INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
Several agencies, institutions, bureaus, organizations make (sensitive) data involving people publicly available. However the sensitivity of the real world datasets needs more data privacy, confidentiality, authenticity. It is obvious that the user’s data privacy is being violated by the intruders. So, in order to secure the user’s sensitive data during releases from the intruders, a technique called Slicing is proposed. Several anonymization techniques, such as generalization and bucketization, have been designed for privacy preserving micro data publishing. We show that slicing preserves better data utility than generalization and can be used for membership disclosure protection and it can also handle high-dimensional data. Our workload experiments confirm that slicing preserves better utility than generalization and is more effective than bucketization in workloads involving the sensitive attribute.
Keywords:
Keywords- Privacy-preserving release of transaction data, anonymity, sequential background knowledge
Cite Article:
"A Novel Approach for Privacy Preserving in Data Publishing Using Slicing", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.8, Issue 7, page no.d800-d802, July-2023, Available :http://www.ijnrd.org/papers/IJNRD2307392.pdf
Downloads:
000118760
ISSN:
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Facebook Twitter Instagram LinkedIn