analysis of sinkhole attack in leach base d wireless...

ANALYSIS OF SINKHOLE ATTACK IN LEACH BASED WIRELESS

SENSOR NETWORK

S.Ranjeeth Kumar 1, M.Thalaimalaichamy

2, A.Umamakeswari

3

1 Department of Computer Science & Engineering,

Srinivasa Ramanujan Centre, SASTRA University,

Kumbakonam – 612001, Tamil Nadu, INDIA.

2 Department of Electronics and Communication Engineering,

Srinivasa Ramanujan Centre, SASTRA University,

Kumbakonam – 612001, Tamil Nadu, INDIA.

3School of Computing, SASTRA University,

Thirumalaisamudram, Thanjavur – 613401, Tamil Nadu, INDIA.

Abstract: Wireless sensor network (WSN) deploys tiny sensor nodes to sense physical parameters

and transmits to a central station called sink nodes or base station. Since, WSN is deployed in hostile

environment security forms a major concern for the network. In WSN protocol stack, the network

layer poses many security threats. Sinkhole attack is one of the serious network layer threat which

attracts the entire traffic towards itself and drops or selectively forwards the data packets. This attack

will lead to high data loss rate and performance degradation of the network. This research work

focuses on sinkhole attack and presents its adverse effects over the sensor network which uses a

clustering based routing protocol namely Low-Energy Adaptive Clustering Hierarchy (LEACH).

The sinkhole attack is launched on LEACH based sensor network. The simulation results shows that

the sinkhole node drops all the packets which it receives form its cluster members and it greatly

affects the network performance.

Keywords: Wireless sensor network, IDS, sinkhole attack, black hole attack

1. Introduction

Wireless Sensor Networks is comprised of densely deployed sensor nodes, which are responsible

for collecting data from the environment around and send it to the sink node (base station). The

sensor nodes have limited resources like CPU, battery power and memory, but it uses short-range

wireless communication to communicate with the base station and with each other. The base station

manages the working of the network, and also performs processing the collected data and storing

them. In WSN, the number of sensor nodes is of high magnitude, densely deployed and are prone to

failures. Furthermore, the sensor nodes use broadcast communication unlike most of the traditional

networks which uses point to point communication. Also, the most important constraint on sensor

nodes is requirement of low power consumption. Sensor nodes carry limited, generally irreplaceable,

power sources. Therefore, while traditional networks aim to achieve high quality of service (QoS)

International Journal of Pure and Applied MathematicsVolume 116 No. 24 2017, 185-197ISSN: 1311-8080 (printed version); ISSN: 1314-3395 (on-line version)url: http://www.ijpam.euSpecial Issue ijpam.eu

185

provisions, sensor network protocols must focus primarily on power conservation. As a result, the

routing protocols designed for traditional networks cannot be used for wireless sensor networks.

Hierarchical clustering is a method of arranging the nodes into a hierarchy of groups based on a

weight function. LEACH or Low Energy Adaptive Clustering Hierarchy is an energy efficient

protocol that works based on hierarchical clustering. Unlike, the usual clustering protocols where the

head continues to be the same node, LEACH involves rotation of cluster heads in a dynamic and

random manner so that energy is uniform in all the sensor nodes. There are two phases in

LEACH.LEACH involves creation of cluster, where nodes form clusters by themselves and do not

require a centralized approach. Here nodes need not directly communicate with the base station and

cluster can be formed even without the knowledge of node location. In addition, nodes need not

communicate globally to set up the clusters. During the design of cluster formation care should be

taken to ensure that nodes become cluster-heads the same number of time approximately, with the

assumption that all the nodes have same energy in the beginning. Finally, the cluster heads should be

distributed throughout the network, so that the distance, anon-cluster head nodes require to transmit

their data is minimized. A random number between 0 and 1 is chosen by the sensor node during the

set-up phase. If the chosen number is lesser compared to the threshold T (n), the sensor node is a

cluster-head. T (n) is calculated in the following equation:

T (n) = ))/1mod((1 prp

p

if nG else T (n) =0

Where p is the desired percentage to become a cluster head, r is the current round, G is the set of

nodes that have not been selected as the cluster head in the last 1/p rounds [7]. Once the election is

over, the entire set of elected cluster heads announces itself to be the cluster head by broadcasting an

