Abstract: Embodiments described herein provide a privacy mechanism to protect user data when transmitting the data to a server that estimates a frequency of such data amongst a set of client devices. In one embodiment, a differential privacy mechanism is implemented using a count-mean-sketch technique that can reduce resource requirements required to enable privacy while providing provable guarantees regarding privacy and utility. For instance, the mechanism can provide the ability to tailor utility (e.g. accuracy of estimations) against the resource requirements (e.g. transmission bandwidth and computation complexity).

Abstract: Systems and methods are disclosed for a server learning new words generated by user client devices in a crowdsourced manner while maintaining local differential privacy of client devices. A client device can determine that a word typed on the client device is a new word that is not contained in a dictionary or asset catalog on the client device. New words can be grouped in classifications such as entertainment, health, finance, etc. A differential privacy system on the client device can comprise a privacy budget for each classification of new words. If there is privacy budget available for the classification, then one or more new terms in a classification can be sent to new term learning server, and the privacy budget for the classification reduced. The privacy budget can be periodically replenished.

Abstract: Disclosed are systems, methods, and non-transitory computer-readable storage media for monitoring the current context of a computing device. In some implementations, a context daemon can collect context information about the computing device. The context information can include current device hardware state information. The context information can include current software state information. The context can be derived or implied from a combination of hardware state information, software state information, or any other type of state information. For example, the derived context can be a user state (e.g., a user activity, sleeping, running, etc.) derived from or implied by hardware or software state information.

Abstract: Systems and methods are disclosed for generating term frequencies of known terms based on crowdsourced differentially private sketches of the known terms. An asset catalog can be updated with new frequency counts for known terms based on the crowdsourced differentially private sketches. Known terms can have a classification. A client device can maintain a privacy budget for each classification of known terms. Classifications can include emojis, deep links, locations, finance terms, and health terms, etc. A privacy budget ensures that a client does not transmit too much information to a term frequency server, thereby compromising the privacy of the client device.

Abstract: Systems and methods are disclosed for a server learning new words generated by user client devices in a crowdsourced manner while maintaining local differential privacy of client devices. A client device can determine that a word typed on the client device is a new word that is not contained in a dictionary or asset catalog on the client device. New words can be grouped in classifications such as entertainment, health, finance, etc. A differential privacy system on the client device can comprise a privacy budget for each classification of new words. If there is privacy budget available for the classification, then one or more new terms in a classification can be sent to new term learning server, and the privacy budget for the classification reduced. The privacy budget can be periodically replenished.

Abstract: The system described may implement a 1-bit protocol for differential privacy for a set of client devices that transmit information to a server. Implementations of the system may leverage specialized instruction sets or engines built into the hardware or firmware of a client device to improve the efficiency of the protocol. For example, a client device may utilize these cryptographic functions to randomize information sent to the server. In one embodiment, the client device may use cryptographic functions such as hashes including SHA or block ciphers including AES. Accordingly, the system provides an efficient mechanism for implementing differential privacy.

Abstract: Systems and methods are disclosed for generating term frequencies of known terms based on crowdsourced differentially private sketches of the known terms. An asset catalog can be updated with new frequency counts for known terms based on the crowdsourced differentially private sketches. Known terms can have a classification. A client device can maintain a privacy budget for each classification of known terms. Classifications can include emojis, deep links, locations, finance terms, and health terms, etc. A privacy budget ensures that a client does not transmit too much information to a term frequency server, thereby compromising the privacy of the client device.

Abstract: Systems and methods are disclosed for generating term frequencies of known terms based on crowdsourced differentially private sketches of the known terms. An asset catalog can be updated with new frequency counts for known terms based on the crowdsourced differentially private sketches. Known terms can have a classification. A client device can maintain a privacy budget for each classification of known terms. Classifications can include emojis, deep links, locations, finance terms, and health terms, etc. A privacy budget ensures that a client does not transmit too much information to a term frequency server, thereby compromising the privacy of the client device.

Abstract: In some implementations, a mobile device can be configured to monitor environmental, system and user events associated with the mobile device and/or a peer device. The occurrence of one or more events can trigger adjustments to system settings. The mobile device can be configured to keep frequently invoked applications up to date based on a forecast of predicted invocations by the user. In some implementations, the mobile device can receive push notifications associated with applications that indicate that new content is available for the applications to download. The mobile device can launch the applications associated with the push notifications in the background and download the new content. In some implementations, before running an application or communicating with a peer device, the mobile device can be configured to check energy and data budgets and environmental conditions of the mobile device and/or a peer device to ensure a high quality user experience.

Abstract: Systems and methods are disclosed for generating term frequencies of known terms based on crowdsourced differentially private sketches of the known terms. An asset catalog can be updated with new frequency counts for known terms based on the crowdsourced differentially private sketches. Known terms can have a classification. A client device can maintain a privacy budget for each classification of known terms. Classifications can include emojis, deep links, locations, finance terms, and health terms, etc. A privacy budget ensures that a client does not transmit too much information to a term frequency server, thereby compromising the privacy of the client device.

Abstract: Systems and methods are disclosed for generating term frequencies of known terms based on crowdsourced differentially private sketches of the known terms. An asset catalog can be updated with new frequency counts for known terms based on the crowdsourced differentially private sketches. Known terms can have a classification. A client device can maintain a privacy budget for each classification of known terms. Classifications can include emojis, deep links, locations, finance terms, and health terms, etc. A privacy budget ensures that a client does not transmit too much information to a term frequency server, thereby compromising the privacy of the client device.

