Main Reference PaperFuzzified Cuckoo based Clustering Technique for Network Anomaly Detection, Computers and Electrical Engineering, 2018.[Python]
  • The proposed Fuzzified Cuckoo based Clustering Technique (F-CBCT) attempts to identify the anomalies in the network. It incorporates two phases such as training phase and a detection phase. In the training phase, the proposed method employs a decision tree classifier model, Cuckoo Search Optimization (CSO) and K-means clustering for potential feature extraction and clustering. In the detection phase, the fuzzy approach helps to identify the anomalies.

Description
  • The proposed Fuzzified Cuckoo based Clustering Technique (F-CBCT) attempts to identify the anomalies in the network. It incorporates two phases such as training phase and a detection phase. In the training phase, the proposed method employs a decision tree classifier model, Cuckoo Search Optimization (CSO) and K-means clustering for potential feature extraction and clustering. In the detection phase, the fuzzy approach helps to identify the anomalies.

  • To discover the anomalies in the network.

  • To attain a high detection rate of anomalies

Aim & Objectives
  • To discover the anomalies in the network.

  • To attain a high detection rate of anomalies

  • To develop the system based on the multi-objective optimization function to contribute the accuracy.

Contribution
  • To develop the system based on the multi-objective optimization function to contribute the accuracy.

  • 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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