Efficient Secure Multi-Neuron Attack Defensive and Routing Security Technique in Wireless Mesh Network

International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 04 Issue: 09 | Sep -2017 www.irjet.net p-ISSN: 2395-0072
© 2017, IRJET | Impact Factor value: 5.181 | ISO 9001:2008 Certified Journal | Page 1309
Efficient Secure Multi-Neuron Attack Defensive and Routing Security
Technique in Wireless Mesh Network
Gagandeep Singh1, Ms. Maninder Kaur2
1M.tech Student, Doaba institute of engineering & technology, Ghataur,Punjab , India
2HOD ( M.tech), Doaba institute of engineering & technology, Ghataur,Punjab , India
---------------------------------------------------------------------***---------------------------------------------------------------------
Abstract - Mesh wireless network is an advanced
developing technology that will modify the world more
efficiently or effectively. It is regarded as a highlycapablefield
being adding significant in mobile wireless networks of the
future group. Low-altitude Unmanned Aerial Vehicles
combined with WLAN Mesh Networks have facilitated the
emergence of airborne network-assisted applications. In
misadventure release, they are key solutions:
(i) On-demur ubiquitous network access or
(ii) Efficient investigation of sized areas.
However, these solutions still face major security experiments
as WMNs are disposed to routing attacks. Thus, the network
can be sabotaged, or the attacker might manipulate payload
data or even attack the UAVs. Contemporary security
standards, such as the IEEE 802.11iortheretreatmechanisms
of IEEE 802.11s mesh typical, are susceptible to routing
attacks as we experimentally showed in previous works.
Therefore, a secure routing protocol is essential for making
feasible the deployment of UAV-WMN. As future as identified,
no one of the present investigation methods have increased
receipt in practice owed to their high above or strong
expectations. Here, has been presented the encryption
technique for Secure, or Efficient mesh Routing approach. In
this thesis, the optimization method used for reduce the worm
hole attack effects has been described.
This paper discusses dissimilar encryption or Neural Network
technique to establish algorithm which considers packet
delivery. The existing PASER routing protocols are compared
using new approach or the conception of the secure technique
that is implemented in NN and DES with Mesh wireless
network based on encryption technique. Our proposal
prevents clone attack than the IEEE 802.11s/i security
mechanisms or the well-known, secure NN without making
restrictive assumptions.
Key Words: Packet Delivery Rate, End to End Delay,
Throughput, DES, PASER, NN, Clone Attack.
1. INTRODUCTION
A network is a cluster connected with 3 or many notebook
systems that are paired alongside to talk collectively. The
particular contacts between nodes are established
mistreatment often were advertising or Wi-Fi advertising.
Completely different systems discuss assets available in the
community. These kinds of nodes will adapt to the owners
just like PC, cell phones, hosting space moreover while
network component.
1.1 Wireless Mesh Network
Wireless mesh system created down the assembly of
wireless admittance facts connected at every system
consumer’s locale. Each system user is also a worker,
forwarding data for following knob. The stemming
arrangement is rationalized or simplified for every knob
essential only transfer as far as the nextknob. Wirelessmesh
stemming could allow peoplelivingindistantzonesorminor
industries working with pastoral districtstojointhesystems
collected for reasonable Internet networks.
Mesh System mesh system is a system topology in which
every knob relays data for the system. All mesh knobs co-
operate in the portion of data in the system. Mesh systems
can communicate post using either a saturating method or a
routing technique .With routing, the message is broadcast
along a path by hopping from knob to knob until it reaches
its endpoint. To ensure all its paths’ accessibility, the system
must allow for permanent associates or must re-configure
itself approximately broken paths, using self-healing
procedures such as Straight Path Bridging. Self-healing
permits a routing-based system to operate when knobs
break-down or when a connection becomes unreliable.
Fig -1 Wireless Mesh Network

