The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Hybrid Privacy Preservation Technique Using Neural Networks
Abstract
A novel Artificial Neural Network (ANN) dimension expansion-based framework that addresses the demand for privacy preservation of low dimensional data in clustering analysis is discussed. A hybrid approach that combines ANN with Linear Discriminant Analysis (LDA) is proposed to preserve the privacy of data in mining. This chapter describes a feasible technique for privacy preserving clustering with the objective of providing superior level of privacy protection without compromising the data utility and mining outcome. The suitability of these techniques for mining has been evaluated by performing clustering on transformed data and the performance of the proposed method is measured in terms of misclassification and privacy level percentage. The methods are further validated by comparing the results with traditional Geometrical Data Transformation Methods (GDTMs). The results arrived at are significant and promising.
Related Content
|
Guru Prasad M. S., Praveen Gujjar, H. N. Naveen Kumar, M. Anand Kumar, S. Chandrappa.
© 2023.
14 pages.
|
|
Bhawnesh Kumar, Ashwani Kumar, Harendra Singh Negi, Javed Alam.
© 2023.
15 pages.
|
|
Abhishek Kumar, Karan Singh.
© 2023.
21 pages.
|
|
Anuj Singh, Somjit Mandal, Kamlesh Chandra Purohit.
© 2023.
21 pages.
|
|
Muthumanikandan Vanamoorthy.
© 2023.
13 pages.
|
|
Janmejay Pant, Rakesh Kumar Sharma, Himanshu Pant, Devendra Singh, Durgesh Pant.
© 2023.
11 pages.
|
|
Siddhardha Kollabathini.
© 2023.
9 pages.
|
|
|