K-anonymity privacy protection algorithm for multi-dimensional data against skewness and similarity attacks

HIGHLIGHTS

  • who: Bing Su and colleagues from the School of Computer and Artificial Intelligence, Changzhou University, Changzhou, China have published the Article: K-Anonymity Privacy Protection Algorithm for Multi-Dimensional Data against Skewness and Similarity Attacks, in the Journal: Sensors 2023, 23, 1554. of /2023/
  • what: To defend these the authors propose a algorithm for multi-dimensional and_(KAPP) combined with t-closeness. The authors propose a multi-dimensional sensitive clustering algorithm based on improved African vultures optimization. The authors propose an equivalence class partition and generalization method based on the measurement of sensitive data`s . . .

     

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