Secure information Collection in Wireless Sensor Networks

Using Randomized Routes Approach

Mughele Ese Sophia; School of Science and Technology, Computer

Science Option.

Delta State School of Marine Technology, Burutu. DESOMATEC Delta

State Nigeria.

E-mail: prettysophy77@yahoo.com

Ekpoh Chukwunwike Ustus; Information and Communication Technology

(ICT). Delta State School of Marine Technology, Burutu. DESOMATEC

Delta State Nigeria.E-mail:blessed_mario@yahoo.com

ABSTRACT

In wireless sensor network there are various possible security threats encountered during data

delivery, among the various possible threats like information security, node failure, etc. we are

presenting this paper in order to conquer the ‘blackholes’ that are formed due to

compromised-node (CN) and denial-of-service (DoS) by using some routing mechanisms

approach. The existing multi-path routing approaches are vulnerable to such attacks, mainly

due to their deterministic nature. Compromised-node and denial-of-service are two key attacks

in Wireless sensor networks (WSNs). We have developed a structure that generates randomized

routes. Under this design the routes taken by the “shares” of different packets change over time

to time increasing the probability of randomness of paths to be selected for transferring the

data. Hence, even though adversary or offender comes to know about the routing algorithm

still it cannot pinpoint the routes in where each packet is roam randomly. Apart from

randomness, the routes that are generated by these mechanisms are energy efficient as well as

dispersive which ultimately make them capable of circumventing the blackholes at less energy

cost. Extensive frameworks are conducted to verify the validity of our mechanisms.

Keywords: Compromised Node (CN), Denial of service (DOS), and Wireless

Sensor Networks (WSN), Purely Random Propagation (PRP).

1.0 INTRODUCTION WIRELESS sensor networks have applications in many aspects, such as health

care, homeland

Military, security, manufacturing, environment, agriculture, and so on. In

the past several years, sensor networks have been a very active research

area. Most previous research efforts consider homogeneous sensor networks,

where all sensor nodes have the same capabilities. Most of the security

threats in WSNs are compromised node (CN) and denial of service (DOS),

kumar and kumar, www.ijera.com retrieved 20th June, (2014). In the CN

attack, an adversary physically compromises a subset of nodes to

eavesdrop information, whereas in the DOS attack, the adversary

interferes with the normal operation of the network by actively

disrupting, changing, or even paralyzing the functionality of a subset

of nodes. These two attacks are similar in the sense that they both

generate black holes areas within which the adversary can either

passively intercept or actively block data delivery. Particular node

in each route and compromise (or jam) these nodes. Such an attack can

stop all shares of the data, rendering the above counter-attack

approaches ineffective. Second, as pointed out, actually very few

node-disjoint routes can be found when the node density is moderate

and the source and destination nodes are several hops apart, Motharkar

et al (2013).

1.1 Wireless communication

According to Coils (1895) Wireless communication is the transfer of

information between two or more points that are not connected by an

electrical conductor. The most common wireless technologies use

electromagnetic wireless telecommunications, such as radio. With radio

waves, distances can be short such as a few meters for televisions or

as far as thousands or even millions of kilometers for deep-space

radio communications. It encompasses various types of fixed, mobile,

and portable applications, including two-way radios, cellular

telephones, personal digital assistants (PDAs), and wireless

networking. Other examples of applications of radio wireless technology

include GPS units, garage door openers, wireless computer mice,

keyboards and headsets, headphones, radio receivers, satellite

television, broadcast television and cordless telephones. Common

methods of achieving wireless communications include the use of light,

sound, magnetic, or electric fields, (Margaret, 2006. Examples of

wireless equipment include: Global Positioning System (GPS),Telemetry

control and traffic control systems, Professional LMR and

SMR ,Infrared and ultrasonic remote control devices, Cordless computer

peripherals, Cellular telephones and pagers, The Amateur Radio Service

(Ham radio), Consumer and professional Marine VHF radios, etc

Goldsmith, (2005).

1.2 A sensor network

A sensor network is a group of specialized transducers with a

communications infrastructure intended to monitor and record

conditions at diverse locations. Sensor networks are the key for

gathering the data needed by smart environments Young, (1964). A

sensor network is required in the present scenario that is fast and

easy to install and maintain. The individual nodes that constitute a

wireless sensor network are greatly small in size and uses power-

efficient batteries to extend their operational longevity. Every

sensor node is equipped with a transducer, microcomputer, transceiver

and power source. The transducer generates electrical signals based on

sensed physical effects and phenomena.

