Main Reference PaperEC2: Ensemble Clustering and Classification for Predicting Android Malware Families, IEEE Transactions on Dependable and Secure Computing, 2017.[Python]
  • The proposed EC2 (Ensemble Clustering and Classification) identifies the existing and the new malware families in Android. It amalgamates the supervised learning technique of classification with the unsupervised learning method of clustering to identify the Android family malware. Also, it retrieves the family-specific to discriminate the Android families.

Description
  • The proposed EC2 (Ensemble Clustering and Classification) identifies the existing and the new malware families in Android. It amalgamates the supervised learning technique of classification with the unsupervised learning method of clustering to identify the Android family malware. Also, it retrieves the family-specific to discriminate the Android families.

  • To detect the Android family malware in various sizes

  • To classify the malware families based on the feature extraction technique

Aim & Objectives
  • To detect the Android family malware in various sizes

  • To classify the malware families based on the feature extraction technique

  • The exploitation of features with the linear and the non-linear properties improves the classification performance of the system

Contribution
  • The exploitation of features with the linear and the non-linear properties improves the classification performance of the system

  • M.E / M.Tech/ MS / Ph.D.- Customized according to the client requirements.

Project Recommended For
  • M.E / M.Tech/ MS / Ph.D.- Customized according to the client requirements.

  • No Readymade Projects-project delivery Depending on the complexity of the project and requirements.

Order To Delivery
  • No Readymade Projects-project delivery Depending on the complexity of the project and requirements.

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