BibTeX:

@article{IJIRSTV3I5027,
     title={A Survey on Top-K Query Processing and Malicious Node Identification in MANETS},
     author={D. Porselvi and B. Gopinathan},
     journal={International Journal for Innovative Research in Science & Technology},
     volume={3},
     number={5},
     pages={195--198},
     year={},
     url={http://www.ijirst.org/articles/IJIRSTV3I5027.pdf},
     publisher={IJIRST (International Journal for Innovative Research in Science & Technology)},
}

In versatile imprompt systems (MANETs), it is powerful to recover information things utilizing top-k query. Notwithstanding, precise results may not be obtained in situations when vindictive nodes are available. It is expected that pernicious nodes endeavor to supplant vital information things with pointless ones (we call these as data replacement attacks attacks), and propose techniques for top-k inquiry preparing and malicious node identification taking into account node gathering in MANETs. Keeping in mind the end goal and to keep up the exactness of the query result, answer with nodes k information things with the most noteworthy score along different courses, and the query issuing node tries to identify attacks from the data appended to the answer/reply messages. In the wake of distinguishing attacks, the query issuing node tries to recognize the malevolent nodes through message trades with different nodes. At the point when different malicious nodes are available, the inquiry issuing node will most likely be unable to recognize every single malicious node at a solitary inquiry. It is viable for a node to share data about the identified malicious nodes with other nodes. In our strategy, every node separates all nodes into gatherings by utilizing the likeness of the data about the identified malignant nodes. At that point, it identifies noxious nodes in view of the data on the gatherings. By using network simulator and OTCL, we verify, through simulation experiments, that the proposed top-k query processing method achieves high accuracy of the query result, and that the malicious node identification method effectively identifies a malicious node.

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