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Sensitive and Private Data Analysis: A Systematic Review

Publication Type: 
Refereed Conference Meeting Proceeding
Abstract: 
Each day an extensive amount of data is produced from various organisations, such as e-commerce, IT, hospitals, retail and supply chain, etc. Due to the expansion of computer devices and advances in technology this immense amount of data has been collected and analysed to support decision making. The examination of such data is advancing businesses and contributing advantageously to society in numerous diverse areas. However, serious privacy concerns are raised due to the storage and flow of potentially sensitive data. Strategies that permit the knowledge extraction from the data, while protecting privacy, are known as privacy-preserving data mining (PPDM) techniques. This paper surveys the analysis of private and sensitive data using various PPDM algorithms and techniques. We also highlighted their advantages and limitations within various contexts.
Conference Name: 
3rd International Conference on Future Networks and Distributed Systems (ICFNDS '19)
Digital Object Identifer (DOI): 
10.1145/3341325.3342002
Publication Date: 
02/07/2019
Conference Location: 
France
Institution: 
National University of Ireland, Dublin (UCD)
Open access repository: 
Yes