Abstract: A system for detecting synthetic videos may include a server, a plurality of weak classifiers, and a strong classifier. The server may be configured to receive a prediction result from each of a plurality of weak classifiers; and send the prediction results from each of the plurality of weak classifiers to a strong classifier. The weak classifiers may be trained on real videos and known synthetic videos to analyze a distinct characteristic of a video file; detect irregularities of the distinct characteristic; generate a prediction result associated with the distinct characteristic, the prediction result being a prediction on whether the video file is synthetic; and output the prediction result to the server. The strong classifier may be trained to receive the prediction results of the plurality of weak classifiers from the server; analyze the prediction results; and determine if the video file is synthetic based on the prediction results.

Abstract: Systems and methods are provided to generate an attack surface for a protected entity. The method an include receiving identifying information associated with the protected entity; scanning one or more third parties to identify a host associated with the protected entity; determining that the host resolves to a webpage; resolving the webpage; extracting a uniform resource locator (URL) from the resolved webpage; determining, based on at least one rule, that the URL is associated with the protected entity; and generating the attack surface for the protected entity, the attack surface comprising the URL.

Abstract: In some embodiments, an electronic device dynamically assigns functionalities to one or more buttons depending on an orientation associated with the device.

Abstract: A method is performed at a computer system that is in communication with a display generation component and one or more input devices. A first set of one or more windows in an interactive mode, and a representation of a second set of one or more windows in a non-interactive mode are concurrently displayed. While a window is displayed in an interactive mode, the content of the window can be manipulated in response to user inputs. While a representation of a window is displayed in a non-interactive mode, the content of the window is not available to be manipulated in response to user inputs. An input selecting the representation of the second set of one or more windows is detected. In response to detecting the input, the first set of one or more windows in the interactive mode are ceased to be displayed.

Abstract: The disclosed systems and methods provide roaming physical security intelligence.

Abstract: The disclosed systems and methods provide roaming physical security intelligence.

Abstract: In some embodiments, an electronic device dynamically assigns functionalities to one or more buttons depending on an orientation associated with the device.

Abstract: Systems and methods are provided for unified cyberthreat searching.

Abstract: Systems and methods are provided to generate an attack surface for a protected entity. The method an include receiving identifying information associated with the protected entity; scanning one or more third parties to identify a host associated with the protected entity; determining that the host resolves to a webpage; resolving the webpage; extracting a uniform resource locator (URL) from the resolved webpage; determining, based on at least one rule, that the URL is associated with the protected entity; and generating the attack surface for the protected entity, the attack surface comprising the URL.

Abstract: A method for disrupting a detected cyberthreat can include receiving a request, the request identifying suspected malicious content; identifying one or more indicators of compromise (IOCs) associated with the content; enriching the request with the IOCs; verifying the request; and reporting the verified request and the one or more IOCs to a disruption network.

Abstract: In some embodiments, an electronic device dynamically assigns functionalities to one or more buttons depending on an orientation associated with the device.

Abstract: Systems and methods are provided to generate an attack surface for a protected entity. The method an include receiving identifying information associated with the protected entity; scanning one or more third parties to identify a host associated with the protected entity; determining that the host resolves to a webpage; resolving the webpage; extracting a uniform resource locator (URL) from the resolved webpage; determining, based on at least one rule, that the URL is associated with the protected entity; and generating the attack surface for the protected entity, the attack surface comprising the URL.

Abstract: A method for disrupting a detected cyberthreat can include receiving a request, the request identifying suspected malicious content; identifying one or more indicators of compromise (IOCs) associated with the content; enriching the request with the IOCs; verifying the request; and reporting the verified request and the one or more IOCs to a disruption network.

Abstract: A system for detecting synthetic videos may include a server, a plurality of weak classifiers, and a strong classifier. The server may be configured to receive a prediction result from each of a plurality of weak classifiers; and send the prediction results from each of the plurality of weak classifiers to a strong classifier. The weak classifiers may be trained on real videos and known synthetic videos to analyze a distinct characteristic of a video file; detect irregularities of the distinct characteristic; generate a prediction result associated with the distinct characteristic, the prediction result being a prediction on whether the video file is synthetic; and output the prediction result to the server. The strong classifier may be trained to receive the prediction results of the plurality of weak classifiers from the server; analyze the prediction results; and determine if the video file is synthetic based on the prediction results.

Abstract: A system for detecting synthetic videos may include a server, a plurality of weak classifiers, and a strong classifier. The server may be configured to receive a prediction result from each of a plurality of weak classifiers; and send the prediction results from each of the plurality of weak classifiers to a strong classifier. The weak classifiers may be trained on real videos and known synthetic videos to analyze a distinct characteristic of a video file; detect irregularities of the distinct characteristic; generate a prediction result associated with the distinct characteristic, the prediction result being a prediction on whether the video file is synthetic; and output the prediction result to the server. The strong classifier may be trained to receive the prediction results of the plurality of weak classifiers from the server; analyze the prediction results; and determine if the video file is synthetic based on the prediction results.

Abstract: A system for detecting synthetic videos may include a server, a plurality of weak classifiers, and a strong classifier. The server may be configured to receive a prediction result from each of a plurality of weak classifiers; and send the prediction results from each of the plurality of weak classifiers to a strong classifier. The weak classifiers may be trained on real videos and known synthetic videos to analyze a distinct characteristic of a video file; detect irregularities of the distinct characteristic; generate a prediction result associated with the distinct characteristic, the prediction result being a prediction on whether the video file is synthetic; and output the prediction result to the server. The strong classifier may be trained to receive the prediction results of the plurality of weak classifiers from the server; analyze the prediction results; and determine if the video file is synthetic based on the prediction results.

Abstract: A system and method in one embodiment includes modules for identifying an asset with a vulnerability risk, identifying a service running on a port on the asset, identifying a connection to the port, calculating an operational dependence role of the asset as a function of the service and the connection, and modifying the vulnerability risk based on the operational dependence role. Other embodiments include identifying a protocol of a data packet at the port, classifying the protocol into a protocol category with a protocol importance score, calculating a connection average for the asset, classifying the connection average into a connection category with a connection score, and calculating a service dependence score. Other embodiments include calculating a host dependence score, assigning a data importance score to data communicated by the asset, and calculating the operational dependence role as a function of the host dependence score and data importance score.

Abstract: A system and method in one embodiment includes modules for identifying an asset with a vulnerability risk, identifying a service running on a port on the asset, identifying a connection to the port, calculating an operational dependence role of the asset as a function of the service and the connection, and modifying the vulnerability risk based on the operational dependence role. Other embodiments include identifying a protocol of a data packet at the port, classifying the protocol into a protocol category with a protocol importance score, calculating a connection average for the asset, classifying the connection average into a connection category with a connection score, and calculating a service dependence score. Other embodiments include calculating a host dependence score, assigning a data importance score to data communicated by the asset, and calculating the operational dependence role as a function of the host dependence score and data importance score.