A consequence, the system is naturallyquitedependable,
as there is regularly other than single track amongst a
foundation or an endpoint in the system. Although mostly
used in a wireless situation, this concept can also apply to
wired systems or to software interaction. A mesh system
whose handles are all attached to each other is a fully
connected system. Fully connectedrestlesssystemshave the
compensation of security or reliability: troubles in a cable
affect only the two knobs attached to it. However, in suchset
of connections, the number of cables, or therefore the cost,
goes up quickly as the number of knobs increases.
1.1.1 External Attack in Wireless Mesh Network
They are individuals which are launched by
intruders who are not part of a WMN or try to gain
illegitimate access to the system. Thus, by this they can
increase the calculation power of the system or can degrade
the performance of the system. Some attacks that are
possible in the WMN by the intruder in the system as: DDoS
(Denial of Service) attack. This attack is the main problem in
WMN as it directs the false messages in the system, thus
making the system to choke down or making the capitals
unavailable. Thus noticing the DDoS attacksinthesystemsis
still in research. Other external attack in the WMN is the
encryption or verification. Allowing tothistheverificationof
the system is complete with the access opinions, the
authentication is done by the access points is may be using
the WEP or using WPA technology; as these procedures are
found out to be co-operated by some hacking software. So
these Procedures need to be revised. Encryption is done
while distribution the data was encrypted with the shared
key. As in the system all of the packets being encryptedwith
their communal key, so there is the option of the attack by
guessing the shared key, so that the message can be forged.
1.1.2 Internal Attack in Wireless Mesh Network
Internal attack is launched by the internal knobs which
area part of the WMN, they may be the selfish knobs or the
malicious knobs that have been possibly been compromised
by the attackers. By this they have admitted to all of the key
indoor verification information. So to detect the attack
internally somemechanismsshouldbeemployedtodetector
isolate the misbehaving knobs. The example of the
mechanism is the practice of IDS.
1.2 Data Encryption Standard Algorithm
The secret key algorithm is asecurityprovidesthesimilar
key to encode and decode data. This algorithms uses a
different key for encoding and decoding, and the decoding
key can’t derived from the encoding key.
DES (Data Encryption Standard) Key Algorithm could be
separated into binary Kinds:
 Torrent ciphers and
 Chunk ciphers.
In stream cipher encodinganindividualbitofplain-textat
an interval time, whereas Block-ciphers offer at several of
bits, i.e., normally 64-bits in new ciphers and encodethem as
an individual unit .The secret key algorithm is a symmetric
key chunk cipher printed by the National Institute of
Standards and Technology.
The secret key is an operationofaFeistelCipher.Itusages
16-rounds Feistel structure. The chunk’s scope is 64-bit.
Nevertheless, key distance is64-bit,DEShasanoperativekey
length of 56 bits, since 8 of the 64 bits of the most important
are not rummage-sale by the encryption algorithm or
purpose as checkered bits lone. Universal Construction of
DES is showed in the fig no.1.2. .Meanwhile DES is based on
the Feistel Cipher all that is required to require DES is:
 Curved function
 Significant schedule
 Any other processing , Original and final version
Fig-2 Data Encryption Standard
1.3 Neural Network
The neural network is an artificial neural network based
on an error neural network algorithm. Classification is afield
of learning in whichattributesarematched.Thesealgorithms
are called machine learning algorithms. Figure 2 shows a
simple architecture of a classification system.

