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Abstract
The paper examines personal medical and nutritional data streams on digital healthcare platforms and the cyber threats targeting them. Re-identification, attribute inference and membership inference attacks caused by hidden correlations between quasi-identifiers and clinical and dietary attributes are classified. A multilevel aggregative security model and a method for estimating attribute criticality weights using Shannon mutual information are proposed.
References
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