A WSN is a wireless network consisting of spatially distributed

autonomous devices using sensors to monitor physical or environmental

conditions. A WSN system consolidates a gateway that provides wireless

connectivity back to the wired world and distributed nodes. The

building-up of wireless sensor networks was inspired by military

applications like surveillance in war zones. Today, they consist of

shared independent devices that use sensors to monitor the physical

conditions, for instance vibration, movement and temperature as well

as sound. The WSN is built of nodes from a few to several hundreds or

even thousands, where in each node is connected to one (or sometimes

several) sensors.

Figure 1: Wireless Sensor Networks Wikipedia (1997).

1.2. Typical multi-hop wireless sensor network architecture

WSNs will open the gates to the wireless revolution. In creating a

practical wireless network can be a depressing task unless the

concepts are made simple. In many WSN applications, the deployment of

sensor nodes is performed in an ad hoc model without careful planning

and engineering. Once deployed, the sensor nodes must be able to

autonomously organize themselves into a wireless communication

network. In most cases it is very difficult and even impossible to

change or recharge batteries for the sensor nodes Tao et al, (2010).

However, the new wireless technologies will likewise structure the

society in unpredictable ways. A denial-of-service attack (DoS attack)

or distributed denial-of-service attack (DDoS attack) is an effort in

making a computer resource unavailable to its intended users. Although

the channel to carry out, motives for, and targets of a DoS attack may

vary, it generally consists of the intensive efforts of person or

persons to prevent an Internet site or service from functioning

efficiently temporarily or indefinitely. A denial-of-service attack is

characterized by an explicit attempt by attackers to prevent

legitimate users of a service from using that service. There are two

general forms of DoS attacks: those that crash services and those that

flood services.

Figure 2: Typical multi-hop wireless sensor network architecture Wikipedia (1997) .

This section discusses with different type of attacks in wireless

sensor network: Eitaro et al (2012)

A. Node capture attack: The confidentiality and integrity can be compromised

by physically capture the sensor node and extract the data from their

memory is called Node Capture Attack. This can manage the sensor node

and use for further attacks.

B. Compromised node: The sensor node distributes in a large number of

areas and cannot be monitored. So, the attacker goes into the wireless

network and compromise the sensor node. The attacker can get

cryptographic keys, information and control the sensor node which part

of wireless sensor network.

C. Denial of service (DOS): The Denial of service (DoS) attack tries to convey

unnecessary packets and utilize more network bandwidth. It prevents

the network user from accessing the service or resource which they

need to communicate. The DoS attack could be in Physical layer, link

layer, network layer and transport layer.

Attacks can be channel at any network device, including attacks on

routing devices and web, electronic mail, or Domain Name System

servers. A DoS attack can be perpetrated in many ways. The five basic

types of attack are:

• Disruption of physical network components.

• Disruption of state information, such as unsolicited resetting of

TCP sessions.

• Consumption of computational resources, such as bandwidth, disk

space, or processor time.

• Obstructing the communication media between the intended users and

the victim so that they can no longer communicate adequately.

• Disruption of configuration information, such as routing

information, Misra, et al, (2009).

DoS attack may include execution of malware intended to:

Trigger off errors in the sequencing of instructions, so as to

force the computer into an unstable state or lock-up.

Damage the operating system itself.

Exploit errors in the operating system, causing resource

starvation thrashing available facilities so no real work can

be accomplished.

Maximize usage of processor, preventing any work from occurring.

Trigger off errors in the microcode of the machine, Singal (2014).

Node compromise detection It is a difficult security requirement

for a favorable deployment of large-scale wireless sensor

networks. A node compromise attack often consists of three

stages:

i. The first stage is physically obtaining and compromising the

sensors.

ii. The second stage is redeploying the compromised nodes back to

the sensor network.

iii. The last stage is compromised sensors rejoining the network and

launching attacks

These two attacks are alike in the sense that both procreate black

holes and the areas within which the opponent can either passively

intercept or actively block data delivery.

