DOI 10.4010/2016.763
ISSN 2321 3361 © 2016 IJESC
Research Article
Volume 6 Issue No. 4
False-Data Injection Detector in Networked System
Pazham Nachiappan M R1, Prasanth I2, Rohan David A3, Sathish Saravanan P4
UG Scholar1, 2, 3, Assistant Professor4
Department of Information Technology
Dhanalakshmi College of Engineering, Chennai, India.
nachiappanlm@gmail.com1, www.prasanthilangovan@gmail.com2, ROHANDAVID54@gmail.com3,
psathishsaravanan@gmail.com4
Abstract:
This system is used to detect and filter the sensor’s for validation. The received information contains falsely injected data in a
cyber physical networked system. These system have received a changed attention because of the advances in sensor network
technologies and new development in cyber-physical networked systems (CPNS) .Typical CPNS cover a wide range of
applications including transportation networks, vehicular networks, networks and so on. Unlike more traditional embedded
systems, CPNS is natural and engineered physical systems, which are integrated, monitored and controlled by an intelligent
computational core. In CPNS, sensor nodes obtain the extents from the physical components, process the calculations and send
measured data to the controller through networks.
Keywords: Forward nodes and sensing nodes , CPNS , Cluster Head.
I.
INTRODUCTION
For decades, false data injection detector is being existing;
the reason it is in the existing system while data exchange is
done within the single cluster (i.e.) within a single network.
The main drawback of existing system is, all the process is
carry out only in a single cluster. Controller is available in
cluster to receive all information from other normal data
then its store the information otherwise false information
has been identified and blocked. The main problem in
existing is, all process can be performed by the controller for
this controller resource time has been wasted. On the other
side, In our proposed system, we propose a Polynomialbased Compromise- Resilient En-route Filtering scheme
(PCREF) for CPNS, which can filter false injected data
effectively. PCREF adopts polynomials instead of MACs
(Message Authentication Codes) to verify reports, and can
mitigate node-impersonating attacks against legitimate
nodes. In our scheme, two types of nodes are
considered, they are sensing node and forwarding node.
These two types of nodes are denoted as sensor nodes. Each
node stores check polynomial, which are derived by
different primitive polynomials. When a report is transmitted
from a sensor node to the controller, each forwarding node
checks whether the forwarding reports actually carry valid
data. If not, the report is considered as a false one forged by
the adversary and then dropped. Otherwise, the report is
forwarded to the next forwarding nodes along the route. This
process ensures that false reports can be filtered along the
route as quickly as possible before arriving at the controller.
II.
EXPERIMENTAL STUDY
The design is based on IEEE Transactions on
Computers, which focus on creation of network secured
International Journal of Engineering Science and Computing, April 2016
system using JDK. False data injection detector is an
application that is designed to be used by the network
communicators to filter the false data using sensor
technologies.
The user transferring data through the false data injection
technique should be authenticated as the first step. This
authentication is done by providing a user name and
password to enter into the system for transferring the
data packets.
Figure.1.Architecture of False Data Injection Detector
In the past, a number of schemes have been designed to
filter the false injected data in sensor networks. However,
those schemes have their limitations and cannot be used
to effectively deal with attacks related to CPNS. For
example, SEF and IHA have the -threshold limitation, that
is, if the adversary compromises nodes from different
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groups, they can launch the node impersonating attack on
legitimate nodes. LBRS, LEDS and CCEF are vulnerable to
node failure and denial-of-service (DoS) attacks. Those
attacks may cause the controller not to receive measurement
on time and make the system operation unstable. DEFS and
GRSEF
achieve low resilience to the number of
compromised nodes and DEFS introduces lots of extra
control messages and incurs the consumption of energy
resources on nodes.
Before the sensor nodes are deployed, we need to prepare a
master key and a global primitive polynomial pool. The
master key can be generated and stored in the memory of
nodes before nodes are deployed and used to produce the
cluster key for each cluster. The global primitive polynomial
pool consists of several ternary polynomials, which are
randomly created before nodes are deployed. The global
primitive polynomial pool is used to assign the primitive
polynomial to each cluster and its size is < , where
is the number of sensing nodes monitoring a component, is
the total sensing nodes in the system. Finally, there is a hash
function in our scheme, and its domain and range are the set
of encrypted measurements of components reported by
sensing nodes and the set of positive integers, respectively.
III.
EXPERIMENTAL RESULTS
After logging in, the Admin creates ‘n’ number of cluster
and also creates nodes in the clusters.
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The Admin then finds out the neighbouring nodes. To find
the neighbouring nodes the Admin uses parameters such as
Distance, Range, Memory and battery of the system under
consideration. Neighbouring nodes are identified to send
data between them. Forward sensor acts as the
intermediary that facilitates data sending between
clusters. Forward sensor is also a node but it is not a group
of nodes but a single node that acts as the intermediary.
Controller also known as cluster aka Leader node head is
also selected using the previously stated parameters.
Controller is the head of a cluster, the remaining nodes send
data to the controller, and controller forwards the data to the
forward sensor, which in turn sends data to the other nodes.
Keys are provided after the clusters are created. A single
symmetric key is given to a cluster which is common to all
the nodes in the cluster. The nodes send data to the cluster
which sends it to the forward sensor. Before sending the
data, the cluster heads encrypts the data using a public
key. DES (Data Encryption Standard) is used for encryption.
After being encrypted, a signature will be generated. The
data along with the signature is sent to the forward sensor.
Data injection will only take place in the forward sensor. The
forward sensor will forward the data to the second cluster.
The second cluster will decrypt the data using the same
public key. If the signatures mismatch, then false data has
been injected. The whole process will be stopped if data has
been injected. If the signatures match then, false data has
not been injected.
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Figure.2.Data Flow Of False Data Injection Detector
As the data flow shows, the key is sent by the cluster head
to the sensor with the data. The key is verified by the second
cluster by decrypting it with the public key. If the signatures
match then no false data has been injected, else false data
has been injected.
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IV.
CONCLUSION
False data injection has been a major threat when it comes to
secure data transmission. The retransmission of data due to
false injection is a tedious system. Using encryption and
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decryption, the data can be verified as to whether it is false
or true data.
V.
FUTURE ENHANCEMENTS
We developed a cluster based primitive polynomial
assignment to limit the effect of compromised nodes to small
area via both theoretical analysis and simulation
experiments. Our data show that the developed scheme
achieves better filtering capacity and resilience to a large
number of compromised nodes in comparison with the
existing schemes.
VI.
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