ADV (Advertisement) packet. Each non-cluster head node finds the cluster head nearer to it based on

the minimum communication energy required. Having decided the cluster, the nodes send a JOIN-

REQ (Join request) packet to the corresponding cluster heads. At the end of set up phase, clusters are

created and each cluster head allots time slot for its cluster nodes using TDMA (Time Division

Multiple Access). Allocation of time slots based on TDMA ensures that each node communicates

with the cluster head during the allotted slot without collision. The steady state phase involves each

node sending its data during its allotted time. Each node in the cluster transmits its packet to the

corresponding cluster head. The cluster head aggregates data and transmits it either to the base

station or to its nearest cluster head if the base station is outside its transmission range. Thus cluster

heads are the only nodes that communicate directly with the base station. Only during their time slot

a cluster node has its radio on. Otherwise, it gets into the sleep mode which makes the cluster nodes

to reserve energy. In addition to this, dynamic allocation of cluster heads ensures that every node has

uniform energy which makes LEACH an energy efficient protocol for WSN.

1.1 Security Threats in WSN

Wireless networks face many threats from the environment. Security is a challenging issue in the

wireless platform and a major issue in the resource constrained WSN. A spoofing attack is one in

which a program successfully disguises as another by spoofing data and thereby getting an illegal

advantage. Through this the network traffic can be corrupted extensively and sometimes it results in

creating unnecessary traffic flow on the network. Selective forwarding involves forwarding certain

chosen packets while dropping the rest of them. In a sensor network using multi hop communication,

a node which chooses a malicious node’s path might lose its data owing to selective forwarding

attack. Selective forwarding not only involves dropping of few packets, but also has malicious node

dropping all the packets it receives, hence no information being forwarded. This creates a black hole.

Such attacks are effective when the attacker is external and is included explicitly in the network. In

Sinkhole attack, the attacker attracts most of the network traffic to pass through the compromised

International Journal of Pure and Applied Mathematics Special Issue

186

node thus creating a sinkhole. Many other attacks such as wormhole, selective forwarding or

eavesdropping can be started through this sinkhole attack because the malicious node receives all the

packets and hence can drop, alter or selectively forwards it. The Sybil attack can be described as an

intruder illegally taking on multiple identities. Each node in a sensor network has a unique identity

and hence numerous threats can be observed. Since intruder has multiple identities, the actual nodes

may be transmitting multi-path data through the same compromised node. Two malicious nodes may

create a hidden route between them which is called wormhole attack. These nodes may be present

anywhere in the network, and the attacker records the packets at one location and tunnels them to

another location. The tunnelling of bits could be done selectively. There is another case where the

attackers may create a sinkhole by attracting their neighbour nodes for fast routing to the base

station. This can occur when the routing based on location is employed. There are two major security

mechanisms are available to defend these attacks namely, low level and high level. The low level

security mechanism includes secret key establishment, data privacy and secure authentication. The

high level security mechanism includes secure data aggregation and communication, Intrusion

Detection System (IDS) [7].

The remaining paper is organized as follows. The brief survey about the related articles is given in

Section 2. Section 3 presents the sinkhole attack. The attack analysis is given in Section 4. The

Section 5 concludes the paper with future directions.

2. Literature Survey

Wireless sensor network, owing to its operation in open area is prone to large number of threats.

Hence security in WSN has been a widely preferred research topic. There are few work done on all

possible security attacks in WSN’s. The efficient intrusion detection system with low overhead on

routing protocol was proposed by Nagai et al [1]. This robust algorithm checks data consistency and

identifies the intruder by checking the network flow information. They also proposed the detection

of sinkhole attack in an asymmetric many-to-one communication pattern. In [2], the possible

network layer attacks along with simple ways to resolve each one of them is given. One among the

several network layer attacks namely Sinkhole attack, seems to grab attention of the researchers

because this attack in turn leads to several other attacks thereby damaging the network to a large

extent.In [3], various ways to launch the sinkhole attack are given. The base station is identified as

the trusted member in the network. Depends on the sequence number, the sinkhole attack was

launched and subsequently the packet transmission was performed through the Ad Hoc On-Demand

