Abstract: Disclosed herein are systems and methods for protecting user data. In one aspect, an exemplary method comprises, by a hardware processor, detecting one or more user files, created by a user, that are on a user device; generating user transactional data associated with one or more detected network-based interactions with a service provider by the user, and user behavior data based on one or more user interactions with a graphical user interface of the user device by the user; generating a user classification using a machine learning model that classifies the user based on the one or more user files, the user transactional data, and the user behavior data; and when the user is identifiable based on the user classification, modifying at least one of the one or more user files stored on the user device and user behavior of the user during an operation of the user device.

Abstract: Disclosed herein are systems and methods for continuous user authentication during access of a digital service. In an exemplary aspect, a continuous authentication module may receive, at a computing device, initial authentication credentials of the user. The initial authentication credentials enable access to a service via the computing device. While the service is being accessed, the continuous authentication module may continuously monitor whether an unauthorized user has replaced the user in accessing the service by comparing usage attributes of the service with historic usage attributes associated with the user. In response to determining that the unauthorized user has replaced the user, the continuous authentication module may cease the access to the service via the computing device.

Abstract: Disclosed herein are systems and method for subduing target individuals using unmanned aerial vehicles (UAVs) comprises deploying one or more UAVs to a location of an individual. The method obtains information about the individual from the one or more UAVs and external sources. The method assigns an aggression factor to the individual based on the obtained information. In response to determining that the aggression factor is greater than an aggression threshold, the method prepares a neutralization action designed to reduce the aggression factor of the individual by: identifying one or more exception conditions of the individual, and selecting, from a plurality of neutralization actions that the one or more UAVs are capable of performing, a neutralization action based on the one or more exception conditions. The method then instructs the one or more UAVs to perform the selected neutralization action on the hostile individuals.

Abstract: Disclosed herein are systems and methods for protecting user data. In one aspect, an exemplary method comprises, by a hardware processor, detecting one or more user files modified by a user on a user device; identifying user actions executed by the user to modify the one or more user files; training a machine learning algorithm to identify whether an arbitrary user action is performed by the user, wherein the user actions used by the user to modify the one or more user files are comprised in a training dataset of the machine learning algorithm; detecting a user action to modify a user file; determining, using the machine learning algorithm, whether the user action classifies as being performed by the user; and in response to determining that the machine learning algorithm classifies the user action as being performed by the user, modifying the user action to mask an identity of the user.

Abstract: Methods and systems are provided for modifying configuration of a storage system using artificial intelligence. An exemplary method comprises collecting, over a period of time, health and parameter information of the storage system. The method comprises predicting, using a machine learning algorithm, upcoming events that may degrade performance of the storage system based on the health and parameter information. The method comprises determining that the storage system will not operate in accordance with a set of goals based on the upcoming events. In response to determining that the storage system will not operate in accordance with the set of goals, the method comprises generating parameter changes, and applying the parameter changes to the storage system.

Abstract: Disclosed are systems and methods for proactive disaster recovery. The described technique monitors for events raised by a system of interconnected external sensors and other devices for obtaining data on the external environment of servers. The system uses these events as a chain of triggers according to which preventative or preparatory actions for disaster recovery are performed.

Abstract: Disclosed herein are systems and methods for managing access to data objects in cloud storage. In one aspect, an exemplary method comprises storing, by a processor, a data object in a storage device of a cloud storage service for a duration of time, wherein the data object is accessible to a plurality of user accounts. The method comprises extending the duration of time for retaining the data object on the storage device to a first extended duration when a degree of access of the data object by the plurality of user accounts meets a target threshold value during the duration of time. The method further comprises extending the duration of time for retaining the data object on the storage device to a second extended duration when the degree of access does not meet the target threshold value during the duration of time.

Abstract: Disclosed herein are systems and method for securely providing access to data. In one exemplary aspect, a method may comprise receiving a request to access data on a computing device of a user and identifying a location of the computing device. The method may comprise determining whether access to the data is allowed in the location based on a location-based rule of a plurality of location-based rule. The method may comprise, in response to determining that access to the data is allowed in the location, detecting, via sensors of the computing device, (1) at least one other person different from the user or (2) a surveillance device in the location, and determining whether the at least one other person or the surveillance device can view the data without direct access to the computing device. If not, the method may comprise providing access to the data on the computing device.

Abstract: Disclosed herein are systems and methods for protecting user data. In one aspect, an exemplary method comprises, by a hardware processor, detecting one or more user files modified by a user on a user device; identifying user actions executed by the user to modify the one or more user files; training a machine learning algorithm to identify whether an arbitrary user action is performed by the user, wherein the user actions used by the user to modify the one or more user files are comprised in a training dataset of the machine learning algorithm; detecting a user action to modify a user file; determining, using the machine learning algorithm, whether the user action classifies as being performed by the user; and in response to determining that the machine learning algorithm classifies the user action as being performed by the user, modifying the user action to mask an identity of the user.

Abstract: Disclosed herein are systems and methods for protecting user data. In one aspect, an exemplary method comprises, by a hardware processor, detecting one or more user files, created by a user, that are on a user device; generating user transactional data associated with one or more detected network-based interactions with a service provider by the user, and user behavior data based on one or more user interactions with a graphical user interface of the user device by the user; generating a user classification using a machine learning model that classifies the user based on the one or more user files, the user transactional data, and the user behavior data; and when the user is identifiable based on the user classification, modifying at least one of the one or more user files stored on the user device and user behavior of the user during an operation of the user device.