A conventional cryptography-based security method cannot singly

provide satisfactory solutions to these problems. This is because once

a node is compromised; the adversary can always acquire the secret

keys of that node, and thus can intercept any information passed

through it. At the same time, a rival can always perform certain form

of DOS attack (e.g., jamming) even if it does not have any knowledge

of the crypto-system used in the WSN. One solution to these attacks is

to exploit the network’s routing performance. Specifically, if the

locations of the black holes are known a priori, then information can

be delivered over paths that bypass these holes, whenever possible

typically through a two-step process. First, the packet is broken into

M shares (i.e., components of a packet that carry partial information)

using a ðT; MÞ-threshold secret sharing mechanism such as the Shamir’s

algorithm. The original information can be recovered from a

combination of at least T shares, but no information can be guessed

from less than T shares. Second, multiple routes from the source to

the destination are computed according to some multipath routing

algorithm. The M shares are then distributed over these routes and

delivered to the destination. As long as at least M _ T þ 1 (or T)

shares bypass the compromised (or jammed) nodes, the adversary cannot

acquire (or deny the delivery of) the original packet.

We contend that three security problems subsist in the upon counter

attack approach:

• This approach is no longer valid if the attacker can selectively

compromise or jam nodes. This is because the route computation in

the above multipath routing algorithms is deterministic for a

fixed topology, a fixed set of routes are always computed by the

routing algorithm for given source and destination.

• Secondly, as pointed out in, actually very few node-disjoint

routes can be found when node density is moderate and source and

destination nodes are several hops apart. The lack of enough

routes significantly undermines the security performance of this

multipath approach.

• Finally, even worse, because the set of routes is computed under

certain constraints, the routes may not be spatially dispersive

enough to avoid a moderate-sized black hole.

In this research, we propose a randomized multipath routing algorithm

that can overcome the above issue. In this algorithm, multiple paths

are created in a randomized way whenever a data packet needs to be

sent, such that the set of routes taken by different shares of various

packets keep alternating time to time and a large number of routes can

be potentially created for each source and end. To intercept various

packets, the adversary has to compromise or jam all possible routes

from the source to the destination, which is basically impossible.

Because routes are now randomly generated, they may no longer be node-

disjoint. However, the algorithm ensures that the randomly generated

routes are as dispersive as possible, i.e., the routes are

geographically separated as far as possible such that they have high

likelihood of not simultaneously passing through a black hole.

Considering the stringent constraint on energy consumption in WSNs,

the main challenge in our design is to generate highly dispersive

random routes at low energy cost. As explained later, such a challenge

is not trivial. A naive algorithm of generating random routes, such as

Wanderer scheme (a pure random-walk algorithm), only leads to long

paths containing many hops, and therefore, consuming lots of energy

without achieving good dispersiveness. Due to Security considerations,

we also require that the route computation be implemented in a

distributed way, such that the final route represents the aggregate

decision of all the nodes participating in the route selection. As a

result, a small number of compromised nodes cannot dominate the

selection result. In addition, for efficiency purposes, we also

require that the randomized route selection algorithm only incurs a

small amount of communication overhead, Misra et al,( 2005).

1.4 RELATED WORK

Recently, several works have taken security metrics into account when

constructing (deterministic) multi-path routes. Specifically, the

SPREAD algorithm in attempts to find multiple most-secure and node-

disjoint paths. The security of a path is defined as the likelihood of

node compromise along that path, and is labeled as the weight in path

selection. A modified Dijkstra algorithm is used to iteratively find

the top- K most secure node-disjoint paths. The H-SPREAD algorithm

improves upon SPREAD by simultaneously accounting for both security

and reliability requirements, Lou and Kwon, (2006).

Lee et al., (2007) presents distributed Bound-Control and Lex-Control

algorithms, which compute multiple paths, respectively, in such a way

that the performance degradation (e.g., throughput loss) is minimized

when a single-link attack or a multi-link attack happens. Other

examples of secure deterministic multi-path routing algorithms include

SRP, SecMR, Papadimitratos and Haas, (2002). Existing randomized

multi-path routing algorithms in WSNs have not been designed with

security considerations in mind, largely due to their low energy

efficiency. To the best of our knowledge, the work presented in this

paper fills a void in the area of secure randomized multi-path

routing. Specifically, flooding is the most common randomized multi-

path routing mechanism. As a result, every node in the network

receives the packet and retransmits it once. To reduce unnecessary

retransmissions and improve energy efficiency, the Gossiping algorithm

was proposed as a form of controlled flooding whereby a node

retransmits packets according to a pre-assigned probability. It is

well known that the Gossiping algorithm has a percolation behavior, in

that for a given retransmission probability, either very few nodes

receive the packet, or almost all nodes receive it. Parametric

Gossiping was proposed in to overcome the percolation behavior by

relating a node’s retransmission probability to its hop count from

either the destination or the source. A special form of Gossiping is

the Wanderer algorithm, whereby a node retransmits the packet to one

randomly picked neighbor, Barrett et al, (2003). When used to counter

compromised-node attacks, flooding, Gossiping, and parametric

Gossiping actually help the adversary intercept the packet, because

multiple copies of a secret share are dispersed to many nodes. The

Wanderer algorithm has poor energy performance, because it results in

long paths. In contrast, the NRRP, DRP, and MTRP schemes proposed in

this paper are specifically tailored to security considerations in

energy constrained WSNs. They provide highly dispersive random routes

at low energy cost without generating extra copies of secrete shares.

