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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, ...
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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, ...
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In this paper we propose a new approach for anonymizing sequential data by hiding infrequent, and thus potentially sensible, subsequences. Our approach ...