Identifying and protecting against computer security threats while preserving privacy of individual client devices using condensed local differential privacy (cldp)

Abstract

Identifying and protecting against computer security threats while preserving privacy of individual client devices using condensed local differential privacy (CLDP). In one embodiment, a method may include accessing an actual data value, generating a perturbed data value by adding noise to the actual data value, aggregating the perturbed data values to at least partially cancel out aggregate noise of the aggregated perturbed data values at a population level, analyzing, using CLDP, the aggregated perturbed data values to identify a computer security threat, and in response, protecting against the computer security threat by performing a remedial action. The amount of noise added to each actual data value may be probabilistically computed such that a probability of noise being added decreases as an amount of added noise increases. The perturbed data values may preserve privacy of the actual data values.