2013.

[14]Parman &,S.C Sharma, “Comparison of Routing Protocols for MANET and Performance

Analysis of DSR Protocol”, Springer Berlin Heidelberg 2011.


1348

[15] Nilesh P. Bobade1 & Nitiket N. Mhala, “performance evaluation of aodv and dsr on-

demand routing protocols with varying manet size”, International Journal of Wireless & Mobile

Networks, Vol. 4, no. 1, 2012.

[16] Karaboga & Basturk 2008, “On the Performance of Artificial Bee Colony (ABC)

Algorithm, Science Direct Applied Soft Computing, vol. 8, no. 1, pp. 687-697.


1349

bee -m imetic dsr based secure r outing in manet using ... · paper we have proposed the bee...

Documents