SYSTEM ANALYSIS Barrett et al, (2003).

1.4.1 EXISTING SYSTEM

SPREAD algorithm in attempts to find multiple most-secure and node-

disjoint paths. The security of a path is defined as the likelihood of

node compromise along that path, and is labeled as the weight in path

selection. A modified Dijkstra algorithm is used to iteratively find

the top- K most secure node-disjoint paths. The H-SPREAD algorithm

improves upon SPREAD by simultaneously accounting for both security

and reliability requirements. Distributed Bound-Control and Lex-

Control algorithms, which computes multiple paths, respectively, in

such a way that the performance degradation (e.g., throughput loss) is

minimized when a single-link attack or a multilink attack happens,

respectively. Flooding is the most common randomized multi-path

routing mechanism. In this regard, every node in the network receives

the packet and retransmits it once. To decrease unnecessary

retransmissions and pick up energy efficiency, the Gossiping algorithm

was propounded as a form of controlled flooding, whereby a node

retransmits packets according to a pre-assigned probability.

Parametric Gossiping was propound to overcome the percolation

character by relating a node’s retransmission probability to its hop

count from either the destination or the source as shown in figure 2.

A special form of Gossiping is the Wanderer algorithm, whereby a node

retransmits the packet to one randomly picked neighbor. When used to

counter compromised node attacks, flooding, Gossiping, and parametric

Gossiping actually help the opponent to intercept or block the packet,

because multiple copies of a secret transmission are dispersed to many

nodes, Karunakaran and Venkatesh, (2012).

According to Motharkar et al (2013) The following are the

disadvantages of existing system

• The Wanderer algorithm has low energy performance, because it

results in long paths.

• Multi-path routing mechanism, Gossiping algorithm has a percolation

behavior, in that for a given retransmission probability, either

very few nodes receive the packet, or almost all nodes receive it.

• Existing randomized multi-path routing algorithms in WSNs have not

been designed with security considerations in mind, largely due to

their poor energy efficiency.

1.4.2 PROPOSED SYSTEM

The proposed solution is to create a randomized multi-path routing

algorithm that can conquer the black holes formed by Compromised-node

and denial-of-service attacks. Instead of choosing paths from a pre-

computed set of routes, our aim is to compute multiple paths in a

randomized form each time a data packet needs to be sent, such that

the set of routes taken by distinct shares of different packets keep

changing over time. To intercept different packets, the intruder has

to compromise or jam all possible routes from the source to the

destination, which is practically infeasible.

According to Motharkar et al (2013) The following are the advantages

of existing system.

• Provides highly dispersive random routes at low energy cost without

generating extra copies of secrete shares.

• If the routing algorithm becomes known to the adversary, the

adversary still cannot pinpoint the routes traversed by each packet

• Energy efficient

Advantages of DDRA Algorithm

Cost is low compare to cryptographic technique.

It’s applicable for wired and wireless networks.

Number of retransmission is less

SYSTEM DESCRIPTION

Steps for Proposed Approach

Enter the number of nodes to form a network.

Enter the node name, IP address and port number for each node.

Enter the maximum possible paths between the nodes to send the

data from source to destination.

Login each node to activate it in the network.

Enter the source and destination node and select the text file

which is to be send.

After selecting the files apply the Randomize Dispersive Routing

algorithm, which breaks the file into multiple packets and as a

result the multiple paths are generated.

Each packet is sent through randomized path and all the packets

reach to the destination successfully.

Data Flow Diagram: Motharkar et al (2013).

1.5 RANDOMIZED MULTIPATH DELIVERY

Randomized multipath delivery proposed by Tao, Liu and karuz ,

(2010), Data delivery mechanism main drawback is black hole attack.

