Mcafee, Inc.

Musarubra US LLC

Sumant Vashisth

Sudeep Das

Pramod Sharma

Ned M Smith

Vincent J Zimmer

Rajesh Poornachandran

Simon R Hunt

Arthur S Zeigler

Technologies for privacy-safe security policy evaluation are disclosed herein. An example apparatus includes at least one memory, and at least one processor to execute instructions to at least identify one or more non-sensitive parameters of a plurality of policy parameters and one or more sensitive parameters of the plurality of the policy parameters, the plurality of the policy parameters obtained from a computing device in response to a request from a cloud analytics server for the plurality of the policy parameters, encrypt the one or more sensitive parameters to generate encrypted parameter data in response to the identification of the one or more sensitive parameters, and transmit the encrypted parameter data to the cloud analytics server, the cloud analytics server to curry a security policy function based on one or more of the plurality of the policy parameters.

Technologies for privacy-preserving security policy evaluation

Technologies for privacy-safe security policy evaluation are disclosed herein. An example apparatus includes at least one processor, and memory including instructions that, when executed, cause the at least one processor to curry a security policy function to generate a privacy-safe curried function set, the security policy function to generate a security policy as a function of a plurality of policy parameters, the privacy-safe curried function set including a non-sensitive function that receives a non-sensitive parameter of the plurality of policy parameters as an argument, the privacy-safe curried function set further including a sensitive function that receives a sensitive parameter of the plurality of policy parameters as an argument; access unencrypted parameter data corresponding to the non-sensitive parameter of the plurality of policy parameters; evaluate the non-sensitive function of the privacy-safe curried function set to generate the sensitive function; and provide the sensitive function to a client computing device.

Technologies for privacy-safe security policy evaluation include a cloud analytics server, a trusted data access mediator (TDAM) device, and one or more client devices. The cloud analytics server curries a security policy function to generate a privacy-safe curried function set. The cloud analytics server requests parameter data from the TDAM device, which collects the parameter data, identifies sensitive parameter data, encrypts the sensitive parameter data, and transmits the encrypted sensitive parameter data to the cloud analytics server. The cloud analytics server evaluates one or more curried functions using non-sensitive parameters to generate one or more sensitive functions that each take a sensitive parameter. The cloud analytics server transmits the sensitive functions and the encrypted sensitive parameters to a client computing device, which decrypts the encrypted sensitive parameters and evaluates the sensitive functions with the sensitive parameters to return a security policy. Other embodiments are described and claimed.

Premise-based policies can be applied in the management of mobile devices and other computing devices within a system. A computing device is detected using close proximity wireless communication and location information is sent to the computing device using close proximity wireless communication. Policies applied to the computing device can be based at least in part on the location information.

Growing community of inventors

Portland, OR, United States of America

Sumant Vashisth