A Panacea to Soft Computing Approach for Sinkhole Attack Classification in a Wireless Sensor Networks Environment
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Abstract
Description
Small sensor nodes with the capability to sense and process data make up a
wireless sensor network (WSN). This environment has limitations of low
energy, low computational power and simple routing protocols; making is
susceptible to attacks such as sinkhole attack. This attack happens when the
enemy node in the network camouflages as a genuine node nearest to the
base station, thereby have information sent by a source node to another
destination node travel through it, giving it chance to alter, drop or delay
information from reaching to the base station as intended. In our paper, the
research developed a sinkhole detection technique, an enhancement of ant
colony optimization by including a hash table in the ant colony optimization
technique to advance sinkhole attack detection and reduce fa1se alarm rate in
a wireless sensor network. An increase in the detection rate of 96% was
achieved and result out performed other related research works when
compared and further research discussed.
Keywords
QA Mathematics, QA75 Electronic computers. Computer science