1. PERFORMANCE EVALUATION OF SECURE
DATA TRANSMISSION IN WIRELESS
SENSOR NETWORK USING IEEE 802.11X
STANDARDS
Presented by:
Sunny Sall
Department of Information
Technology
Under Guidance
Dr. Rajesh Bansode
(H.O.D)
Department of Information
Technology
Registration No. & Date: 18/18-12-2019
2. Presentation Outline
I. Introduction
II. Motivation
III. Proposed Methodology
IV. Research Objectives
V. Scope
VI. Problem Statement
VII. General outline of Hypothesis
VIII. Literature Survey
IX. Problem Definition( from
Research Gaps and Findings)
X. Tools and Dataset Required
XI. Expected Outcomes
XII. Discussion on Published
Results
XIII. Timeline for Research work
XIV. Conclusion
XV. Publications related to work
References
3. I. Introduction
• The evolution of Wireless
Communication techniques from
1G to 4G, showing the data rate
against mobility/ coverage.
• It shows unlicensed/ licensed,
Circuit/ packet switched, spectral
efficiency, Wi-Fi, Blue tooth, Wi-
Max.
• The inference from Figure 1,
indicates that the Mobility in
terms of outdoor, indoor can be
observed through 4G and beyond
heterogeneous Networks (5G).
Figure 1: Evolution of Wireless Technology
A Survey of 5G Network: Architecture and Emerging Technologies by Akhil Gupta in IEEE Access vol. 3, August 2015
4. II. Motivation
• In Figure 2, it is observed
that in the year 2020 the
graph has reached up to 21
billion Mobile to Mobile
Connections.
• And by 2022 this is
expected to reach
approximately 26 billion
and that is the motivation.
Figure 2: Number of Machine to Machine Connection in
Mobile
A Survey of 5G Network: Architecture and Emerging Technologies by Akhil Gupta in IEEE Access vol. 3, August 2015
5. III. Proposed Methodology
• Figure 3, presents an example of
Cluster Based Data Aggregation [6].
• In Cluster Based Data Aggregation,
sensor nodes are subdivided into
clusters.
• Cluster heads can communicate with
the sink directly via long range radio
transmission.
• Thus, cluster heads usually form a
tree structure to transmit aggregated
data by multi hopping through other
cluster heads which results in
significant energy savings.
Figure 3: Cluster Based Data Aggregation
6. IV. Research Objectives
• The work is to be carried out with following objectives as mentioned
below.
a) To enhance the network lifetime in Wireless Sensor Network (WSN).
PHASE III
b) To design and develop an approach for Cluster Head (CH). PHASE I
DEC 2019 Completed Implementation and published.
c) Design and develop a suitable data aggregation technique when data
transmission. PHASE II JUN 2020 Implementation in process.
d) To design Broadcast Tree Construction (BTC) for energy conservation
protocol during data transmission. PHASE III
e) To develop secure HMAC technique for authentication. PHASE IV
f) To validate the proposed system performance evaluation. PHASE IV
7. V. Scope
• Data aggregation is done using priority of packet type like
normal, high, low etc.
• The data transmission packet size is 512 kbps using CBR, TCP
and FTP traffic.
• The system analysis is done using packet throughput 620 bps,
communication cost 750 bps, transmission energy 60 Joules,
receiving energy 42 Joules based on given parameters.
• The proposed protocols effectiveness has measure with various
energy consumption and conservation protocols, like AODV,
DSDV, DSR etc.
• Each node we set random energy between (100-3000 Joules)
and each node having 500 m circular radius.
8. • Based on Protocols, designer can decide their best
optimized Secure WLAN infrastructure.
• Here, one can analyse the effectiveness of such solution,
based on measurement of network life time and energy
consumption implementation.
• Evaluating the performance of Data Transmission in WSN
for various 802.11x standards, would be a foreseeable
extension to this work.
• There are several areas of potential future work in this area
that could be explored.