Abstract: Disclosed herein are systems and methods for protecting user data. In one aspect, an exemplary method comprises, by a hardware processor, detecting user files created by a first user and stored on a user device, the user files containing personal information associated with the first user, generating user transactional data associated with one or more detected network-based interactions with a service provider, generating user behavior data based on one or more user interactions with a graphical user interface of the user device, applying a machine learning model to user data to generate a classification of the first user, the user data comprising the user files, the user transactional data, and the user behavior data, and when the user is identifiable based on the generated classification, modifying at least one of (i) user files stored on the user device and (ii) user behavior during an operation of the user device.

Abstract: Disclosed herein are systems and method for neutralizing hostile individuals using unmanned aerial vehicles (UAVs) comprises deploying one or more UAVs to a location of an individual. The method obtains information about the individual from the one or more UAVs and external sources. The method assigns an aggression factor to the individual based on the obtained information. In response to determining that the aggression factor is greater than an aggression threshold, the method prepares a neutralization action designed to reduce the aggression factor of the individual by: identifying one or more exception conditions of the individual, and selecting, from a plurality of neutralization actions that the one or more UAVs are capable of performing, a neutralization action based on the one or more exception conditions. The method then instructs the one or more UAVs to perform the selected neutralization action on the hostile individuals.

Abstract: Methods and systems are provided for modifying configuration of a storage system using artificial intelligence. An exemplary method comprises collecting, over a period of time, health and parameter information of the storage system. The method comprises predicting, using a machine learning algorithm, upcoming events that may degrade performance of the storage system based on the health and parameter information. The method comprises determining that the storage system will not operate in accordance with a set of goals based on the upcoming events. In response to determining that the storage system will not operate in accordance with the set of goals, the method comprises generating parameter changes, and applying the parameter changes to the storage system.

Abstract: Disclosed herein are systems and method for storing and managing states of a computing device. In one aspect, an exemplary method comprises determining an initial state of the computing device, wherein the initial state includes states of all storage sectors associated with the computing device, storing the determined initial state in an initial blocks storage, for each new state that corresponds to a respective point in time subsequent to a time at which the initial state was determined, creating a snapshot, where the created snapshot includes a difference between the initial state and the new state, for each created snapshot, identifying a set of changed blocks that are in storage, and storing the changed blocks of data to a changed blocks storage, and creating a snap-map for any number of consecutive changes based on the sets of changed blocks corresponding to the respective consecutive changes.

Abstract: Disclosed herein are systems and methods for continuous user authentication during access of a digital service. In an exemplary aspect, a continuous authentication module may receive, at a computing device, initial authentication credentials of the user. The initial authentication credentials enable access to a service via the computing device. While the service is being accessed, the continuous authentication module may continuously monitor whether an unauthorized user has replaced the user in accessing the service by comparing usage attributes of the service with historic usage attributes associated with the user. In response to determining that the unauthorized user has replaced the user, the continuous authentication module may cease the access to the service via the computing device.

Abstract: Methods and systems are provided for modifying configuration of a storage system using artificial intelligence. An exemplary method comprises storing an initial configuration of the storage system as configuration parameters, collecting health information and parameter information related to the storage system over a period of time, analyzing the collected health information using machine learning by comparing the health and the parameter information to a set of goals of the storage system, and in response to determining that the storage system is not operating in accordance with the set of goals, identifying a problem with the storage system using artificial intelligence by analyzing the health information and generating parameter changes that correct the problem, updating the configuration parameters with the parameter changes and applying the parameter changes to the storage system to correct the problem and restore performance of the storage system.

Abstract: Disclosed herein are systems and methods for managing access to data objects in cloud storage. In one aspect, an exemplary method comprises storing, by a processor, a data object in a storage device of a cloud storage service for a duration of time, wherein the data object is accessible to a plurality of user accounts. The method comprises extending the duration of time for retaining the data object on the storage device to a first extended duration when a degree of access of the data object by the plurality of user accounts meets a target threshold value during the duration of time. The method further comprises extending the duration of time for retaining the data object on the storage device to a second extended duration when the degree of access does not meet the target threshold value during the duration of time.

Abstract: Disclosed herein are systems and methods for managing access to data objects in cloud storage. In one aspect, an exemplary method comprises, by a hardware processor, storing a first data object in a cloud storage service, wherein the first data object is uploaded by a first user, modifying a data access policy associated with the first data object to permit access by user accounts other than the first user, determining a utility ranking of the first data object based on a degree of access of the first data object using the cloud storage service, and modifying a data retention policy associated with the first data object based on the determined utility ranking.

Abstract: Disclosed herein are systems and method for storing and managing states of a computing device. In one aspect, an exemplary method comprises determining an initial state of the computing device, wherein the initial state includes states of all storage sectors associated with the computing device, storing the determined initial state in an initial blocks storage, for each new state that corresponds to a respective point in time subsequent to a time at which the initial state was determined, creating a snapshot, where the created snapshot includes a difference between the initial state and the new state, for each created snapshot, identifying a set of changed blocks that are in storage, and storing the changed blocks of data to a changed blocks storage, and creating a snap-map for any number of consecutive changes based on the sets of changed blocks corresponding to the respective consecutive changes.

Abstract: Disclosed are systems and methods for proactive disaster recovery. The described technique monitors for events raised by a system of interconnected external sensors and other devices for obtaining data on the external environment of servers. The system uses these events as a chain of triggers according to which preventative or preparatory actions for disaster recovery are performed.