25-08-2017, 09:32 PM
Detecting False Data in Wireless Sensor Network using Efficient Becan Scheme
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ABSTRACT
Wireless sensor networks (WSNs), as an emerging technology
face numerous challenges. Sensor nodes are usually resource
constrained and also vulnerable to physical attacks or node
compromises. As the projected applications for wireless sensor
networks range from smart applications such as traffic
monitoring to critical military applications such as measuring
levels of gas concentration in battle fields, security in sensor
networks becomes a prime concern. In sensitive applications, it
becomes imperative to continuously monitor the transient state
of the system rather than steady state observations and take
requisite preventive and corrective actions. Generally, the
networks are prone to be attacked by adversaries who intend to
disrupt the functioning of the system by compromising the
sensor nodes and injecting false data into the network. So it is
important to shield the sensor network from false data injection
attacks. In this work, it is proposed to use a novel bandwidthefficient
cooperative authentication (BECAN) scheme for
filtering injected false data based on Bloom Filter.
INTRODUCTION
Wireless sensor network is usually composed of a large number
of sensor nodes which are interconnected through wireless links
to perform distributed sensing tasks. Each sensor node is lowcost
but equipped with necessary sensing, data processing, and
communicating components [1].
Wireless sensor network is a collection of nodes organized into
a cooperative network [2]. Each node consists of processing
capability with one or more microcontrollers, CPUs or DSP
chips and may contain multiple types of memory or flash
memory which holds program or data. Each node has a RF
transceiver usually with a single Omni- directional antenna, and
a power source such as batteries and solar cells, and
accommodates various sensors and actuators.
The advancements in micro electronics and wireless
communications have led to the creation of the wireless sensor
network (WSN) technology. This technology has many
applications including various environmental monitoring. A
primitive objective of WSNs is to answer queries by gathering
sensory data from the deployed sensors. The process of
collecting sensory data is generally called as „in-network
processing‟ or „aggregation‟. Since sensor nodes in WSN
Wireless Sensor Networks
Wireless sensor network (WSN) is an emerging technology that
has resulted in a variety of applications. Many applications
such as health care, medical diagnostics, disaster management,
military surveillance and emergency response have been
deploying such networks as their main monitoring framework
[2]. Basically, a wireless sensor network consists of a number
of tiny sensor nodes connected together through wireless links.
Some more powerful nodes may operate as control nodes called
base stations. Often, the sensing nodes are referred to as
„motes‟ while base stations are sometimes called „sinks‟. Each
sensor node can sense data such as temperature, humidity,
pressure from its surroundings, conduct simple computations
on the collected data and send it to other neighboring nodes
through the communication links. Control nodes may further
process the data and probably transfer it to a database server via
a wired connection. Figure 1 shows a typical architecture for a
WSN. The sensing nodes known as „motes‟ are represented by
black spheres and are responsible for observing the surrounding
environment whereas the cube represents a control node known
as „sink‟ which serves as the base station.