Main Reference PaperEfficient Trustworthiness Management for Malicious User Detection in Big Data Collection, IEEE Transactions on Big Data, 2018 [Python/Hadoop]
  • In data collection, the trustworthiness of users is an important. To calculate the trustworthiness of user in data collection, this work divides the trustworthiness into familiarity and similarity trustworthiness. To reduce the computational complexity, it divides all the participated users into small groups according to similarity, and calculate the trustworthiness of each group separately. The grouping strategy makes the trustworthiness be able to represent the trust level of the whole group.

Description
  • In data collection, the trustworthiness of users is an important. To calculate the trustworthiness of user in data collection, this work divides the trustworthiness into familiarity and similarity trustworthiness. To reduce the computational complexity, it divides all the participated users into small groups according to similarity, and calculate the trustworthiness of each group separately. The grouping strategy makes the trustworthiness be able to represent the trust level of the whole group.

  • To reduce the computational complexity

Aim & Objectives
  • To reduce the computational complexity

  • In the proposed scheme, if users provide false information in the very beginning, they cannot be found out to be malicious effectively, a method is contributed to detect the malicious user.

Contribution
  • In the proposed scheme, if users provide false information in the very beginning, they cannot be found out to be malicious effectively, a method is contributed to detect the malicious user.

  • 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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