Abstract: A method and system for health rank based virtual machine restoration using a conformal framework. With respect to enterprise data protection, solutions need to address two primary responsibilities: at the onset of failure or disaster, restore any running applications, as well as any lost or damaged data; and minimize (if not eliminate) the future occurrence of such failures or disasters. In tackling the latter responsibility, the disclosed method and system leverage health-score assessments to ensure the restoration of virtual machines onto healthy infrastructure. The aforementioned health-score assessments employ clustering to identify, and a conformal framework to rank, healthy hosts onto which virtual machines may be restored.

Abstract: A method and system for risk score based asset data protection using a conformal framework. Concerning Internet-of-Things (IoT) environments, there is a growing challenge to ensure the availability and continuity of applications executing, as well as relevant application data maintained, on IoT devices, in order to mitigate potential operational failures and/or interruptions. The disclosed method and system address this growing challenge through risk-score assessments of the applications and their respective relevant application data (collectively referred to as assets), as well as the potential degradation of the underlying IoT device hardware. The aforementioned risk-score assessments employ clustering to identify, and a conformal framework to rank, high-risk (for failure) assets, which may subsequently be subjected to backup operations (overriding existing policies) to guarantee asset protection.

Abstract: A method and system for risk score based asset data protection using a conformal framework. Concerning Internet-of-Things (IoT) environments, there is a growing challenge to ensure the availability and continuity of applications executing, as well as relevant application data maintained, on IoT devices, in order to mitigate potential operational failures and/or interruptions. The disclosed method and system address this growing challenge through risk-score assessments of the applications and their respective relevant application data (collectively referred to as assets), as well as the potential degradation of the underlying IoT device hardware. The aforementioned risk-score assessments employ clustering to identify, and a conformal framework to rank, high-risk (for failure) assets, which may subsequently be subjected to backup operations (overriding existing policies) to guarantee asset protection.

Abstract: A method and system for health rank based virtual machine restoration using a conformal framework. With respect to enterprise data protection, solutions need to address two primary responsibilities: at the onset of failure or disaster, restore any running applications, as well as any lost or damaged data; and minimize (if not eliminate) the future occurrence of such failures or disasters. In tackling the latter responsibility, the disclosed method and system leverage health-score assessments to ensure the restoration of virtual machines onto healthy infrastructure. The aforementioned health-score assessments employ clustering to identify, and a conformal framework to rank, healthy hosts onto which virtual machines may be restored.

Abstract: Method to provide data protection through light fidelity network is disclosed herein. Method starts with a data protection server (DPS) that is enabled with light fidelity (Li-Fi) receiving a backup request from a first client device through a Li-Fi network. The first client device is enabled with Li-Fi. DPS registers the first client device through the Li-Fi network and triggers to start the backup of the first client device to a storage included in DPS. DPS receives a registration request from a proxy server for the DPS via a network, and registers the proxy server. DPS receives via the proxy server a backup request from a second client device for backup to the DPS. The second client device and the proxy server are enabled with Li-Fi DPS triggers to start the backup of the second client device to the storage included in the DPS. Other embodiments are described.

Abstract: Image backup using a trained image classifier is disclosed. In various embodiments, an image classifier is applied to a plurality of images to identify one or more images to be included in a save set of images. The save set of images are selectively stored to a second location according to one or more policies.

Abstract: Systems and methods for remotely operating a data protection server are described. The data protection server is configured to perform predefined data protection operations for computing assets of an enterprise network. An email agent is installed on the data protection system to receive a specially-coded email message from an authorized user, where the specially-coded message includes an instruction for performing a predefined data protection operation. Upon receiving the email message and parsing it to extract the instruction, the data protection system initiates execution of the instruction.

Abstract: Image backup using a trained image classifier is disclosed. In various embodiments, an image classifier is applied to a plurality of images to identify one or more images to be included in a save set of images. The save set of images are selectively stored to a second location according to one or more policies.

Abstract: Image backup using a trained image classifier is disclosed. In various embodiments, an image classifier is applied to a plurality of images to identify one or more images to be included in a save set of images. The save set of images are selectively stored to a second location according to one or more policies.