Implementation on Data Security Approach in Dynamic Multi Hop Communication

(IJCSIS) International Journal of Computer Science and Information Security,
Vol. 16, No. 1, January 2018
Implementation On Data Security Approach In
Dynamic Multi Hop Communication
Dr. S. A. Ubale
Zeal college of Engineering and
research
Narhe 41
Pune, India
swapnaja.b.more@gmail.com
Anuradha V. Khare
Zeal college of Engineering and
research
Narhe 41
Pune, India
anuradhakhare53@gmail.com
Dr. Sulbha S. Apte
Walchand Institute of Technology
Solapur 06
Solapur, India
Abstract— In remote sensor arrange messages are
exchanged between the different source and goal matches
agreeably such way that multi-jump parcel transmission is
utilized. These information bundles are exchanged from the
middle of the road hub to sink hub by sending a parcel to goal
hubs. Where each hub overhears transmission close neighbor
hub. To dodge this we propose novel approach with proficient
steering convention i.e. most brief way directing and conveyed
hub steering calculation. Proposed work additionally
concentrates on Automatic Repeat Request and Deterministic
Network coding. We spread this work by the end to end message
encoding instrument. To upgrade hub security match shrewd key
era is utilized, in which combined conveying hub is allocated with
combine key to making secure correspondence. End to end. We
dissect both single and numerous hubs and look at
basic ARQ and deterministic system coding as strategies for
transmission.
Keywords: SINR, Mesh Network, Sensor Deployment.
I. INTRODUCTION
In multi-jump remote system parcel transmission by
safeguarding the privacy of transitional hubs, with the goal
that information sent to a hub is not shared by some other hub.
Additionally, in which secrecy is a bit much, it might be not
secure to consider that hubs will dependably remain
uncompromised. In remote system hubs, information
secret can be seen as a security to stay away from a traded off
hub from getting to data from other uncompromised hubs. In a
multi-bounce organize, as information parcels are exchanged,
middle of the road hubs gets all or part of the information
bundle through straightforward transmission of system hub by
means of multi-jump arrange mold, while exchanging
classified messages. Proposed work alludes productive
calculations for secret multiuser correspondence over multi-
bounce remote systems. The metric we use to quantify the
privacy is the shared data spillage rate to the transfer hubs, i.e.,
the equivocation rate. We require this rate to be self-
assertively little with high likelihood and force this in the asset
allotment issue by means of an extra limitation. We
consider down to earth postpone necessities for every client,
which wipes out the likelihood of encoding over
a discretionarilylong piece.
II. PROBLEM STATEMENT
Proposed system present the problem of network
utility maximization, into which confidentiality is
incorporated as an additional quality of service constraint.
Secure message transmission between the source and a
destination node with less overhead cost. Data transfer using
multi-hop with minimum overhead and secure communication
among network node. Proposed system resolve problem of
distributed scheduling. Cross-layer node allocation problem
with confidentiality in a cellular wireless network, where
users transmit information to the base station, confidentially
from the other users.
III. LITERATURE SURVEY
This system proposed private and public channels
to minimize the use of the (more expensive) private channel in
terms of the required level of security. This work considers
both single and multiple users and compares simple ARQ and
deterministic network coding as methods of transmission
[1].This paper design secure communications of one source-
destination pair with the help of multiple cooperating
intermediate nodes in the presence of one or more
eavesdroppers. Three Cooperative schemes are considered:
decode-and-forward (DF), amplify-and-forward (AF), and
cooperative jamming (CJ). For these schemes, the
relays transmit a weighted version of a re-encoded noise-free
message signal (for DF), a received noisy source signal (for
AF), or a common jamming signal (for CJ)[2].This paper
considers secure network coding with nonuniform or restricted
wiretap sets, for example, networks with unequal link
capacities where a wiretapper can wiretap any subset
of links, or networks where only a subset of links can
be wiretapped [3].The scheme does not require eavesdropper
CSI (only the statistical knowledge is assumed) and the secure
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throughput per node increases as we add more legitimate users
to the network in this setting. Finally, the effect of
eavesdropper collusion on the performance of the proposed
schemes is characterized [4].We characterize the secrecy
capacity in terms of generalized eigenvalues when the sender
and eavesdropper have multiple antennas, the intended
receiver has a single antenna, and the channel matrices are
fixed and known to all the terminals and show that a
beamforming strategy is capacity-achieving. In addition, we
study a masked beam forming the scheme that radiates
power isotropically in all directions and shows that it attains
near-optimal performance in the high SNR regime [5].
IV. SYSTEM ARCHITECTURE
In existing hop to hop communication in wireless
sensor network considered to succumb to the vulnerability of
data transmission. Due to hop by hop communication
increased cost for packet transmission, the existing system
uses security mechanism as a node to node authentication
among network resources. Hop to hop identity of intermediate
node compromise security threats. To avoid security threat
they use digital signature authentication at node level for
communication or packet transmission. In the existing system,
message transmission is done through all neighbors between
the source and destination nodes, which result in overhearing
and increase overhead between nodes. Also, it leads to
compromised node communication in wireless sensor
communication.
Figure. 1. Proposed System ( Architecture ) and Working.
