Nortonlifelock Inc.

Nissan North America, Inc.

Renault S.a.s.

Mehmet Emre Gursoy

Acar Tamersoy

Vikram Krishnamurthy

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.

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

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.

A method and apparatus may be used in a vehicle to generate a dynamic driver score. The method may include collecting data. The data may be collected at a predetermined interval. The data may include one or more frames. Each frame may correspond to the predetermined interval and may be divided into segments. Each frame may include a first acceleration data and a second acceleration data. The first acceleration data may be associated with an acceleration of a vehicle at a first segment of the frame, and the second acceleration data may be associated with an acceleration of the vehicle at a second segment of the frame. The frames may be grouped using machine learning methods to determine the driver score. The driver score may be used to modify driving behavior.

Growing community of inventors

Atlanta, GA, United States of America

Mehmet Emre Gursoy