Nothing Special   »   [go: up one dir, main page]

×
Please click here if you are not redirected within a few seconds.
Feb 13, 2014 · We introduce a k-anonymity framework for sequence data, by defining the sequence linking attack model and its associated countermeasure.
In this paper we propose to apply the Privacy-by-design paradigm for designing a technological framework to counter the threats of undesirable, unlawful effects ...
In this paper we propose to apply the Privacy-by-design paradigm for designing a technological framework to counter the threats of undesirable, unlawful effects ...
Abstract: The increasing availability of personal data of a sequential nature, such as time-stamped transaction or location data, enables increasingly ...
This paper introduces a k-anonymity framework for sequence data, by defining the sequence linking attack model and its associated countermeasure, ...
People also ask
ABSTRACT. Research in the areas of privacy preserving techniques in databases and subsequently in privacy enhancement tech-.
May 17, 2021 · In this paper, we propose a privacy-preserving framework using sequential pattern mining in distributed data sources.
In this paper, we propose a new technique that provides an anonymized dataset of sequences, while preserving sequential pattern mining results. We use a method ...
Privacy preserving data mining is a hot research direction of data mining in the big data environment. If Data mining has been used properly, ...
Missing: Anonymity | Show results with:Anonymity
In this paper we propose a new approach for anonymizing sequential data by hiding infrequent, and thus potentially sensible, subsequences. Our approach ...