Cryptanalysis of a Privacy-Preserving Aggregation Protocol
Amit Jyoti Datta, Marc Jóye · IEEE Transactions on Dependable and Secure Computing · 2016
Privacy-preserving aggregation protocols allow an untrusted aggregator to evaluate certain statistics over a population of individuals without learning each individual’s privately owned data. In this note, we show that a recent protocol for computing an aggregate sum due to Jung, Li, and Wan (IEEE Transactions on Dependable and Secure Computing, 2015) is universally breakable, that is, anyone is able to recover each individual’s private data from the corresponding ciphertext. We also describe an alternate collusion attack against their companion product protocol.