Proposed system implements an optimal dynamic
policy for the case in which the number of blocks across
which secrecy encoding is performed is asymptotically large.
Next, to that, This work propagate encoding between a finite
number of data packets, which removes the possibility
of achieving perfect secrecy. In this case, proposed work
design a dynamic policy to select the encoding rates for every
data packet, based on the instantaneous channel state
information, queue states and secrecy humiliation
requirements. By numerical analysis, we observe that the
proposed scheme approaches the optimal rates asymptotically
with increasing block size.
Finally, we address the consequences of practical
implementation issues such as infrequent queue updates and
de-centralized scheduling. Existing work present the
efficiency of our policies by numerical studies under various
network conditions. Next to this work proposed
system contribute to deterministic network coding Automation
of repeat packet request mechanism to actively transfer data
packet. This help to network costs and other
system parameters were just designed as constants in our work
the network costs are related to physical layer parameters such
as channel encoding parameters and transmission power. Here
proposed system design in the way, which formulate problem
by adding noise to original message or request at a destination.
The proposed system also
formulate problem ARQ case in which automatic
repeat request is sent between numbers of the time slot during
packet sending. Where packets are generally transferred
via the private channel and public channel from source to
destination. These packets are generally geometrically
distributed among network nodes.
V. ALGORITHM DETAILS
A. Generate an RSA key pair
Input : Required modulus bit length, k.
Output : An RSA key pair ((N,e), d) where N is the modulus,
the product of two primes (N=pq) not exceeding k bits in
length; e is the public exponent, a number less than and
coprime to (p-1)(q-1); and d is the private exponent such that
ed ≡ 1 (mod (p-1)(q-1)).
Select a value of e from { 3, 5, 17, 257, 65537 }
repeat
p ← genffiprime(k/2)
until (p mod e) ≠ 1
repeat
q ← genffiprime(k - k/2)
until (q mod e) ≠ 1
N ← pq
L ← (p-1)(q-1)
d ← modffiinv(e, L)
Return (N, e, d)
The system has classified into the different sets like below
Sys={inp, process, out, analysis}
Inp= {D1,D2……Dn}
That is the set of input data chunks
EncData 
m
n
DnEncDEnc
1
)()...( -------------- (1)
Equation (1) shows the data aggregation as well as data
encryption process.
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Data=∑ D[i] ----- (2)
Equation (2) shows the get the data from each node
PlainData 
m
n
DnDecDDec
1
)()...( ----- (3)
Equation (3) shows the data aggregation of cipher data on
receiver phase with decryption process.
B. Construction of updated BTC
Input: Initial source node sn, Destination node dn, Group of
neighbor nodes nd [], each node id, each node energy eng.
Output: Source to destination path when data received
success.
Step 1: User first selects the sn and dn
Step 2: choose the packet or file f for data transmission.
Step 3: if(f!=null) fd<= f
Step 4: read each byte b form fd when reach null
Step 5: send data; initialize cf1, cf2, pf1, pf2.
Step 6: while (nd[i] when reach NULL)
Cf1=nd[i].eng
Pf1= nd[i].id
Cf2=nd[i+1].eng
Pf2= nd[i+1].id
Step 7: if (cf1>cf2)
Cf2=null
Pf2=null
Else
Pf1=pf2
Cf1=cf2;
Pf2=null
Cf2=null
Step 8: end while
Step 9: repeat up to when reach at sink node.
VI. EXPERIMENTAL SETUP
We run our experiments in NS2 simulator version
2.35 that has shown to produce realistic results. NS simulator
runs TCL code, but here use both TCL and C++ code for
header input. In our simulations, we use Infrastructure based
network environment for communication. For providing
access to the wireless network at any time used for the
network selection.
WMN simulate in NS2.TCL file shows the
simulation of all over architecture which proposed. For
run.TCL use EvalVid Framework framework in NS2 simulator
it also helps to store running connection information message
using connection pattern file us1. NS2 trace file .tr can help to
analyze results. It supports filtering, processing and displaying
vector and scalar data. The results directory in the project
folder contains us.tr file which is the files that store the
performance results of the simulation. Based on us.tr file using
the xgraph tool we execute graph of result parameters with
respect to x and y-axis parameters. Graphs files are of .awk
extensions and are executable in the x-graph tool to plot the
graph.
A. Types of simulation
Parameter Value
Simulator Ns-allinone-2.35
Simulation Time 40sec
Channel Type Wireless Channel
Propogation Model Propogation Two Ray Ground
Medium Phy/Wireless Phy
Standard Mac/802 11
Logical Link Layer LL
Antenna Antenne/Omni Antenna
X dimension of the
topography
1500
Y dimension of the
topography
1000
Max Packet in ifq 1000
Adhoc Routing AODV
Routing DSR
Traffic cbr
Table 1. Behaviour of parameters versus Simulation time for
Different Nodes .
These Parameters are defined and evaluated below:
B. Average End-to-End Delay
End-to-End Delay (E2ED) refers to time occupied by
a data packet travel from a source to a destination in a
network. Here only data that reaches successfully to the
destination are considered. The minimum value
of E2ED means the good performance of the protocol. The
smallest amount value of end-to-end delay states superior
performance of the protocol.
