Main Reference PaperAn Evaluation of the Performance of Restricted Boltzmann Machines as a Model for Anomaly Network Intrusion Detection, Computer Networks, 2018.
  • It illustrates the potential use of Restricted Boltzmann Machine (RBM) machine learning technique to discriminate the anomalous and normal NetFlow traffic. It also exploits the balanced set for mitigating any biases.

+ Description
  • It illustrates the potential use of Restricted Boltzmann Machine (RBM) machine learning technique to discriminate the anomalous and normal NetFlow traffic. It also exploits the balanced set for mitigating any biases.

  • To evaluate the use of RBM in the anomaly detection system

  • To eliminate the biases in the system

+ Aim & Objectives
  • To evaluate the use of RBM in the anomaly detection system

  • To eliminate the biases in the system

  • To evaluate the performance of the RBM machine learning technique for different real-world dataset

+ Contribution
  • To evaluate the performance of the RBM machine learning technique for different real-world dataset

  • Operating system: Ubuntu / Windows

  • Java/Python/R

+ Software Tools & Technologies
  • Operating system: Ubuntu / Windows

  • Java/Python/R

  • 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.

Professional Ethics: We S-Logix would appreciate the students those who willingly contribute with atleast a line of thinking of their own while preparing the project with us. It is advised that the project given by us be considered only as a model project and be applied with confidence to contribute your own ideas through our expert guidance and enrich your knowledge.

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