V. Scope
9. VI. Problem Statement
• The research gaps addressed from literature survey table
resulting into design and develop a system for energy
conservation protocol in Wireless Sensor Network (WSN).
This is to eliminate the network data overhead using data
aggregation mechanism. The authentication system generally
deals with Hash Mandatory Access Control (HMAC)
protocol to prevent the various network attacks.
10. VII. General Outline of Hypothesis
• Design and Development of a system for energy conservation protocol in
Wireless Sensor Network (WSN), with eliminating the network data
overhead using data aggregation technique.
• To provide defence mechanism from various network attacks in untrusted
network environment.
• How to select Cluster Head?
• How to Enhance Security?
• How to minimise Energy Consumption?
• How to improve Network Life Time?
• How to perform Data Aggregation?
• How to minimise Data loss and Data leakage?
• How to minimise Network Overheads?
11. VIII. Literature Survey
Ref. No. Authors and Title Method Used Key Findings Research Gaps
[1] Firoj Ahamad and Rakesh Kumar
Energy Efficient Region Based
Clustering Algorithm for WSN using
Fuzzy Logic
Provides an approach to prolong
the WSN lifetime using fuzzy logic
based selection of cluster head that
provides completely non
probabilistic approach.
Use multi hop for data
transmission which
eliminates packets loss
issues
Every round CH selection
consumes higher energy
that generate lifetime loss
issues
Low data transmission
rates.
High computation when
data size is large
[2] I.S. AKILA AND R. VENKATESAN
A Fuzzy Based Energy-aware Clustering
Architecture for Cooperative
Communication in WSN
Cluster Head (CH) is chosen based
on the parameters residual energy,
using Partial Swarm Optimization
(PSO) trust, signal-to-interference-
plus-noise ratio and load.
Proposed technique
Enhances the network
lifetime and energy
efficiency.
[3] Wael Y. Alghamdi, Hui Wu, Salil S.
Kanhere
Reliable and Secure End-to-End Data
Aggregation Using Secret Sharing in
WSNs
Reliable and Secure End-to-End
Data Aggregation Using Secret
Sharing in WSNs
Data aggregation eliminates
the network overhead
12. Ref. No. Authors and Title Method Used Key Findings Research Gaps
[4] OZDEMIR et. Al.
Energy Efficient & Secured
Data Routing Through
Aggregation Node in WSN
Detect the attack on all nodes including cluster
member, cluster head and aggregator node as
well as checks data truthfulness on cluster
head when data is received from all cluster
members. SHA1 algorithm is used for
integrity checking
improves the energy
utilization, memory
management
and security of data along
with attack detection on CH.
It can’t recover the
compromised node and use
it again in the
Network instead of leaving
it.
Time complexity higher
than traditional LEACH
System does not reflect how
better for time complexity
that traditional approaches.
[5] Basavaraj G. N, Dr. Jaidhar
C.D
H-LEACH Protocol with
Modified Cluster Head
selection for WSN
A new threshold condition
T (n) for electing Cluster Heads (CHs) among
the Sensor Nodes (SNs).
Provides balancing or
efficient energy
management
[6] T M Behera, S K Mohapatra,
Proshikshya Mukherjee, H K
Sahoo
Work-In-Progress: DEEC-
VD: A Hybrid Energy
Utilization Cluster-based
Routing Protocol for WSN for
application in IoT
DEEC-VD not only uses cluster and active
cluster head forming with the help of vector
quantization but also it uses Dijkstra
Algorithm to find the shortest path between
the active cluster heads (CHs) to provide high
energy utilization.
Improves the average
energy
Utilization of the network
has increased to almost
60%.
VIII. Literature Survey
13. Ref. No. Authors and Title Method Used Key Findings Research Gaps
[7] Dhiviya.S, Sariga A Dr. P. Sujata
SURVEY ON WSN USING
CLUSTERING
The survey on a distinct clustering
algorithm for WSN which is classified
based on distinct clustering attributes
Describes the strategy of
clustering to eliminate data
leakage
Not implemented in real
time environment
Data reduction issues has
generated
Generate high time
complexity for encryption
and decryption.
