Abstract: A method of transmitting a data flow over a link aggregation group (LAG), including: comparing the bandwidth demand of the data flow with the capacity of a first link assigned to the flow in the LAG; identifying an underutilized second link in the LAG when the bandwidth demand of the flow is greater than the capacity of the link assigned to the flow resulting in excess packets; determining if the second link is available; determining the traffic type of the traffic flow; calculating a time delay and delaying excess packets of the traffic flow by the calculated time delay when the determined traffic type does not include a packet sequence number; and sending excess packets of the traffic flow on the second link.

Abstract: The disclosed technology relates to a network agent for generating platform specific network policies. A network agent is configured to receive a platform independent network policy from a network policy system, determine implementation characteristics of the network entity, generate platform specific policies from the platform independent network policy based on the implementation characteristics of the network entity, and implement the platform specific policies on the network entity.

Abstract: A multilayer stack is described. The multilayer stack includes: (i) one or more inorganic barrier layers for reducing transport of gas or vapor molecules therethrough; (ii) an inorganic reactive layer disposed adjacent to one or more of the inorganic barrier layers, and the reactive layer capable of reacting with the gas or the vapor molecules; and (iii) wherein, in an operational state of the multilayer stack, the vapor or the gas molecules that diffuse through one or more of the inorganic barrier layers react with the inorganic reactive layer, and thereby allow said multilayer stack to be substantially impervious to the gas or the vapor molecules.

Abstract: A security platform employs a variety techniques and mechanisms to detect security related anomalies and threats in a computer network environment. The security platform is “big data” driven and employs machine learning to perform security analytics. The security platform performs user/entity behavioral analytics (UEBA) to detect the security related anomalies and threats, regardless of whether such anomalies/threats were previously known. The security platform can include both real-time and batch paths/modes for detecting anomalies and threats. By visually presenting analytical results scored with risk ratings and supporting evidence, the security platform enables network security administrators to respond to a detected anomaly or threat, and to take action promptly.

Abstract: A security platform employs a variety techniques and mechanisms to detect security related anomalies and threats in a computer network environment. The security platform is “big data” driven and employs machine learning to perform security analytics. The security platform performs user/entity behavioral analytics (UEBA) to detect the security related anomalies and threats, regardless of whether such anomalies/threats were previously known. The security platform can include both real-time and batch paths/modes for detecting anomalies and threats. By visually presenting analytical results scored with risk ratings and supporting evidence, the security platform enables network security administrators to respond to a detected anomaly or threat, and to take action promptly.

Abstract: A security platform employs a variety techniques and mechanisms to detect security related anomalies and threats in a computer network environment. The security platform is “big data” driven and employs machine learning to perform security analytics. The security platform performs user/entity behavioral analytics (UEBA) to detect the security related anomalies and threats, regardless of whether such anomalies/threats were previously known. The security platform can include both real-time and batch paths/modes for detecting anomalies and threats. By visually presenting analytical results scored with risk ratings and supporting evidence, the security platform enables network security administrators to respond to a detected anomaly or threat, and to take action promptly.

Abstract: A security platform employs a variety techniques and mechanisms to detect security related anomalies and threats in a computer network environment. The security platform is “big data” driven and employs machine learning to perform security analytics. The security platform performs user/entity behavioral analytics (UEBA) to detect the security related anomalies and threats, regardless of whether such anomalies/threats were previously known. The security platform can include both real-time and batch paths/modes for detecting anomalies and threats. By visually presenting analytical results scored with risk ratings and supporting evidence, the security platform enables network security administrators to respond to a detected anomaly or threat, and to take action promptly.

Abstract: A security platform employs a variety techniques and mechanisms to detect security related anomalies and threats in a computer network environment. The security platform is “big data” driven and employs machine learning to perform security analytics. The security platform performs user/entity behavioral analytics (UEBA) to detect the security related anomalies and threats, regardless of whether such anomalies/threats were previously known. The security platform can include both real-time and batch paths/modes for detecting anomalies and threats. By visually presenting analytical results scored with risk ratings and supporting evidence, the security platform enables network security administrators to respond to a detected anomaly or threat, and to take action promptly.