Distance Vector (AODV) protocol to identify the malicious activity of theintruder. S.Ahmad Salehi

et.al [4] proposed an intrusion detection system for detecting sinkhole attack in the WSN. It is a two-

step base station analysing the network routing patterns. In [5], the effect of wormhole attack on

clustered environment is given. This attack can create a separate tunnel through which the data is

transferred to the malicious nodes also be used to launch the sinkhole attack by making one of the

wormhole nodes as sinkhole. This attack can be made as a platform to launch further attacks like

selective forwarding, hello flood and so on [14]. In [8], the possible ways of launching sinkhole

attack from the intruder’s point of view is given. Considering the intruder’s ways of launching will

help in devising a better IDS. The same set of authors has also proposed an IDS that detects sinkhole

attack in WSN. Most of the paper listed above describe sinkhole attack in general and proposes an

IDS in such a way that it is not specific to any routing protocol. But LEACH being the protocol of

study, some more papers were referred. The original LEACH protocol was proposed by Wendi

Rabiner Heinzelman [9]. This protocol involves dividing the sensor nodes to clusters with each

cluster having a cluster head. The cluster heads are elected in a randomized fashion based on a

specific equation which involves the energy level of each sensor node. Every non-cluster head node

transmits data packet to its cluster head during the allotted time slot and cluster head aggregates all


187

the packets and transmits it to the base station. Only during the allotted slot every non- cluster head

node has its radio on. Otherwise, the cluster heads communicate, while the non-cluster head nodes

are in sleep mode and hence it is energy efficient. The network layer threat is more dangerous to the

WSN and sinkhole attack is one of the important security issue in WSN [18-19].

3. Sinkhole Attack

Sinkhole attack is an active attack where the compromised node attracts all the traffic towards itself.

The compromised node grabs attention from the other nodes by establishing itself to have a high

value with respect to the routing metric. As a result, the intruder gets hold of all the packets and

proceeds to launch further attacks like selective forwarding, altering packets or dropping them. The

metric used by the compromised node to attract the packet towards itself varies based on the routing

protocol. For example, if Mintroute protocol is used, the compromised node can advertise that it has

a higher link quality and thus attract packets. Apart from the metrics, even fake packets can be sent

to the sensor nodes, so that the compromised node is included in the path of packet flow. For

example, if DSR protocol is used for routing operation, the compromised node can attract packets by

sending gratuitous message claiming that it is closer to the destination or can send the fake RERR

message claiming that the link before it is broken. The sinkhole attack can be detected by the Method

using Geographical frailty survival model and distributed monitoring by analyzing a particular

region in the sensor field [10]. Themitigation is the next approach to identify the intruders in the

affected region. This method of identifying the sinkhole nodes is computationally very expensive.

Thus, the sinkhole node is a serious threat to the routing layer of the network and reduces the

efficiency of the routing protocol. Cryptographic schemes like key establishment, key exchange are

also used to counter sinkhole attack [13]. This analysis study provide the ways of launching the

attack by the intruders and the effects of the attack on the network. The sinkhole attack brings the

network lifetime by decreasing the energy level of the sensor node [11]. When the attack happens in

a network, then the packet delivery ratio is also dropped to a greater extent [12]. The sinkhole attack

serve as a platform to launch further attacks and creates more damage to the network [20].

CN

SN

SN

SN

SN

SN

SN

BSBS

CN – Compromised Node SN – Sensor Node BS – Base Station

SN

SN

SN

Figure 1: Sinkhole attack

4. Attack Analysis

LEACH protocol works in two phases namely the set- up phase and the steady state phase. Set-up

phase involves electing the cluster heads, while the steady state phase involves transferring of data

packets from the cluster nodes to cluster heads and from the cluster heads to the base station.


188

In Figure 2, the circled nodes in the depicted picture namely nodes with ID’s 8, 11, 26 and 29

denotes the initial cluster heads in the configured scenario. At the end of set up phase, cluster heads

are elected and the nodes in each cluster are ready for the data transmission.

Figure 2: Set-Up Phase

Upon choosing the cluster heads, the steady state phase starts, where the data transfer happens. As

mentioned previously, only the cluster heads and the base station receive data packets. All the cluster

heads will not be within the transmission range of the base station. So, to transfer data from a cluster

head which is not within the transmission range of the base station, the data packets are first sent to

that cluster head and then cluster head transmits the data to its neighbouring cluster head which in

turn can transfer the data to the base station (provided the neighbouring cluster head is within the

transmission range of the base station). In Figure 3, Node 8 being the cluster head gets data packets

from its cluster nodes i.e., node 3 which is one of its cluster member.

