Use of Class Dependent Features in K-NN Classifier for the Classification of Encrypted Data
Keywords:
Cloud Computing, Features Selection, Privacy-Preserving, Data Encryption, Machine LearningAbstract
Cloud Computing stores the data in encrypted form. Classification of the data is required in many machine learning applications, so in the field of cloud computing, classification of the encrypted data is one of the major challenges. Extracting the class dependent features from the encrypted data and using these features in a well-known K-NN classifier can be used to classify the encrypted data at the cloud. In the proposed work we have encrypted and data extracted the correlation coefficient between the two or more variables and feeding it into the K-NN classifier and classifying the data. We have calculated the precision, recall, F1 score and accuracy of the proposed system and evaluated the performance of it with SVM and Naïve Byes classifiers.
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