When using multipath routing attacker can easily get the data, so it

avoids multipath routing. If randomly sent the data to the designation

and attacker doesn’t get the data easier. Sensor node sent the data

randomly and can save more energy, Anri et al., (2012). The randomized

multipath delivery is used sent the data securely by using multi-hop

routing. Each node randomly select by neighbor nodes. Purely random

propagation is mainly based on one –hop neighbor if sensor node sent

the information from the source to designation and mainly based on

neighbor list and all sensor nodes ID when sensor node sent the

information to the sink node based on TTL values. In considering the

three-phase approach for secure data delivery in a WSN as shown below

• Secret sharing of information,

• Randomized propagation of each information share, and

• Normal routing (e.g., min-hop routing) toward the sink.

Figure 4: Randomized dispersive routing in a WSN. (EXTRACTED FROM

www.secs.oakland.edu) .

The effect of route dispersiveness on bypassing black holes is

illustrated in Fig.4, where the dotted circles represent the ranges

the secret shares can be propagated to in the random propagation

phase. A larger dotted circle implies that the resulting routes are

geographically more dispersive. It is clear that the routes of higher

dispersiveness are more capable of avoiding the black hole.

1.5 Randomized Dispersive Routing Algorithm Formula

M – T + 1

Where,

M= Multiple routes from the source to the destination are computed

according randomized routing algorithm.

T = Original information can be recovered from a combination of at

least T shares.

More specifically, when a sensor node wants to send a packet to the

sink, it first breaks the packet into M shares, according to a (T, M)

-threshold secret sharing algorithm. Each share is then transmitted to

some randomly selected neighbor. That neighbor will continue to relay

the share it has received to other randomly selected neighbors, and so

on. In each share, there is a TTL field, whose initial value is set by

the source node to control the total number of random relays. After

each relay, the TTL field is reduced by 1. When the TTL (Time to live)

value reaches 0, the last node to receive this share begins to route

it toward the sink using min-hop routing. Once the sink collects at

least T shares, it can reconstruct the original packet. No information

can be recovered from less than T shares.

Figure 5: Implication of route depressiveness on

bypassing the black hole. (Extracted from www.secs.oakland.edu).

(a) Routes of higher depressiveness. (b) Routes of lower

depressiveness.

The upshot of route depressiveness on bypassing black holes is

illustrated in the above figure. A larger dotted circle implies that

the resulting routes are geographically more dispersive. Comparing the

two cases in the above Figure, it is clear that the routes of higher

depressiveness are more capable of avoiding the black hole. Clearly,

the random propagation phase is the key component that dictates the

security and energy performance of the entire mechanism.

1.6 Random Propagation of Information Shares

To diversify routes, an ideal random propagation mechanism or

algorithm that would propagate shares depressively as much as

possible. Typically, this means propagating the shares farther from

their source and towards the sink. At the same time, it is highly

desirable to have an energy-efficient propagation, which calls for

limiting the number of randomly propagated hops. Now the challenge

here lies in the random and distributed nature of the propagation i.e.

a share may be sent one hop farther from its source in a given step,

but may be sent back closer to the source in the next step, wasting

both steps from a security point of view. To tackle this issue, some

control needs to be imposed on the random propagation process.

Generally we have four types of schemes:

Multicast Tree-Assisted Random Propagation

Directed Random Propagation

Non- repetitive Random Propagation

Purely Random Propagation (Baseline Scheme)

The random routes generated by the four algorithms are not necessarily

node disjoint. Note that the security analysis for the CN and DOS

attacks is similar because both of them involve calculating the packet

interception probability. For brevity, we only focus on the CN attack

model. The same treatment can be applied to the DOS attack with a

straightforward modification. Basically this paper involves three

important steps for implementing secure data transmission/collection

in WSN’s using some programming language like java and database like

ORACLE is as follows which include three modules:

o Topology Construction

o Randomized multipath routing

o Message Transmission

1.7 Topology Construction

In this module, we construct a topology structure. Here we use mesh

topology because of its unstructured nature. Topology is constructed

by getting the names of the nodes and the connections among the nodes

as input from the user. While getting each of the nodes, their

associated port and IP address is also obtained. For successive nodes,

the node to which it should be connected is also accepted from the

user. While adding nodes, comparison will be done so that there would

be no node duplication. Then we identify the source and the

destinations.

1.8 Randomized Multipath Routing

We achieve randomized multipath routing that can conquer the

Compromised Node attack & Denial of Service attack. Here several paths

are computed in a randomized pattern each time an information packet

needs to be sent. In this context a large number of routes can be

potentially produce for each source and destination as shown in figure

6. To capture different packets, the offender need to compromise and

squash all possible routes from the source to the destination, which

is practically not possible.