There are two main stages in a classification system:
 Training stage
 Testing stage
Fig -3 Neural Network
NeuralNetwork is an organically stimulatedorganization
algorithm. It consists of amount of simple neuron like
processing units, prearranged in layers. Every unit in a layer
relates to all the units in the preceding layer. These
connections are not all equal: each joining may have a
different strength or weight. The bulks on these contacts
encodethe information on a network. Frequentlytheunitsin
a neural network are also called nodes.
Data arrives at the inputs and permits through the
network, layer by layer; pending it arrives at the
productivities. Throughoutconsistentprocess,thatiswhenit
acts as a classifier, there is no comment between layers. This
is why they are identifying neural system.
2. LITERATURE SURVEY
Mohamad Sbeitietal discussed about WLAN Mesh Systems
in paper titled PASER: Secure or Efficient Routing Approach
for Airborne Mesh Networks. In this paper the author has
simplified the entrance of airborne system-assisted
applications. In adversity relief, they were a key solution for
(i) On-demand or everywhere system access and (ii) Well-
organized exploration of sized areas. However, these
solutions still feature main security challenge as WMNs are
horizontal to steering attacks. Therefore, the complex can be
disrupted, or the attacker might operate, load data or even
take over the UAVs. Existingsanctuary standards,suchasthe
IEEE 802.11i or the sanctuary mechanism of the IEEE
802.11s network typically, were susceptible to direction-
finding attacks as they experimentally show in preceding
works. Therefore, a protected routing procedure was crucial
formaking possible the placement of UAV-WMN.Asfaraswe
know, not a single personoftheexistinginvestigateapproach
had gained reception in performing due to their high-slideor
strong assumptions. Here, they near the Position-Aware,
Secure, or Efficient mesh Routing approach. The suggestion
averts more doses than the IEEE 802.11s/i safety
instruments or the well-known protected steering protocol
ARAN, without making defensive expectations.
3. PROPOSED SYSTEM
Step I. First wireless mesh network created which connects
one UAV node to another UAV node. To communicate the
information in connecting form, this network is linked
together.
Step II. In next step the source and destination node is
selected in this network. The Main Head node name is Key
Distributed Centre is plotted.
Step III. In ‘Main Head’ normal id’s and unique id’sascreated
in the wireless mesh networks to travel on position to
another position in the mesh networks.
Step IV. The unique id generates, the purpose is Main Head
communicates a secure message and send the trusted node,
which is defined by the KDC administration.
StepV. KDC administrator providesauthenticationbymeans
of the registration process. Limit decided at the 20 - 50
Unmanned Aerial Vehicles. If any other user who crosses the
limit, then message will be displayed by KDC (not authorized
Unmanned Aerial Vehicles).

Fig -4: Proposed Flow chart
Step VI. Then implemented the encryption technique to
provide the security in the mesh networks. Secret key
encryptionalgorithmisusedforencryption.Wherethesecret
key algorithm will be deployed was implementing a security
which provides the similar key to encode and decode data.
This algorithm uses a dissimilar key for encoding and
decoding, and the decoding key can’t derive from the
encoding key.
New Secret Key Algorithm could be separated into binary
types:
a) Stream-ciphers
b) Block-ciphers
In stream cipher, this is encoded a single bit of plaintext as
execute at a time, whereas Block-ciphers offers a number of
bits, i.e., normally 64-bits in new ciphers and encodethem as
an individual unit.
Step VII. The performance parameters are calculated based
on the PASER (Power Aware Secure, Efficient Routing
Protocol) with Encryption Techniques (DistanceProbability,
Throughput, packet delivery rateand frame error rate based
on delay (0%, 10% and 20%).
Step VIII. The proposed approach is implemented named as
Neural Network Algorithm. This is resolving the network
issues and transmits the data securely and calculates the
performance parameters, .e throughput, delay and delivery
rate etc.
Step IX. Comparison between the existing and proposed
approach and proved that proposed work is better than
previous one.
4. RESULTS AND DISCUSSION
In this section, the result in wireless mesh network
with neural network and compare with PASER
(position awer secure efficient routing protocol) to
reduce the delay with frame error rate and enhance the
packet delivery rate (%). In existing work using PASER
approach to achieved the delay increases and packet
delivery rate decreases.
Fig -5 Wireless mesh network
The fig-5 described that the mesh network designs
system, enter the number of unmanned air vehicles and
mesh network length and width 1000*1000 and packet

size 1000. The unmanned air vehicles (UAV) plotted in
the given area i.e. 1000*1000 and connected one UAVto
another UAV is called WMN.
MESH system with connected UAVs for the broadcast of
packets from initial node to the sink in which source or
destination is plotted in pink and crayon color or all other
knobs with their ids. It defined that the plot the start node
and destination nodein thewirelessmeshnetwork.Insource
node means continue the packet travel and destination node
means end the transmission node in the WMN.
Fig-6 Trusted Node
The fig-6 shows that the trusted node means secure data
transmission. We use authentication process to generate the
trusted node in the network. To send the information
securely.
Fig-7 Registration Complete
The fig-7 message box defines that the unmanned air
vehicles are authorizedvehicleregistrationiscompletedwith
KDC. When uav follows the authentication process then
gives the registration message.
Fig-8 Packet Transferred
The fig-8 message box defines that the packet will be
delivered or transferred from unmanned air vehicles. The
packet will be transfermeansKDCgeneratethetrustednodes
in the network and it will sent the information securely
transfer one uav to another uav.
Fig-9 Clone attacker Node
In fig-9 message box shows that the attacked UAV is 8
from the route to which attacker attacks in the system or will
deviateall the packetsfromtheroute.Thecloneattackoccurs
in the network then generates the multiple copies in the
network. In attacker node catch the information in any case
then loss the original packets in the WMNs.
Fig-10 Trusted Node
The fig-10 message box shows the attackedknobwhichis
10 in the system which is in blue color or reset knobs are the
trusted vehicles in the red color. We use authentication
process to generatethe trusted nodein the network. To send
the information securely with one node to another node.
Fig-11 Routing Delay with Paser
In fig-11 the routing delay to transmit the packets from
the start nodeto the sink node havingFER which istheframe
error rate in PASER. These are showing the delay in between
the transfer of the packets when the FER is 0%, FER is 10 %
or FER is 20%. Less delay results in the high Packet Delivery
rates.