Figure 3: Node 3 sending data to node 8

In Figure 4, since node 8 doesn’t fall within the transmission range of the base station, it transfers the

collected data packets to its neighboring node i.e., in the given scenario, node 26 (CH) so that node

26 can transfer it to the base station.


189

Figure 4: Node 8 sending data to node 26

In Figure 5, Cluster head 26 transfers the received data packet to the base station since it is within the

transmission range of the base station. This is the normal working principle of LEACH protocol in

the absence of any malicious activity. The next section 4.1 analyze the impact of sinkhole attack on

the LEACH protocol based WSN.

Figure 5: Node 26 sending data to Base Station

4.1 Launching of Sinkhole Attack

4.1.1 Coordinated Attack

The different ways of launching sinkhole attack in a WSN operating on LEACH protocol was

formulated after a brief study of network dynamics. In a WSN, which works on LEACH protocol, an

intruder can launch sinkhole attack only by attacking the cluster heads. This is because, sinkhole

attack works by attracting data packets and dropping/selectively forwarding them and cluster heads

are the only nodes that receive data packets from the other non- cluster head nodes. Having found

that the attack can be launched only on the cluster heads, further research was done on the different

ways oflaunching attack by compromising the cluster head nodes. It was found that there can be two

ways to launch sinkhole attack by varying the number of cluster heads being compromised. The first

method is being co-ordinated attack where all the cluster heads are compromised at once and the

next one being prolonged attack where cluster heads are compromised on at each round thereby data

packets from one cluster being dropped at each round. In Figure 6, cluster head node 8 receive data


190

from its cluster member node 3. In Figure 7, Node 8 is considered to be the sinkhole node, so it

doesn’t forward the data to other nodes.

Figure 6: Node 8 receive data from Node 3

In Co-ordinated sinkhole attack, all the cluster head nodes are compromised at the same time. This is

launched by choosing one node from each cluster i.e., say diametrically opposite nodes can be

chosen so that each of them belong to a different cluster. Upon choosing the nodes from each cluster,

those nodes are made to project higher energy so that they get elected as the cluster head.

Figure 7: Sinkhole attack on Node 8

Now that the compromised nodes have become the cluster heads, they attract all the data packets

thereby no packets reaching the base station. Thus, the throughput is literally zero which means all

the data packets are dropped in that round where all the compromised nodes become the cluster

heads. The above way of launching attack was formulated after studying the way cluster heads are

elected which showed that once a cluster node becomes a cluster head, it will then get a chance to

become cluster head again only after “p” rounds where “p” is the desired percentage to become a

cluster head [6]. This means that after one round of co-ordinated attack, no attack will be launched

for the next “p” rounds. Though one round of attack will be effective enough, the intruder will have

to wait for another “p” rounds for the next attack. This result led to the formulation of the other way

of launching the attack. The prolonged attack also works similar to the co-ordinated attack but the

number of compromised cluster heads per round is just one. That is nodes to be compromised are

chosen from each cluster and they are compromised one per round i.e., every round one of the

chosen node (to be compromised) becomes the cluster head thereby receiving data packets from that

cluster and dropping them. This means that at the end of every round, data packets from one

particular cluster do not reach the base station. The advantage of this attack over the previous one is

that the attack is prolonged and every round some amount of data packet is dropped thereby making


191

the attack more effective. Overall, both prolonged and co-ordinated attack seems to bring in a huge

loss to the network because data packets are lost in both the cases. However based on the way the

attack is launched, the number of data packets lost per round varies. In Figure 8, the coordinated

attack is launched on Node 11, which doesn’t forward any data that is received from its cluster

member Node 5.

Figure 8: Node 11 receives data from node 5

In Figure 9, the coordinated attack is launched on the Node 11, which doesn’t forward any data that

is received from its cluster member Node 20. The coordinated attack results in quick performance

degradation of the network, since multiple nodes are under attack. The identification of the

coordinated sinkhole attack need less effort than the single node attack. After the successful

identification of the coordinated malicious nodes, they are blocked or removed from the routing

process and avoided from further participation in the network formation. Thus it is inferred that the

coordinated attack leads to immediate performance degradation of the network.

