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 mapping non-ordinal data values to ordinal data values, generating a first ordering scheme for the ordinal data values, accessing actual non-ordinal data values, converting the actual non-ordinal data values to actual ordinal data values according to the mapping, generating first perturbed ordinal data values by adding noise, and aggregating the first perturbed ordinal data values. The method may also include generating a second ordering scheme for the ordinal data values by denoising and refining the aggregated first perturbed ordinal data values, generating second perturbed ordinal data values by adding noise, aggregating the second perturbed ordinal data values, analyzing the aggregated second perturbed ordinal data values to identify a computer security threat, and in response, thwarting the computer security threat.