Wireless Sensors Network Using Machine Learning Approach

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Secured Wireless Sensors Network Using Machine Learning approach
Neha Meshram, Student,
Department of computer Science and information Technology,
Amravati University,
Machine learning inspires many practical solutions that maximize many resource utilization and prolong the lifespan of a network. As wireless sensors network (WSNs) monitor dynamic environment that rapidly changes over time such behavior is either caused by the external factor or by initiated by the system designers. A comparative guide is provided to aid WSN designers to develop suitable machine learning solutions for appropriate application challenges. The security properties of sensors must be known before deploying the intelligent systems on critical infrastructure. This paper provides some steps for generating a comprehensive security model for sensors network as sensors network is not a traditional computing device hence existing security models are not applicable.
Multiple autonomous, tiny, low-cost and low-power sensor nodes comprise a wireless sensors network (WSN). The sensors nodes are equipped with various types of sensors such as thermal , acoustic, chemical, pressure, weather and optical sensors which gather information from various nodes and collaborate to forward sensed data to base stations for further processing. WSNs designers have to address common issues related to data aggregation, data reliability,
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