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Secure Group Testing

The principal goal of Group Testing (GT) is to identify a small subset of &#34;defective&#34; items from a large population, by grouping items into as few test pools as possible. The test outcome of a pool is positive if it contains at least one defective item, and is negative otherwise. GT algorithms are utilized in numerous applications, and in many of them maintaining the privacy of the tested items, namely, keeping secret whether they are defective or not, is critical. In this paper, we consider a scenario where there is an eavesdropper (Eve) who is able to observe a subset of the GT outcomes (pools). We propose a new non-adaptive Secure Group Testing (SGT) scheme based on information-theoretic principles. The new proposed test design keeps the eavesdropper ignorant regarding the items&#39; status. Specifically, when the fraction of tests observed by Eve is $0 \leq δ<1$, we prove that with the naive Maximum Likelihood (ML) decoding algorithm the number of tests required for both correct reconstruction at the legitimate user (with high probability) and negligible information leakage to Eve is $\frac{1}{1-δ}$ times the number of tests required with no secrecy constraint for the f