Figure 6: Randomized Multipath Routing Burmester, and Le (2004)

C. Message Transmission

Here we transmit the message from source to destination. For each

transmission we choose a random path, in that only the packet is

transmitted. Pure Random Propagation (PRP): Shares are propagated based on

one-hop neighborhood information. Particularly, a sensor node

conserves a neighbor list, which contains the identities of all nodes

within its transmission range. When a source node wants to send data

to destination, it contains a TTL of initial value N in each share. It

then randomly picks a neighbor for each share, and unicasts the share

to that neighbor. After receiving the share, the neighbor first

mandates the TTL. If the new TTL is greater than 0, the neighbor

randomly picks a node from its neighbor list (this node cannot be the

source node) and relays the share to it, and so on. When the TTL

reaches 0, the final node receiving this share stops the random

propagation of this share, and starts routing it toward the sink using

normal min-hop routing.

Secured Delivery of Packets: In this module we can maintain the routing

table; here we add one more column to maintain the packet delivery

ratio. In this way we can maintain how many packets are transmitted

over each path. It will be useful to identify any path and can packets

handle packets number. We can stop transmission for some amount of

time period over that path, so that the hacker cannot identify in

which path the message is transmitted and also we can easily transmit

the data securely.

1.8 RESULT ANALYSIS

The original file will be split into Multiple Packets and transmitted

on multipath by using Randomized Dispersive Routing Algorithm formula

(M – T + 1).It also gives the Acknowledgement to the sender and the

receiver that the data is been transmitted in fully secure form and

it is Confidential to only that authorized party anyways. According to

this Algorithm, description is given in a way that tell us data is

fully transmitted and acknowledgment send to sender and receiver.

WHEN 1ST PACKET TRANSFERRED THEN T=5 M=0

M-T+1 = 0-5+1 = - 4 MEANS 4 PACKET YET TO BE RECEIVED

WHEN 2ND PACKET TRANSFERRED THEN T=5 M=1

M-T+1 = 1-5+1 = - 3 MEANS 3 PACKET YET TO BE RECEIVED

WHEN 3RD PACKET TRANSFERRED THEN T=5 M=2

M-T+1 = 2-5+1 = - 2 MEANS 2 PACKET YET TO BE RECEIVED

WHEN 4TH PACKET TRANSFERRED THEN T=5 M=3

M-T+1 = 3-5+1 = - 1 MEANS 1 PACKET YET TO BE RECEIVED

WHEN 5TH PACKET TRANSFERRED THEN T=5 M=4

M-T+1 = 4-5+1 = 0 MEANS ALL PACKET RECEIVED.

The proposed algorithm is easy to implement and compatible with

popular routing protocols, such as RIP and others. This proposed

algorithm is completely orthogonal to the work based on the designs of

cryptography algorithms and system infrastructures. Security enhanced

dynamic routing could be used with cryptography-based system designs

to further improve the security of data transmission over networks.

1.9 CONTRIBUTION TO KNOWLEDGE IN THE DEVELOPMENT OF RANDOMIZED ROUTES

FOR IMPROVING SECURITY IN DATA COLLECTION IN WIRELESS SENSOR NETWORK

This paper depicts the effectiveness of the randomized dispersive

routing in overcoming the CN and DOS attacks which is energy

efficient. By appropriately setting the secret sharing and propagation

parameters, the packet interception probability can be easily reduced

by the proposed algorithms to a better extent. Improved security

performance comes at a reasonable cost of energy. The energy

consumption of the projected randomized multipath routing algorithms

is only one to two times higher than that of their deterministic

complement algorithms. The proposed algorithms can be applied to

selective packets in WSNs to create supplementary security levels

against adversaries attacking to acquire these packets. Considering

that the percentage of packets in a WSN that require a high security

level is small, we are convinced that the selective employ of the

proposed algorithms does not significantly impact the energy

efficiency of the entire system. Thus the route generated are highly

dispersive, secure and energy efficient. The paper resolution requires

that my co-researcher can extend the mechanisms further.

CONCLUSION we are presenting this paper in order to conquer the ‘blackholes’ that are formed due to

compromised-node (CN) and denial-of-service (DoS) by using some routing mechanisms

approach. We define attack and establish taxonomy of this attack by

distinguishing different attack types. The definition and taxonomy are

very important in understanding and analyzing the threat the proposed

algorithms can be applied to selective packets in WSNs to create

supplementary security levels against adversaries attacking to acquire

these packets. Considering that the percentage of packets in a WSN

that require a high security level is small, we are convinced that the

selective employ of the proposed algorithms does not significantly

impact the energy efficiency of the entire system.

.

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