US 12,019,784 B2
Privacy preserving evaluation of sensitive user features for anomaly detection
Salah E. Machani, Medford, MA (US); and Alex Zaslavsky, Brookline, MA (US)
Assigned to EMC IP Holding Company LLC, Hopkinton, MA (US)
Filed by EMC IP Holding Company LLC, Hopkinton, MA (US)
Filed on Oct. 30, 2019, as Appl. No. 16/668,705.
Prior Publication US 2021/0133357 A1, May 6, 2021
Int. Cl. G06F 21/62 (2013.01); G06F 21/32 (2013.01); G06F 21/60 (2013.01)
CPC G06F 21/6263 (2013.01) [G06F 21/32 (2013.01); G06F 21/602 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method, comprising:
obtaining, by at least one processing device of a service provider, values of one or more predefined features based at least in part on personal information of a given remote user, wherein the values of the one or more predefined features are computed by at least one processing device of the given remote user, wherein at least one of the values of the predefined features is categorized into a discrete category of a plurality of discrete categories, by the at least one processing device of the given remote user, prior to providing the values of the one or more predefined features to the service provider, such that the service provider cannot access the personal information of the given remote user associated with the at least one value of the one or more predefined features, wherein the categorization of the at least one value of the one or more predefined features by the at least one processing device of the given remote user is based at least in part on an evaluation of dynamic contextual data by the at least one processing device of the given remote user, wherein the dynamic contextual data is used for the categorization of the at least one value of the one or more predefined features and is provided to the at least one processing device of the given remote user by the at least one processing device of the service provider; and
processing, by the at least one processing device of the service provider, the values of the one or more predefined features based at least in part on personal information to detect one or more predefined anomalies associated with one or more of the given remote user and the at least one processing device of the given remote user.