International Journal of Engineering Trends and Technology (IJETT) – Volume 23 Number 8- May 2015
Data Security Using Loc-Trust Method
Jnanavi R B#1, Hemanth S R*2
1
M Tech student, Dept of computer science, Maharaja Institute of Technology, Mysore,
Karnataka, India
2
Asst Professor, Dept of computer science, Maharaja Institute of Technology, Mysore,
Karnataka, India
Abstract: Wireless sensor networks are broadly distributed
sensors which monitor physical or environmental conditions.
They are vulnerable to various security attacks such as selective
forwarding, black hole and false data injection attack. An
adversary can compromise one or more sensor nodes and get the
information about those nodes. Through those compromised
nodes false data is injected and drains the energy resource in the
en-route nodes. So the filtering should be executed as early as
possible to pacify the energy consumption. To deal with this issue
a filtering mechanism known as Loc-Trust scheme is proposed
which filters false data earlier and provides secure data
transmission. The AODV protocol is used for routing and it is
implemented in NS2, the en-route nodes verifies the reports
based on the relative location information of the node. Only
small amount of injected data needs to be checked by the sink,
this reduces the burden on sink.
Keywords: Wireless Sensor Networks, false data injection,
compromised node, energy consumption.
I. INTRODUCTION
Wireless Sensor Networks comes up as an vital area in
wireless technology. In future, the WSNs is composed by
thousands of inexpensive nodes, each nodes with sensing
capability with limited computational and communication
power and can be deploy in a large-scale sensor network. It is
a new network technique and applied in real life, rescue and
military environment. A large number of tiny and inexpensive
sensor nodes compose a distributed WSN; they are typically
resource constrained, with limited energy lifetime, slow
embedded processor, limited memory, and low-bandwidth
radios[1].
A tiny device in WSN monitors physical or environmental
conditions such as temperature, pressure, motion or pollutants
etc. at different areas[3][4]. Such sensor networks is deployed
in a vast variety of environments for commercial, civil, and
military applications such as surveillance, vehicle tracking,
climate and habitat monitoring, intelligence, medical, and
acoustic data gathering. The key limitation in wireless sensor
networks is storage, power and processing. The main
components of sensor nodes are radio transceiver,
microcontroller, power supply, and the actual sensor[2]. The
sensing bounds measures atmosphere condition related to the
environment surrounding, the sensor then transforms them
into an electric signal. Proceeding such a signal broadcast
some properties about objects located and/or events happening
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in the vicinity of the sensor. The sensor sends the collected
data, via radio transmitter, to a base station either directly or
through a intermediate nodes.
Sensor nodes will be deployed in hostile environment and it
doesn’t equip with special tamper-resistant hardware, so an
adversary can easily compromise a sensor node[5]. By using
the compromising nodes the attacker can inject fake sensing
reports, which represent nonexistent events in the field, into
the network with the aim of delude the BSs or depleting the
limited energy resources of forwarding nodes. To prevent
them from fabricating reports, every sensing report should be
witnessed by multiple nodes, through attaching multiple
message authentication codes (MACs) generated by them
using different cryptographic keys. The key challenge in
sensor networks is to maximize the lifetime of sensor nodes
due to the fact that it is not practical to replace the batteries of
thousands of sensor nodes. Therefore, computational
operations of nodes and communication protocols must be
made as energy efficient as possible.
It is crucial to filter false data in WSN[4] which results in
energy deprivation. To deal with this issue, some false data
filtering mechanism have been developed. Some filtering
mechanisms use the symmetric key technique when the node
is compromised. Compromised node can abuse its keys to
generate false reports and the reliability of the filtering
mechanisms is degraded. The node can verify the report based
on the MACs carried in it. This cannot filter false data forged
collaboratively by t compromised nodes from different areas.
In order to overcome this Loc-Trust scheme is used, in this
secure routing is established using the AODV protocol.
Initially the location information of the sensor nodes is
obtained using that information trust value will be calculated.
Based on these values the report will be verified by the enroute nodes and filters out the false data.
II. EXISITING SYSTEM
Different works on filtering false data in wireless sensor
networks have been proposed, some are Statistical en-route
filtering, interleaved hop-by-hop authentication and A Double
Key-sharing. The details of these techniques are discussed
below.
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International Journal of Engineering Trends and Technology (IJETT) – Volume 23 Number 8- May 2015
A. Statistical en-route filtering
Ye et al. proposed a statistical en-route filtering scheme based
on probabilistic key distribution. In this the global key pool
will be divided into n partitions, each partitions contain m
keys. Every node randomly selects k keys from one partition.
When some event occurs, each sensing node creates a
message authentication code (MAC) for its report using one of
its random keys. The cluster head combines the reports from
the sensing nodes and guarantees each aggregated report
contains T MACs that are generated using the keys from T
different partitions, where T is a predefined security parameter.
