Abstract: 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.

Abstract: 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.

Abstract: Technologies for privacy-safe security policy evaluation are disclosed herein.

Abstract: Technologies for privacy-safe security policy evaluation are disclosed herein.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: A tracking station detects a mobile data processing system (DPS) within communication range of a short range wireless module of the tracking station. In response to detecting the mobile DPS, the tracking station obtains identification data for the mobile DPS from a security module of the mobile DPS. The tracking station uses the identification data to obtain credentials to access secure storage on the mobile DPS. The tracking station automatically generates security configuration data for the mobile DPS, based on multiple factors pertaining to the mobile DPS, such as identity of the mobile DPS, a location of the mobile DPS, capabilities of the mobile DPS, etc. The tracking station uses the credentials to write the security configuration data to the secure storage of the mobile DPS. The security configuration data calls for the mobile DPS to automatically disable or enable at least one component. Other embodiments are described and claimed.