Titlebook: Global Security, Safety, and Sustainability; 7th International an Christos K. Georgiadis,Hamid Jahankhani,Ameer Al-N Conference proceedings

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,First Analysis—From Naive to Flexible,privacy of data subjects data refer to. Furthermore, existing privacy and information loss related metrics are presented, as well as the algorithm implementing the maximum entropy anonymity concept. From a privacy protection perspective, the achieved results are very promising, while the suffered information loss is limited.

PHIL

entail

Maximum Entropy Oriented Anonymization Algorithm for Privacy Preserving Data Mining,privacy of data subjects data refer to. Furthermore, existing privacy and information loss related metrics are presented, as well as the algorithm implementing the maximum entropy anonymity concept. From a privacy protection perspective, the achieved results are very promising, while the suffered information loss is limited.

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https://doi.org/10.1007/978-1-4842-3441-9n of monophyletic clusters. In this paper, using public available data, we demonstrate the departure of the democratic virus writing model in which even moderate programmers managed to create successful virus strains to an entirely aristocratic ecosystem of highly evolved malcode.

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Maximum Entropy Oriented Anonymization Algorithm for Privacy Preserving Data Mining,icular, a maximum entropy oriented algorithm to protect sensitive data is proposed. As opposed to .anonymity, ℓ.diversity and .closeness, the proposed algorithm builds equivalence classes with possibly uniformly distributed sensitive attribute values, probably by means of noise, and having as a lowe

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