C. Packet Delivery Ratio
The packet delivery ratio (PDR) defined as a ratio of
numbers of data packets reached to target over the network
to a number of packets generated. The greater amount value of
packet delivery ratios states superior performance of the
protocol.
D. Throughput
Throughput can be defined as the ratio of the total
bytes in data packets received by sink nodes to time from first
packets generated at a source to the last packet received by
sink nodes. The greater value of throughput states superior
performance of the protocol.
E. Energy Cosumption
Energy consumption is most important concepts in WSN. The
lifetime of the sensor network is based on energy consumption
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of the sensor node. Total energy consumption of the node
defined as the difference between initial energy
and final energy of the node. The smallest amount value of
energy consumption states superior performance of the
protocol.
F. For 100no of Nodes
1) Delay versus Smulation Time
The end-to-end delay in SINGLE HOP, DUAL HOP
and DDT with an increase in Simulation time. However,
increasing treads in DUAL HOP and SINGLE HOP is much
higher than Proposed as shown in Table 2. The smallest
amount value of end-to-end delay states superior performance
of the protocol. Figure 2 shows, the proposed system gives
superior performance than other three protocols.
Delay
Simulation
Time
Multi Hop
Proposed
Single Hop Dual Hop Distributed
Data
Transmission
( DDT )
0.15 0.00562 0.00752 0.00622 0.00803
0.20 0.00578 0.00782 0.00653 0.00901
Table 2. Delay of 100 Nodes.
Fig. 2. Delay versus Simulation Time.
2) Packet Delivery Ratio versus Simulation Time
The packet delivery ratio of SINGLE HOP, DUAL
HOP, and DDT than proposed system decreases with increase
in Simulation Time as shown in Table, However, decreasing
treads in SINGLE HOP and DUAL HOP is much
smaller than proposed approach. The greater amount value of
packet delivery ratios states superior performance of the
protocol as shown in Fig 3.
PDR
Simulation
Time
Multi Hop
Proposed
Data
Transmission
( DDT )
0.15 95.20 90.20 92.45 95.10
0.20 95.15 90.40 91.30 96.03
Table 3. PDR of 100 Nodes.
Fig. 3. PDR versus Simulation Time.
3) Throughput versus Simulation time
Figure 4 shows the throughput under different
networks scale in DUAL HOP, SINGLE HOP, DDT and
Multi-Hop. The throughput in proposed, SINGLE HOP, DDT
and DUAL HOP increases with increase in Simulation Time.
The greater value of throughput states superior performance of
the protocol as shown in Table 4.
Throughput
Simulation
Time
Multi Hop
Proposed
Data
Transmission
( DDT )
0.15 196.20 189.20 183.45 179.10
0.20 194.15 188.40 184.30 181.03
Table 4. Throughput of 100 Nodes.
Fig. 4. Throughput versus Simulation Time.
4) Energy versus Simulation time
The energy consumption of DUAL HOP , SINGLE
HOP , DDT and Hybrid DUAL HOP decreases with increase
in Simulation Time . However, decreasing treads in DUAL
HOP and Proposed approach is much higher than SINGLE
HOP , DDT as shown in Table 5. The smallest amount value
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of energy consumption states superior performance of the
protocol as shown in Fig 5.
Energy
Simulation
Time
Multi Hop
Proposed
Data
Transmission
( DDT )
0.15 755 1120 1320 1760
0.20 956 1293.40 1570 1985
Table 5. Energy required for simulation of 100 Nodes.
Fig. 5. Energy versus Simulation Time.
5) Accuracy of System
In order to evaluate the performance of system
performed. The network architecture considered is the
following:
 A fixed base station (sink node) is located away from
the sensor field.
 The sensor nodes are energy constrained with
homogeneous initial energy allocation.
 Each sensor node senses the surroundings at a fixed
rate and at all times its data to send to the base
Station (data are sent if an event occurs).
 The sensor nodes are assumed to be stationary.
However, the protocol can also support.
We compare the proposed system results with different
existing system. Below table shows the comparison analysis of
proposed system with some existing system
Fig. 6. System comparison proposed vs existing ( miliseconds ) .
We consider energy evaluation for transmission which will
conserve the node energy at the time of transmission, the
system will select efficient path for communication with
neighbor node at same time remaining network will sleep
node.
VII. CONCLUSION
Secure and effective way reproduction for parcel
misfortunes and in addition directing progression. At the hub
side, Pathfinder is an instrument which has a connection
between's an arrangement of bundle ways and productively
packs the way data utilizing way distinction. At the sink side,
Pathfinder deduces parcel ways from the compacted data and
utilizes astute way theory to reproduce the bundle ways with
high remaking proportion.
Straightforward Automatic Repeat Request (ARQ), and
Deterministic Network Coding (DNC), where in each vacancy
the source shapes M directly autonomous deterministic blends
of the M parcels and afterward utilize basic ARQ to transmit
each straight mix dependably to the goal. We expect for this
situation that the collector does not make an induction from
the got straight blends but rather either disentangles the
transmitted bundles or not.
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