Main Reference PaperAn Efficient and Privacy-Preserving Disease Risk Prediction Scheme for E-Healthcare, IEEE Internet of Things Journal, 2018 [Contiki-Cooja Simulator] [Java].
  • An efficient and privacy-preserving disease risk prediction scheme in the e-healthcare system is proposed, named EPDP. The cryptosystem has been used to protect privacy, which serves as the basis of the EPDP. Then, EPDP presents a super-increasing sequence to reduce the encryption time, and the symptom vector set of each disease is extracted by taking advantage of the naive Bayesian classifier in the phase of disease model training. Finally, based on the extracted symptom vector sets, the disease prediction result is obtained by using the efficient Bloom filter technique.

+ Description
  • An efficient and privacy-preserving disease risk prediction scheme in the e-healthcare system is proposed, named EPDP. The cryptosystem has been used to protect privacy, which serves as the basis of the EPDP. Then, EPDP presents a super-increasing sequence to reduce the encryption time, and the symptom vector set of each disease is extracted by taking advantage of the naive Bayesian classifier in the phase of disease model training. Finally, based on the extracted symptom vector sets, the disease prediction result is obtained by using the efficient Bloom filter technique.

  • To reduce the computational and communication overheads

  • To predict the disease risk and improve the diagnosis efficiency

  • To improve the efficiency using a bloom filter

+ Aim & Objectives
  • To reduce the computational and communication overheads

  • To predict the disease risk and improve the diagnosis efficiency

  • To improve the efficiency using a bloom filter

  • A technique is contributed to further improve the prediction result in the network.

+ Contribution
  • A technique is contributed to further improve the prediction result in the network.

  • Operating System : Ubuntu 12.04 LTS 64bit

  • Simulator: Cooja, Instant Contiki-3.0 and Vmware Player 12.5.6

  • Language: C

+ Software Tools & Technologies
  • Operating System : Ubuntu 12.04 LTS 64bit

  • Simulator: Cooja, Instant Contiki-3.0 and Vmware Player 12.5.6

  • Language: C

  • 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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