[8] Abhay Gupta, Narendra Shekokar
A Novel K-Means L-Layer
Algorithm for uneven Clustering
in WSN
A modification of the K Means
algorithm which provides even
clustering as well as the study of
energy consumption of the nodes with
regards to the data packet optimization.
This system provides energy
consumption of the nodes with
regards to the data packet
optimization.
[9] K. Hamsha and Nagaraja G.S
Analysis of Security Mechanism
Using Threshold Cryptography
for Hierarchical Wireless Sensor
Networks
The Sink node shares the secret group
key to the entire sensor node in the
network. Threshold cryptography
protects the shared key by malicious or
intruder node in the network.
Threshold cryptography has
used for data encryption
VIII. Literature Survey
14. Ref. No. Authors and Title Method Used Key Findings Research Gaps
[10] Yasha Istwal, Shashi Kant Verma
DUAL CLUSTER HEAD
ROUTING PROTOCOL IN
WSN
DCHRP (Dual Cluster Head Routing
Protocol) having dual cluster head with
three level of heterogeneity to improve
the life span of a Wireless Sensor
Network (WSN).
Proposed routing approach
provides dual CH for routing.
Dual CH creation takes high
computation
This protocol takes link
reliability into account when
forming clusters.
Evolutionary optimization
algorithm has used which
increased the delay.
[11] Wang Jin, Wang Bin
Adaptive clustering approach
over unreliable links for WSN
Design an energy-efficient cluster
forming protocol for WSN based on
relative difference between energy level
of an ordinary node and its cluster head
node in the previous round.
System unreliable links can
prolong network lifetime when
compared with other energy-
efficient clustering protocol for
WSN.
[12] Jingyi Wang ,Yuhao Jing,
Xiaotong Zhang , Hongying Bai
Clustering Protocol based on
Immune Optimization Algorithms
for Wireless Sensor Networks
Immune Optimization Algorithms to
reduce the total transmission distance of
the whole network by choosing the
appropriate nodes as cluster heads in
WSN.
CH selection base optimization
technique which reduces time.
VIII. Literature Survey
15. Ref. No. Authors and Title Method Used Key Findings Research Gaps
[13] Mukesh Mishra, Gourab sen
Gupta, Xiang Gui
A review of and a proposal for
cross-layer design for efficient
routing and secure data
aggregation over WSN
A review of and a proposal for cross-
layer design for efficient routing and
secure data aggregation over WSN
Secure data aggregation which
improves the data security.
Less security during data
transmission.
No attack detection
mechanism has used.
Only DOS based attack has
detected not others.
[14] Priyanka Nehra, A. Nagaraju
Fault Tolerance using Quadratic-
Minimum Spanning Tree (Q-
MST) with Secure Data
Aggregation in Wireless Sensor
Networks
Transmission of data along with the
integration of two-hop mechanism
which is Secure and Efficient protocol
for Data Aggregation in wireless sensor
Networks (SEDAN) is used.
MST algorithm provides
execution in minimum time
execution
[15] P.Padmaja
Dr. G. V. Marutheswar
DETECTION OF MILICIOUS
NODE IN WIRELESS SENSOR
NETWORK
Optimization Wireless Sensor Network
(WSN) is necessary to reduce
redundancy and energy consumption.
Eliminates the energy
consumption.
VIII. Literature Survey
16. Ref. No. Authors and Title Method Used Key Findings Research Gaps
[16] Madiha Razzaq, Devarani Devi
Ningombam, Seokjoo Shin
Energy Efficient K-means
Clustering-based Routing
Protocol for WSN Using Optimal
Packet Size
An energy efficient K-means clustering-
based routing protocol and considers an
optimal fixed packet size according to the
radio parameters and channel conditions of
the transceiver.
Clustering techniques has
used to eliminate high
packet overhead.
Time complexity issues.
Reduce throughput and
packet loss ratio.