More than T-1 nodes cannot be compromised; each
forwarding node can detect a false report with a probability
proportional to 1/n. The filtering ability of SEF is independent
of the network topology, but restrained by the value of n. To
increase the filtering ability, the value of n is cut down;
however this allows the adversaries to break all partitions
more easily. Along with this, since the keys are shared by
number of nodes, the compromised nodes can take off other
nodes and report some forged events that “occur” in other
clusters [8].
III. PROPOSED SYSTEM
The design goal of Loc-trust method is to achieve energy
efficient authentication for filtering false data and providing
data security. Sensor nodes are deployed randomly at certain
region. The communication between the two sensors nodes
are bidirectional. The nodes within the transmission range can
directly transfer the data. If the sensor node is far from the
transmission, it makes use of other intermediate nodes to
establish a route. Each sensor node have the node ID’s.
Between the sensor nodes they elect one node as COS based
on battery. Data aggregation is done, it is a process in which
information is gathered and expressed in a summary form.
Once the nodes are deployed secure routing is established
using AODV protocol. Every node will have the node ID
using that ID routing is done. When the nodes sense the event
it obtains its location information. And finally generates a
report with location information binded to the report. En-route
node verifies the report by calculating the trust value, using
the location information in the report. The trust value should
be in the range [0, 1].
B. Interleaved hop-by-hop authentication (IHA)
Zhu et al. proposed an IHA scheme. In this, the base station
periodically initiates an association process enabling each
node to establish pair wise keys with other nodes that are t+1
hops away, where t is called as security threshold value. In
IHA, each sensing node creates a MAC using one of its
multihop pairwise keys and a legitimate report should contain
t+1 distinct MACs. Since every multihop pairwise key is
distinguishable, IHA can tolerate up to t level compromised
nodes in each cluster instead of in the whole network as SEF
does. Moreover, the high communication overhead incurred
by the association process makes IHA unsuitable for the
networks whose topologies change frequently[7].
C. A Double Key-sharing
Sun et al. Proposed Double key sharing based false data
filtering scheme. In DSF, after deployment nodes will be
grouped into clusters and a block region is formed through
pair-wise keys closer to the source node. When an event
occurs, a legitimate report must carry two types of MACs.
And even symmetric keys are added to the clusters. In
filtering phase, each forwarding node has to validate the
correctness of these two types of MACs carried in the report
and drops part of tail of the reports just outside the blocked
region. False report injected by compromised node from
different clusters can be detected and filtered out by binding
the set of keys to the cluster. The cluster head will be elected
based on its ID, it collects the sensing information from the
nodes and generates the report on behalf of the cluster. Later
by checking the MACs the reports will be verified. If the
attached MAC differs from locally computed the report will
be dropped. But in this false report generated by the cluster
can be filtered within only little hops[9].
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Fig -1: Flow of stages in proposed model
A. AODV working
AODV builds routes using a route request/route reply cycle.
When a source node needs a route to a destination, it
broadcasts a route request (RREQ) packet.
1. Nodes which receive this packet add that entry in their
routing tables for the source. The nodes also keep track of
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International Journal of Engineering Trends and Technology (IJETT) – Volume 23 Number 8- May 2015
source’s IP address, current sequence number and broadcast
ID. The RREQ also contains the most recent sequence number
for the destination, of which the source node is aware.
2. A node receiving the RREQ may send a route reply(RREP)
in the following case:If it is the destination.
If it has a route to the destination with sequence number
greater than or equal to that contained in the RREQ, indicating
that it has fresh information about the destination. If none of
the above cases are satisfied then the RREQ is forwarded
using a broad-cast. The broadcast ID is used by nodes to
detect already processed RREQs. If they receive a RREQ
which they have already processed, they discard the RREQ
and do not forward.
3. After establishing the path source sends data to Destination.
Fig -3: Energy Consumption (JS) with number of nodes
IV. EXPERIMENTAL RESULTS
The comparison of the proposed routing scheme and basic
AODV routing protocol is done. The results are obtained for
the different combinations of the number of connected nodes
in the network. The secure data transmission mechanism is
evaluated in terms of Packet Delivery Ratio, Average Delay,
Energy consumption and overhead. Its compared with existing
system and found remarkable improvement in their
performances.
Fig -4: Packet Delivery ratio with number of nodes
Fig - 2: Delay (ms) with number of nodes
Fig -5: Overhead with number of nodes
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International Journal of Engineering Trends and Technology (IJETT) – Volume 23 Number 8- May 2015
CONCLUSION
A major challenge for a wireless sensor network lies in the
energy constraint at each node, which poses a fundamental
limit in the network life time. False data filtering is an
important issue in Wireless Sensor Networks. Multiple
compromised nodes forge a fake report and inject the report
into the network. This type of attack is hard to defend with
existing approach. This method aims to deal with this problem,
by using the location information along with the MAC. The
reports are verified by using the location and trust value. It is
very suitable for filtering false data in wireless sensor
networks and hence compromise-tolerant.
ACKNOWLEDGMENT
We would like to give our sincere gratitude to our guide Mr.
Hemanth who encouraged and guided us throughout this paper.
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