Fig-12 Probability Density Function
The fig-12showsabovetheprobabilitydensityfunctionin
D-NN WMNs which shows the probability of receiving the
path damage when attacker attacks in the systems or the red
line shows the average probability for the designed system
function.
Fig-13 Packet Delivery Rate with Paser
In fig-13 the packet delivery rate for the successful
broadcast of packets from the start node to the sink node
through trusted vehicles which shows that 70% delivery
packets are transmitted using secure transmission.
Fig-14 Throughput with Paser
The fig-14 shows Throughput for the successful
transmission of packets from the initial node to the
destination through trusted vehicles which shows that 33%
throughput achieved in (PASER) are transmitted using
secure broadcast. Throughput is the maximum rate of
production or the maximum rate at which something can be
processed.
Fig-15 Packet Delivery Rate with NN
The fig-15 the packet delivery rate for the successful
transmission of packets from source to the destination
through trusted vehicles which shows that 98% throughput
with NN are transmitted using secure transmission. It is
the ratio of actual packet delivered to total packets sent.
Fig-16 Routing Delay with NN
In fig-16 the routing delay to transfer the packets from
the basics to the destination having FER which is edge error
rate in NN. These are showing the delay in between the
transfer of the packets whenthe FER with NNis0%, FER with
NNis10% or FER with NN is 20%. Little delay results in the
high Packet Delivery rate.
Fig-17 Throughput with NN
In fig-17 throughput for the successful transmission of
packets from source to the destination through trusted
vehicles which shows that 79% throughput with D-NN are
transmitted using secure transmission.

Table – 1: Performance Parameters
Performance Parameters Values
Delay 0% 64.63ms
Delay 10% 6.4ms
Delay 20% 12.93ms
Throughput 70%
Packet Delivery rate 98%
Table – 2: Comparison between Throughput of NN and
PASER
Time [ms] Throughput-D-NN Throughput-PASER
100 25 23
200 38 35
300 55 50
400 69 64
500 79 67
Fig-18 Comparison between throughput NN and
PASER
Table -3 represents that the comparison based on PASER
and D-NN in throughput (%).In NN there is improvement in
the accuracy of the wireless mesh network. In this method it
is observed and prevention isperformed in thenetworkwith
the help of dataant colony optimization techniqueandsecret
key algorithm.
Table - 3: Comparison between Packet delivery Rate NN
with PASER
Time [ms] Packet delivery
rate D-NN
Packet Delivery Rate
PASER
100 84 54
200 89 58
300 93 60
400 95 69
500 98 70
Fig-19 Comparison between PDR NN and PASER
The fig-19 represents that the comparison based on
PASER and D-NN in the PDR (%). We improve the packet
delivery with D-NN and PASER. We implement the proposed
approach to enhance the performance of the information
transmission.
5. CONCLUSIONS
WMNs are the efficacious technology that provides internet
access in rural areas in a cost effective way with the modus
operandi. This security becomes paramount and a critical
parameter for wireless mesh network because of its
vulnerability to various attacksand requirement ofintensive
care for impregnability and unassailability. The attacks have
been conversed about and their genre herein. Distinguished
routing protocols, and meta-heuristic algorithm schemes
could be implemented to protect the network. There are
assorted techniques which are hypothesized in this thesison
the essence of distinct parameters. Using the network
simulator MATLAB 2016a, realistic mobility patterns of
unmanned air vehicles or experimentally derived data
transfer model of unmannedair DES-NN- WMN hascompare
presentation evaluation like packet delivery rate, end to end
delay or throughput.
ACKNOWLEDGEMENT
The author is thankful to Mrs. Maninder Kaur, Office
Incharge, DIET and her staff for providing the necessary
facilities for the preparation of the paper. Without the
proper guidance of them it is not possible to learn about
latest technologies and research works
REFERENCES
[1] Sbeiti, Mohamad, et al. "PASER: Secure or Efficient
Routing Approach for Airborne Mesh Networks." IEEE
March 2016.
[2] Sen, Jaydip. "Security or privacy issues in wireless mesh
networks: A survey." Wireless networks or security.
Springer Berlin Heidelberg, 2013. 189-272.