Generate congestion when
large data.
[17] J. S. Saji Kumar,Elizabeth Sherly,
A New Hybrid Algorithm for
Tolerating Security Threats in
Wireless Sensor Networks
The proposed model of MRM, H-PAL-
PLR, and HOL-5-DAS has been proved to
be efficient in case of link or node failure,
packet loss and latency respectively.
High packet delivery ratio,
network
life time, throughput,
latency ratio and packet
loss ratio
Parameters
[18] Marwa Sharawi, Eid Emary
Impact of Grey Wolf
Optimization on WSN Cluster
Formation and Lifetime
Expansion
The introduced system outperforms the
LEACH in almost all topologies using the
different indicators.
Fast approach for cluster
generation in large network
VIII. Literature Survey
17. Ref. No. Authors and Title Method Used Key Findings Research Gaps
[19] Limin Shen, Jianfeng Ma,
Ximeng Liu, Fushan Wei and
Meixia Miao
A Secure and Efficient ID-Based
Aggregate Signature Scheme for
Wireless Sensor Networks
The security of our identity-based aggregate
signature scheme is rigorously presented
based on the computational Diffie-Hellman
assumption in random oracle model.
ID based signature
eliminate certificate
verification as long process.
Third party resource
required for ID signature
generation
Overhead generate during
data transmission.
Collusion attack has
generates from various
attacks.
[20] Ravi Teja, Dr. S. Indu
A Priority Based WSN Clustering
of Multiple Sinl( Scenario using
Artificial Bee Colony Algorithm
An energy efficient as well as a priority based
wireless sensor network clustering and routing
algorithm for a multiple sink scenario using
Artificial Bee Colony Optimization with a
multi objective fitness function which takes
into account the priority of each sink.
ABCA has used for
efficient clustering.
[21] Scott A. Thompson Jr. and
Bharath K. Samanthula
Optimized Secure Data
Aggregation in Wireless Sensor
Networks
A novel solution for the secure aggregation of
data in WSNs based on probabilistic
homomorphic encryption. By combining with
a unique encoding function, proposed solution
guarantees the privacy of sensor data, while
also greatly reducing communication costs.
Two way encoding has used
which provide highest
security.
VIII. Literature Survey
18. IX. Problem Definition (Derived from Research
Gaps & Findings)
• Large data transmission should generate network overhead
during data transmission and it produces data leakage issues.
• Trust calculation of individual node in next hop selection is
not considered in excising systems.
• No backup path provided in existing WSN when internal or
external attack is generated.
• Many nodes are destroyed when high power is consumed by
internal nodes, it create a cut in network thus data is loosed
which can’t be recovered by systems.
19. X. Tools and Data set Required
• Software:
• Ubuntu
• VM Ware
• NS2
• Hardware:
• PC with Minimum Configuration
20. XI. Expected Outcomes
• Energy consumption and energy modelling are important issues in designing and
implementing of Wireless Sensor Networks (WSNs), which help the designers to
optimize the energy consumption in WSN nodes. Good knowledge of the sources of
energy consumption in WSNs is the first step to reduce energy consumption [19].
a) To enhance the network lifetime in WSN using cluster network and reduce data
transmission time as well as enhance the QoS. PHASE III
b) To design and develop an approach for cluster head (CH) selection using evolutionary
based Genetic Algorithm (GA). PHASE I DEC 2019 Completed and published
c) Design and develop a suitable data aggregation technique when data transmission
using MAC protocol. PHASE II JUN 2020
d) To design Broadcast Tree Construction (BTC) based sleep scheduling approach for
energy conservation protocol during data transmission. PHASE III
e) To develop secure HMAC technique for authentication with secure manner. PHASE
IV
f) To validate the proposed system performance evaluation with traditional existing
approaches. PHASE IV
22. XII. Discussion on Published Results
• Default cluster generation Cluster head generation
23. XII. Discussion on Published Results
• CH moves to central location Communication between sensor
node and CH
24. • This figure 4, will provide the drop rate overall simulation during the
communication with other protocols.