Abstract: Systems and methods are disclosed for a server learning new words generated by user client devices in a crowdsourced manner while maintaining local differential privacy of client devices. A client device can determine that a word typed on the client device is a new word that is not contained in a dictionary or asset catalog on the client device. New words can be grouped in classifications such as entertainment, health, finance, etc. A differential privacy system on the client device can comprise a privacy budget for each classification of new words. If there is privacy budget available for the classification, then one or more new terms in a classification can be sent to new term learning server, and the privacy budget for the classification reduced. The privacy budget can be periodically replenished.

Abstract: Systems and methods are disclosed for a server learning new words generated by user client devices in a crowdsourced manner while maintaining local differential privacy of client devices. A client device can determine that a word typed on the client device is a new word that is not contained in a dictionary or asset catalog on the client device. New words can be grouped in classifications such as entertainment, health, finance, etc. A differential privacy system on the client device can comprise a privacy budget for each classification of new words. If there is privacy budget available for the classification, then one or more new terms in a classification can be sent to new term learning server, and the privacy budget for the classification reduced. The privacy budget can be periodically replenished.

Abstract: Disclosed are systems, methods, and non-transitory computer-readable storage media for monitoring the current context of a computing device. In some implementations, a context daemon can collect context information about the computing device. The context information can include current device hardware state information. The context information can include current software state information. The context can be derived or implied from a combination of hardware state information, software state information, or any other type of state information. For example, the derived context can be a user state (e.g., a user activity, sleeping, running, etc.) derived from or implied by hardware or software state information.

Abstract: Disclosed are systems, methods, and non-transitory computer-readable storage media for notifying context clients of changes to the current context of a computing device. In some implementations, a context client can register to be called back when the context daemon detects specified context. For example, the context client can specify a context in which the context client is interested. When the context daemon detects that the current context of the computing device corresponds to the registered context, the context daemon can notify the context client that the current context matches the context in which the context client is interested. Thus, context clients do not require the programming necessary to independently obtain context updates and detect changes in context that are relevant or of interest to the context client.

Abstract: Disclosed are systems, methods, and non-transitory computer-readable storage media for efficiently monitoring the operating context of a computing device. In some implementations, the context daemon and/or the context client can be terminated to conserve system resources. For example, if the context daemon and/or the context client are idle, they can be shutdown to conserve battery power or free other system resources (e.g., memory). When an event occurs (e.g., a change in current context) that requires the context daemon and/or the context client to be running, the context daemon and/or the context client can be restarted to handle the event. Thus, system resources can be conserved while still providing relevant context information collection and callback notification features.

Abstract: In some implementations, a mobile device can be configured to monitor environmental, system and user events associated with the mobile device and/or a peer device. The occurrence of one or more events can trigger adjustments to system settings. The mobile device can be configured to keep frequently invoked applications up to date based on a forecast of predicted invocations by the user. In some implementations, the mobile device can receive push notifications associated with applications that indicate that new content is available for the applications to download. The mobile device can launch the applications associated with the push notifications in the background and download the new content. In some implementations, before running an application or communicating with a peer device, the mobile device can be configured to check energy and data budgets and environmental conditions of the mobile device and/or a peer device to ensure a high quality user experience.

Abstract: In some implementations, a mobile device can be configured to monitor environmental, system and user events associated with the mobile device and/or a peer device. The occurrence of one or more events can trigger adjustments to system settings. The mobile device can be configured to keep frequently invoked applications up to date based on a forecast of predicted invocations by the user. In some implementations, the mobile device can receive push notifications associated with applications that indicate that new content is available for the applications to download. The mobile device can launch the applications associated with the push notifications in the background and download the new content. In some implementations, before running an application or communicating with a peer device, the mobile device can be configured to check energy and data budgets and environmental conditions of the mobile device and/or a peer device to ensure a high quality user experience.

Abstract: In some implementations, a mobile device can be configured to monitor environmental, system and user events associated with the mobile device and/or a peer device. The occurrence of one or more events can trigger adjustments to system settings. The mobile device can be configured to keep frequently invoked applications up to date based on a forecast of predicted invocations by the user. In some implementations, the mobile device can receive push notifications associated with applications that indicate that new content is available for the applications to download. The mobile device can launch the applications associated with the push notifications in the background and download the new content. In some implementations, before running an application or communicating with a peer device, the mobile device can be configured to check energy and data budgets and environmental conditions of the mobile device and/or a peer device to ensure a high quality user experience.

Abstract: Disclosed are systems, methods, and non-transitory computer-readable storage media for tracking and managing resource usage through a ledger feature that can trigger complex real-time reactions. The resource tracking can be managed through a ledger module and a ledger data structure. The ledger data structure can be updated each time a task requests a resource. Additionally, as part of the update, the ledger module can verify whether a resource has been over consumed. In response to the detection of an over consumption, the ledger module can set a flag. At some later pointer when the thread is in a stable, well-understood point, the ledger module can check if the flag has been set. If the flag has been set, the ledger module can call the appropriate callback function, which can react to the over consumption in a resource specific manner.