Efficient and secured compression and steganography technique in wireless sensor network
Wireless Sensor Networks (WSNs) have emerged as one of the most promising so- lutions for wireless communication. They can be used in a wide variety of appli- cations ranging from military tasking, healthcare servicing, disaster prediction and indoor positioning. However, the need to use less com...
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| Main Author: | |
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| Format: | Thesis |
| Language: | English |
| Published: |
2016
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| Online Access: | http://psasir.upm.edu.my/id/eprint/69360/1/FSKTM%202016%2024%20IR.pdf http://psasir.upm.edu.my/id/eprint/69360/ |
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| Summary: | Wireless Sensor Networks (WSNs) have emerged as one of the most promising so-
lutions for wireless communication. They can be used in a wide variety of appli-
cations ranging from military tasking, healthcare servicing, disaster prediction and
indoor positioning. However, the need to use less complex and low-cost sensor de-
vice results in constraints in computational power, communication bandwidth, and
operational energy. In fact, the growing demands for new and much complex WSN
applications require optimising both efficiency and security of data communication
archetype in order to counterbalance their intrinsic limitations. In this study, to ad-
dress these issues, we propose two techniques, one for minimising the transmitted
data size in order to improve the efficiency of the WSN and the other for securing
the sensed data transmission. First, the new data compression algorithm is proposed
for compressing sensed data before it gets transmitted to the sink. The proposed
solution is designed to be less complicated, low energy consumption and resource
efficient with the ability to provide a lossless compression for a variety of data size.
We analyse the solution and compare with a range of well-known algorithms in terms
of compression ratio, memory usage, the number of instructions, compression speed
and energy consumption. Two datasets have been used in the experiment, generated
data set and Harvard Sensor Lab data set, in order to validate the performance of the
proposed solution. The result shows that the proposed solution can compress both
small and large data efficiently with up to 60% compression rate, 10 times faster
compression speed and 4 times lower energy consumption compared to existing al-
gorithms. Second, an improved steganographic algorithm based on the infamous
Least Significant Bit (LSB) is proposed for hiding the sensed data scheduled for
transmission. The proposed solution comes with low complexity and is used to en-
hance the security of the standard LSB algorithm by replacing an originally less
secured sequential data hiding with a random pixel selection. This random pixel se-
lection is achieved via the use of an Elliptic Curve equation. In terms of security, the proposed solution is studied against brute-force attacks and the analysis shows
that the new algorithm can withstand this type of attack with an ample amount of
hiding possibilities that make the process of retrieving the message extremely diffi-
cult. Furthermore, some analyses on hiding quality show that our algorithm retains
the cover image quality as high as that of standard LSB algorithm. Apart from being
able to work with various limitations of the sensor node, both techniques can pre-
serve the resource without sacrificing the performance of the nodes, security level
of the data and lifetimes of the WSN, and therefore are good candidates for future
implementation into the sensor node. |
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