Figure 9: Node 11 receives data from Node 20

4.1.1 Prolonged Attack

Figure 10 shows the prolonged attack in which cluster head node 8 alone act as a sinkhole node. The

data packets received from its cluster members are not forwarded further. The sinkhole node i.e.,

Node 8 drops all the packets. This increases the attack period and all the sensed data from its cluster

are dropped leading to degradation of the network performance.


192

Figure 10: Node 8 receives data from node 3

The cluster head 8 acts as a sinkhole node and drops all the packets that is received from its cluster

members. This attack prolong until the malicious node is identified and removed from the routing

process. This type of prolonged attack leads to energy hole in a particular region or cluster in which

the sinkhole node exists. The data from a particular cluster is completely blocked from reaching the

base station. The identification of the single malicious node is difficult. To identify the prolonged

attack, the region under attack should be identified initially. After identifying the region of attack,

the malicious node can be mitigated.

Figure 11: Node 8 drops the packet received from node 3

The implementation of sinkhole attack is done by blindly making the next hop value of the

corresponding cluster head to be null so that none of the data packets received by the cluster head

will have a route to the base station. This will either reduce the throughput of the network (in the

case of prolonged attack) or make the throughput of the network to zero (in the case of co-ordinated

attack).


193

5. Results and Discussion

The NETSIM simulation tool is applied to launch the sinkhole attack on LEACH based network. The

attack is launched in two different ways i.e., coordinated sinkhole attack which contains multiple

malicious nodes and another method to prolong the attack using single node in a cluster. In the

coordinated sinkhole attack, the malicious nodes cause immediate damage to the network by

droppingmore packets from different clusters. In the prolonged sinkhole attack, the attack period is

extended and the data from the single cluster is restricted from reaching base station. Table 1 show

the results obtained from the coordinated sinkhole attack. The cluster head nodes N8, N11, N26, N29

act as sinkhole nodes. These malicious nodes drops all the packets which it receives from its cluster

members. The nodeN37 is modelled as the base station. In Table 2, the prolonged sinkhole attack

results are tabulated. The cluster head node N8 act as the sinkhole node and it drops the packets

which it receives from its cluster member nodes.

Table 1 No attack

Table 2 Coordinated Sinkhole Attack

Table 3 Prolonged Sinkhole Attack

Figure 12: LEACH Normal operation

The identification of prolonged sinkhole attack is much difficult than

identifying the coordinated sinkhole attack. The prolonged attack is identified by analysing the

region or cluster which is affected by the malicious activity. This can be done by continuous

monitoring of the network traffic. In other case, the identification of coordinated sinkhole attack is

easier, since it forms energy consumption variation in the cluster. This results shows the impact of

the sinkhole attack which creates more data loss to the network.

Column1 N8 N 11 N 26 N 29 N 37

Packets Successfully Transmitted 77 74 70 70 0

Packets Received from cluster nodes 67 65 62 63 0

Column1 N8 N 11 N 26 N 29 N 37



Column1 N8 N 11 N26 N 29 N37




194

5.1 Conclusion and Future Work

Sinkhole attack is one of the serious threat in the routing layer of WSN protocol stack.

This vulnerability reduces the performance of the network in terms of energy consumption,

packet delivery rate and so on. In LEACH based clustered environment, the sinkhole attack

creates more vulnerability and information loss to the network. The clustered network depends

on the cluster head node longevity, which is reduced by this attack. This research work shows the

impact of the data loss to the network due to sinkhole attack. The attack is launched in two

different ways i.e. single node attack and coordinated node attack. The adverse effects of the

attack is studied. The graphical comparison shows the data loss information due to sinkhole

attack in two different scenarios. This analysis depicts the impact of sinkhole attack on the

network and the necessity to build an effective defensive mechanism. In future work, an energy

efficient Intrusion Detection System will be developed for LEACH based clustered network to

reduce the adverse effects of the sinkhole attack.

6. Acknowledgements

The authors would like to acknowledge SASTRA University for the great support and

assistance rendered to carry out this research work.

References

[1] Ngai. E.C.H, Liu.J and Lyu. M.R, An efficient intruder detection algorithm against

sinkhole attacks in wireless sensor networks,Computer communications. (2006). 2353-

2364.

[2] Karlof. C and Wagner.D, Secure routing in wireless sensor networks: Attacks and

countermeasures. AdHoc Networks Journal, 1(2003), 293–315.

