Abstract
Spontaneous reporting systems (SRSs) are used to collect adverse drug events (ADEs) for their evaluation and analysis. Periodical SRS data publication gives rise to a problem where sensitive, private data can be discovered through various attacks. The existing SRS data publishing methods are vulnerable to Medicine Discontinuation Attack(MD-attack) and Substantial symptoms-attack(SS-attack). To remedy this problem, an improved periodical SRS data publishing—PPMS(k, θ, ɑ)-bounding is proposed. This new method can recognize MD-attack by ensuring that each equivalence group contains at least k new medicine discontinuation records. The SS-attack can be thwarted using a heuristic algorithm. Theoretical analysis indicates that PPMS(k, θ, ɑ)-bounding can thwart the above-mentioned attacks. The experimental results also demonstrate that PPMS(k, θ, ɑ)-bounding can provide much better protection for privacy than the existing method and the new method dose not increase the information loss. PPMS(k, θ, ɑ)-bounding can improve the privacy, guaranteeing the information usability of the released tables.
Highlights
Many developed countries have established spontaneous reporting systems (SRSs) for the collection of adverse drug events (ADEs)
We introduce new symbols as follows: Substantial symptoms-record(ss-record): as mentioned earlier, for a record t(t2T), if t has many more symptoms/adverse drug reactions than others in T, t is an ss-record in table T
We analyze the methods from security and information loss
Summary
Many developed countries have established spontaneous reporting systems (SRSs) for the collection of adverse drug events (ADEs). These datasets allow researchers to analyze possible correlations between drugs and adverse reactions. Typical spontaneous reporting systems include FAERS of the US Food and Drug Administration [1] and the UK Yellow Card scheme [2]. These datasets usually involve information which relates to an individual’s privacy.
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