• This figure 5, will provide the throughput of system during the
communication with other protocols.
• This figure 6, will provide the how system will increased the actual
time percentage of simulation due to proposed energy conservation
protocol.
• There is a decrease in drop rate by 2%, the throughput has
increased by 3%. Also Network Lifetime has increased to 8 seconds
as compared to 2 seconds in other systems.
XII. Discussion on Published Results
Figure 4: Drop rate of proposed vs existing Figure 5: Throughput of proposed vs existing
Figure 6: Network lifetime of proposed vs existing
25. XII. Discussion on Published Results
Parameter Values
Simulator NS-allinone 2.35
Simulation time 25 sec
Channel Type Wireless Channel
Propagation Model Two Ray Ground
Standard MAC/802.11
Simulation Size 1000 *1500
Max packet Length 1000
Ad hoc routing AODV
Traffic CBR
Parameters WSN [21] Proposed (cluster base with
AODV)
Data Aggregation No Yes
Data Security Yes (selective) Yes
Energy Conservation No Yes
Packet Loss High Low
End to End delay High Low
Packet Overhead High Low
Table 1: Simulation Parameters used
Table 2: Difference between the Proposed and existing WSN
26. XII. Discussion on Published Results
Most of existing system having high packet drop rate due to
heavy network overhead.
Various security approaches not able to provides drastic security
during data transmission.
Cut generation is another problem in existing systems. (it is the
concept in which any internal node automatically gets destroyed
during data transmission due to energy).
Need to propose an lightweight data transmission with secure
approach in large scale WSN.
27. XIII. Timeline for Research work
To design and develop an approach for cluster head (CH) selection using evolutionary
based Genetic Algorithm (GA). PHASE I DEC 2019 Completed and published
Design and develop a suitable data aggregation technique when data transmission using
MAC protocol. PHASE II JUN 2020
To enhance the network lifetime in WSN using cluster network and reduce data
transmission time as well as enhance the QoS. PHASE III A SEPT 2020
To design Broadcast Tree Construction (BTC) based sleep scheduling approach for
energy conservation protocol during data transmission. PHASE III B DEC 2020
To develop secure HMAC technique for authentication with secure manner. PHASE IV
A MAR 2021
To validate the proposed system performance evaluation with traditional existing
approaches. PHASE IV B JUN 2021
28. XIV. Conclusion
• We have proposed a HMAC and data aggregation in WSN. Initially the
CHs are chosen based on the node connectivity, which acts as a Data
Aggregator. Then, the clustering process is executed using the genetic
algorithm. This technique highly minimizes energy consumption and
thereby enhancing the network lifetime [20].
• When the cluster member wants to transmit data to the aggregator, a data
encryption techniques are utilized. The data security module utilized offers
confidentiality to the data packets, thus ensuring the authenticity and
integrity of the sensed data.
• Simulation results, shows that the proposed technique minimizes the
energy consumption, ensures data security and reduces the transmission
overhead [21].
29. XV. Publication related to work
• A Paper submitted and presented in IC-ICN Multicon- W 2020
conference in February 2020 at TCET.
• Also submitted in Springer through IC-ICN Multicon- W 2020
• Status: accepted in Springer
• Title: “Secure Data Aggregation and data Transmission using HMAC
Protocol in Cluster base Wireless Sensor Network”
30. Courses Completed
• Completed course on “Wireless Communication Emerging Technologies”,
offered by Yonsei University through Coursera on 15 June 2018.
• Attended the PMMMNMTT Sponsered One Week FDP on “Cyber Security”
at Atharva College of Enginnering from 3 to 8 Sept. 2019.
• Attended the Webinar on “IoT for Music Theropy, Research Paper Writing,
Gateway to Cyber Security” at St. John College of Enginnering from 24 to 28
May 2020.
• Attended the Webinar on “Usage of Technology in COVID 19” at Terna
College of Enginnering from 28 May to 2 June 2020.
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