Adil Fahad scite author profile

In this paper, a novel k-NN approach based on Various-Widths Clustering, named kNNVWC, is proposed to efficiently find k-NNs for a query object from a given data set. kNNVWC does clustering using various widths, where a data set is clustered with a global width first and each produced cluster that meets the predefined criteria is recursively clustered with its own local width that suits its distribution. Experimental results demonstrate that kNNVWC performs well compared to state-ofart of k-NN search algorithms.

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PPFSCADA: Privacy preserving framework for SCADA data publishing

Fahad

Tari

Almalawi

et al. 2014

Future Generation Computer Systems

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Adil Fahad

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An Efficient Data-Driven Clustering Technique to Detect Attacks in SCADA Systems

kNNVWC: An efficient k-nearest neighbours approach based on Various-Widths Clustering

PPFSCADA: Privacy preserving framework for SCADA data publishing

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