[3] Agnihotri, Mohit, et al. "Topology Formation in Mesh
networks considering Role Suitability."
[4] Akyildiz, Ian F., Xudong Wang, or Weilin Wang.
"Wireless mesh networks: a survey." Computer
networks 47.4 (2005): 445-487.
[5] Apostolaras, Apostolos, et al. "A Mechanism for Mobile
Data Offloading to Wireless Mesh Networks."
(2016).Acharjee, Tapodhir, Pinky Borah, and Sudipta
Roy."A New Hybrid Algorithm to Eliminate Wormhole
Attack in Wireless Mesh Networks." 2015 International
Conference on Computational Intelligence and
Communication Networks (CICN).IEEE, 2015.
[6] B. Sun, Y. Guan, ,J. Chen ,U.W Pooch, ”Detecting Black
hole attack In Mobile Ad-hoc
Netwoks”.5thEuropeenPersonel Mobile
Communications Conference,2003,pp. 490-495.
[7] Branch, Joel W., et al. "In-networ k outlier detection in
wireless sensor networks." Knowledge or information
systems 34.1 (2013): 23-54.
[8] De Judicibus, Dario, et al. "Method or system forsecured
transactions over a wireless networ k." U.S. Patent No.
8,352,360. 8 Jan. 2013.
[9] Dia, Hussein. "An object-oriented neural network
approach to short-term traffic forecasting." European
Journal of Operational Research 131, no. 2 (2001): 253-
261.
[10] Singh, Rajpreet, and Sanjeev Dewra. "Performance
evaluation of star, tree & mesh optical network
topologies using optimizedRaman-EDFAHybridOptical
Amplifier." 2015 International Conference on Trendsin
Automation, Communications and Computing
Technology (I-TACT-15).Vol. 1.IEEE, 2015.
[11] Srikrishna, Devabhaktuni, or Amalavoyal Chari.
"Selection of routing paths based upon path quality of a
wireless mesh network." U.S. Patent No. 6,965,575. 15
Nov. 2005.
[12] Subhashis Banerjee ,Mousumi Sardar, or
koushikmajumder,” Black-hole attack mitigation in
manet”, springer international publishing switzerlor
2014.
[13] Kishor Jyoti Sarma,et.al,” A Survey of Black Hole Attack
Detection in Manet”, Advanced InformationNetworking
or Applications (AINA), 2014 24th IEEE International
Conference on. IEEE, 2014.
BIOGRAPHIES
Gagandeep Singh has received
B.Tech degree in Electronics and
Communication Engineering from
IET Bhaddal Ropar, Punjab
Technical University, Jalandhar,
Punjab. He is currently pursuing
M.Tech degree in Electronics and
Communication Engineering from
PTU Regional Centre Doaba
Institute of Engineering and
Technology, I.K.Gujral Punjab
Technical University, Jalandhar,
Punjab.

Efficient Secure Multi-Neuron Attack Defensive and Routing Security Technique in Wireless Mesh Network

Recommended

Recommended

More Related Content

What's hot

What's hot (19)

Similar to Efficient Secure Multi-Neuron Attack Defensive and Routing Security Technique in Wireless Mesh Network

Similar to Efficient Secure Multi-Neuron Attack Defensive and Routing Security Technique in Wireless Mesh Network (20)

More from IRJET Journal

More from IRJET Journal (20)

Recently uploaded

Recently uploaded (20)

Efficient Secure Multi-Neuron Attack Defensive and Routing Security Technique in Wireless Mesh Network