[3] Tejinderdeep Singh and Harpreet Kaur Arora, Detection and Correction of Sinkhole

Attack with Novel Method in WSN Using NS2 Tool. International Journal of Advanced

Computer Sciences and Applications, 4 (2013), 32-35.

[4] Ahmad Salehi. S, Razzaque.M.A, Parisa Naraei and Ali Farrokhtala, Detection of

Sinkhole Attack in Wireless Sensor Networks, IEEE International Conference on Space

Science and Communication, IconSpace, Melaka, Malaysia (2013).

[5] Priya Maidamwar and Nekita Chavhan, Impact of Wormhole Attack on Performance of

LEACH in Wireless Sensor Networks,International Journal of Computer Networking,

Wireless and Mobile Communications (2013) 21-32.

[6] Amrinder Kaur, Sunil Saini, Simulation of Low Energy Adaptive Clustering Hierarchy

Protocol for Wireless Sensor Network. International Journal of Advanced Research in

Computer Science and Software Engineering,3 (2013) 1316-1320.

[7] Padmavathi.G, and Shanmugapriya. D.A Survey of Attacks, Security Mechanisms and

Challenges in Wireless Sensor Networks,International Journal of Computer Science and

Information Security. 4(2009) 1-9.

[8] Krontiris. I, Dimitriou. T,Giannetsos. T, and Mpasoukos. M, Intrusion detection of

sinkhole attacks in wireless sensor networks. In 3rd International Workshop on


195

Algorithmic Aspects of Wireless Sensor Networks, AlgoSensors ’07, Wroclaw, Poland,

(2007)150-161.

[9] Wendi Rabiner Hienzelman, Anantha Chandrakasan and Hari Balakrishnan. Energy-

efficient communication protocol for wireless micro sensor networks. In 3rd

Hawaii

International Conference on System Science, (2000) 1-10.

[10] Shafiei. H, Khonsari. A, Derakhshi. H, and Mousavi. P. Detection and Mitigation of

Sinkhole attacks in wireless sensor networks. Journal of Computer and System

Science.80 (2014), 644-653.

[11] Padmalaya Nayak, V. Bhavani, Impact of Black Hole and SinkHole Attacks on Routing

Protocols for WSN. International Journal of Computer Applications, 116 (2015), 42-46.

[12] Usha. G, and Bose. S. Impact of Sinking Behaviour in Mobile Adhoc Network.

International Journal of Ad Hoc, Sensor & Ubiquitous Computing. 3(2012), 95-104.

[13] Anthonis Papadimitriou et al. Cryptographic Protocols to Fight Sinkhole Attacks on Tree-

based Routing in Wireless Sensor Networks. In 5th

IEEE Workshop on Secure Network

Protocols, (2009), 43-48.

[14] Ranjeeth Kumar Sundrarajan, Umamakeswari Arumugam. Intrusion Detection Algorithm

for Mitigating Sinkhole Attack on LEACH protocol in Wireless Sensor Networks.

Journal of Sensors, vol.15 (2015).

[15] Kahina CHELLI. Security Issues in Wireless Sensor Networks: Attacks and

Countermeasures. In Proceedings of the World Congress on Engineering, London, UK,

(2015) 519-524.

[16] Hero Modares, Rosli Salleh and Amirhossein Moravejosharieh. Overview of Security

Issues in Wireless Sensor Networks. In 2011 International Conference on Computational

Intelligence, Modelling and Simulation, (2011) 308-311.

[17] Yong Wang et al. A Survey of Security Issues in Wireless Sensor Networks. IEEE

Communications Surveys. 8(2006), 2-23.

[18] Al-Sakib Khan Pathan et al. Security in Wireless Sensor Networks: Issues and

Challenges. In International conference on Advanced Computing Technologies, (2006)

1043-1048.

[19] Kashif Saghar et al. RAEED: A Formally Verified Solution to Resolve Sinkhole Attack

in Wireless Sensor Network,In 13th

International Bhurban Conference on Applied

Sciences & Technology, Islamabad, Pakistan (2016), 334-345.

[20] Keerthana. G and Padmavathi.G, Detecting Sinkhole Attack in Wireless Sensor Network

using Enhanced Particle Swarm Optimization Technique,International Journal of

Security and Its Applications, 10(2016), 41-54.


196

analysis of sinkhole attack in leach base d wireless...

Documents