Abstract: The disclosed embodiments provide a system that identifies a user of an electronic device. During a training mode, the system uses an initial training data set, comprising sensor data from electronic devices associated with a set of initial users, to train a multilayer neural network model to authenticate the initial users. Next, the system uses an additional training data set, which includes sensor data from electronic devices associated with one or more new users, to update a portion of the weights in the trained model so that the updated model can be used to authenticate both the initial users and the one or more new users. During a subsequent mode, the system uses the updated model to authenticate a user of the electronic device based on sensor data contemporaneously received from the electronic device.

Abstract: The disclosed embodiments provide a system that authenticates a user of an unattended device. In response to sensing a presence of the user in proximity to the unattended device, the system makes a call from the unattended device to an authentication service to authenticate the user. In response to the call, the authentication service authenticates the user based on recently collected sensor data, which was obtained from one or more sensors in a portable electronic device belonging to the user. If authentication succeeds, the system allows the user to proceed with an interaction with the unattended device.

Abstract: The disclosed embodiments provide a system that identifies a user of an electronic device. During a training mode, the system uses an initial training data set, comprising sensor data from electronic devices associated with a set of initial users, to train a multilayer neural network model to authenticate the initial users. Next, the system uses an additional training data set, which includes sensor data from electronic devices associated with one or more new users, to update a portion of the weights in the trained model so that the updated model can be used to authenticate both the initial users and the one or more new users. During a subsequent surveillance mode, the system uses the updated model to authenticate a user of the electronic device based on sensor data contemporaneously received from the electronic device.

Abstract: The inventors recently developed a system that authenticates and/or identifies a user of an electronic device based on passive factors, which do not require conscious user actions. During operation of the system, in response to a trigger event, the system collects sensor data from one or more sensors in the electronic device, wherein the sensor data includes movement-related sensor data caused by movement of the portable electronic device while the portable electronic device is in control of the user. Next, the system extracts a feature vector from the sensor data, and analyzes the feature vector to authenticate and/or identify the user. During this process, the feature vector is analyzed using a model trained with sensor data previously obtained from the portable electronic device while the user was in control of the portable electronic device.

Abstract: The disclosed embodiments relate to a system that anonymizes sensor data to facilitate machine-learning training operations without disclosing an associated user's identity. During operation, the system receives encrypted sensor data at a gateway server, wherein the encrypted sensor data includes a client identifier corresponding to an associated user or client device. Next, the system moves the encrypted sensor data into a secure enclave. The secure enclave then: decrypts the encrypted sensor data; replaces the client identifier with an anonymized identifier to produce anonymized sensor data; and communicates the anonymized sensor data to a machine-learning system. Finally, the machine-learning system: uses the anonymized sensor data to train a model to perform a recognition operation, and uses the trained model to perform the recognition operation on subsequently received sensor data.

Abstract: The disclosed embodiments provide a system that authenticates a user of an unattended device. In response to sensing a presence of the user in proximity to the unattended device, the system makes a call from the unattended device to an authentication service to authenticate the user. In response to the call, the authentication service authenticates the user based on recently collected sensor data, which was obtained from one or more sensors in a portable electronic device belonging to the user. If authentication succeeds, the system allows the user to proceed with an interaction with the unattended device.

Abstract: The disclosed embodiments relate to a system that anonymizes sensor data to facilitate machine-learning training operations without disclosing an associated user's identity. During operation, the system receives encrypted sensor data at a gateway server, wherein the encrypted sensor data includes a client identifier corresponding to an associated user or client device. Next, the system moves the encrypted sensor data into a secure enclave. The secure enclave then: decrypts the encrypted sensor data; replaces the client identifier with an anonymized identifier to produce anonymized sensor data; and communicates the anonymized sensor data to a machine-learning system. Finally, the machine-learning system: uses the anonymized sensor data to train a model to perform a recognition operation, and uses the trained model to perform the recognition operation on subsequently received sensor data.

Abstract: The inventors recently developed a system that authenticates and/or identifies a user of an electronic device based on passive factors, which do not require conscious user actions. During operation of the system, in response to a trigger event, the system collects sensor data from one or more sensors in the electronic device, wherein the sensor data includes movement-related sensor data caused by movement of the portable electronic device while the portable electronic device is in control of the user. Next, the system extracts a feature vector from the sensor data, and analyzes the feature vector to authenticate and/or identify the user. During this process, the feature vector is analyzed using a model trained with sensor data previously obtained from the portable electronic device while the user was in control of the portable electronic device.

Abstract: Methods, systems, and apparatus, including computer program apparatus, implementing techniques for publishing, subscribing to, or playing live appliances. A live appliance includes a current virtual machine image. In publishing, a proxy file of a live appliance file type is provided to the publisher. The type is mapped to a live appliance player; so that when a proxy file is opened, the current virtual machine image is run. The player automatically binds a writeable file system external to the virtual machine image to the image to provide file storage that is accessible from within the virtual machine image and from a host operating system. The player also creates a subscription to the live appliance on the host computer if one does not exist when the proxy file is run. With the subscription, the player runs the then-current virtual machine image whenever the live appliance is run.

Abstract: The disclosed implementations are related to trace-assisted prefetching of a virtual machine from a network resource to improve interactive performance of the virtual machine on a host device. Trace patterns can be automatically uploaded to a network resource, which aggregates the patterns, and serves the patterns back to the host device, or a different host device, when the host device downloads a virtual machine for the first time.

Abstract: Systems and methods for detecting, installing and uninstalling a virtual machine monitor on a host device is provided. In general, in one aspect, a computer implemented method is provided. The computer implemented method includes initiating a user session on a host device, where the user session is initiated upon the insertion of a peripheral device into the host device. Additionally, a virtual machine monitor and a virtual machine are stored on the peripheral device and the virtual machine monitor is automatically installed on the host device. In some implementations, the virtual machine monitor is automatically uninstalled when the user session is terminated.

Abstract: Methods, systems, and apparatus, including computer program apparatus, implementing techniques for publishing, subscribing to, or playing live appliances. A live appliance includes a current virtual machine image. In publishing, a proxy file of a live appliance file type is provided to the publisher. The type is mapped to a live appliance player; so that when a proxy file is opened, the current virtual machine image is run. The player automatically binds a writeable file system external to the virtual machine image to the image to provide file storage that is accessible from within the virtual machine image and from a host operating system. The player also creates a subscription to the live appliance on the host computer if one does not exist when the proxy file is run. With the subscription, the player runs the then-current virtual machine image whenever the live appliance is run.

Abstract: The disclosed implementations are related to trace-assisted prefetching of a virtual machine from a network resource to improve interactive performance of the virtual machine on a host device. Trace patterns can be automatically uploaded to a network resource, which aggregates the patterns, and serves the patterns back to the host device, or a different host device, when the host device downloads a virtual machine for the first time.

Abstract: The disclosed implementations related to prefetching of virtual machines. Some embodiments can receive a virtual disk including a first page table block corresponding to one or more other page table blocks or one or more data blocks. Next, the embodiments can generate a representation of the first page table block, the representation of the first page table block including presence information with respect to the one or more other page table blocks or the one or more data blocks in the virtual disk that are pointed to by the first page table block. The embodiments can then sign the representation of the first page table block. Next, the embodiments can use the signature and the generated position independent representation to verify the integrity of the first page table block, and/or change the offset of the one or more other page table blocks or the one or more data blocks.