Abstract: An electronic device and a method of displaying one or more items are provided. The electronic device includes a display, and at least one processor configured to control for displaying at least one of a first menu and a second menu on the display, receiving a touch gesture connecting a first point and a second point, wherein the first point is a location corresponding to a first parameter that is one of a plurality of parameters included in the first menu and the second point is a location corresponding to a second parameter that is one of a plurality of parameters included in the second menu related to the first menu, and controlling a first input of selecting the first parameter and a second input of selecting the second parameter to be performed based on the touch gesture.

Abstract: A security platform employs a variety techniques and mechanisms to detect security related anomalies and threats in a computer network environment. The security platform is “big data” driven and employs machine learning to perform security analytics. The security platform performs user/entity behavioral analytics (UEBA) to detect the security related anomalies and threats, regardless of whether such anomalies/threats were previously known. The security platform can include both real-time and batch paths/modes for detecting anomalies and threats. By visually presenting analytical results scored with risk ratings and supporting evidence, the security platform enables network security administrators to respond to a detected anomaly or threat, and to take action promptly.

Abstract: The disclosed technology relates to a distributed policy store. A system is configured to locate, in an index, an entry for a network entity, determine, based on the entry, a file identifier for a file containing a record for the network entity and an offset indicating a location of the record in the file. The system is further configured to locate the file in a distributed file system using the file identifier, locate the record in the file using the offset, and retrieve the record.

Abstract: A security platform employs a variety techniques and mechanisms to detect security related anomalies and threats in a computer network environment. The security platform is “big data” driven and employs machine learning to perform security analytics. The security platform performs user/entity behavioral analytics (UEBA) to detect the security related anomalies and threats, regardless of whether such anomalies/threats were previously known. The security platform can include both real-time and batch paths/modes for detecting anomalies and threats. By visually presenting analytical results scored with risk ratings and supporting evidence, the security platform enables network security administrators to respond to a detected anomaly or threat, and to take action promptly.

Abstract: A multilayer stack is described. The multilayer stack of the present arrangements includes: (i) a polymeric film; (ii) a stress relief layer disposed adjacent to the polymeric film. The stress relief layer includes a matrix and a dispersed phase. The dispersed phase is distributed inside the matrix. The stress relief layer provides stress-relief properties to the polymeric film during expansion and contraction of the polymeric film resulting from being subjected to high and low temperatures, respectively.

Abstract: A security platform employs a variety techniques and mechanisms to detect security related anomalies and threats in a computer network environment. The security platform is “big data” driven and employs machine learning to perform security analytics. The security platform performs user/entity behavioral analytics (UEBA) to detect the security related anomalies and threats, regardless of whether such anomalies/threats were previously known. The security platform can include both real-time and batch paths/modes for detecting anomalies and threats. By visually presenting analytical results scored with risk ratings and supporting evidence, the security platform enables network security administrators to respond to a detected anomaly or threat, and to take action promptly.

Abstract: An image display method is provided. The image display method includes displaying a camera preview screen that provides an image of a subject in real time, capturing one or more images by capturing the camera preview screen, and displaying a photo reel on the camera preview screen, the photo reel being generated by arranging thumbnails of the captured one or more images in a row.

Abstract: A security platform employs a variety techniques and mechanisms to detect security related anomalies and threats in a computer network environment. The security platform is “big data” driven and employs machine learning to perform security analytics. The security platform performs user/entity behavioral analytics (UEBA) to detect the security related anomalies and threats, regardless of whether such anomalies/threats were previously known. The security platform can include both real-time and batch paths/modes for detecting anomalies and threats. By visually presenting analytical results scored with risk ratings and supporting evidence, the security platform enables network security administrators to respond to a detected anomaly or threat, and to take action promptly.

Abstract: An image display method is provided. The image display method includes displaying a camera preview screen that provides an image of a subject in real time, capturing one or more images by capturing the camera preview screen, and displaying a photo reel on the camera preview screen, the photo reel being generated by arranging thumbnails of the captured one or more images in a row.

Abstract: A security platform employs a variety techniques and mechanisms to detect security related anomalies and threats in a computer network environment. The security platform is “big data” driven and employs machine learning to perform security analytics. The security platform performs user/entity behavioral analytics (UEBA) to detect the security related anomalies and threats, regardless of whether such anomalies/threats were previously known. The security platform can include both real-time and batch paths/modes for detecting anomalies and threats. By visually presenting analytical results scored with risk ratings and supporting evidence, the security platform enables network security administrators to respond to a detected anomaly or threat, and to take action promptly.

Abstract: The disclosed technology relates to a network agent for generating platform specific network policies. A network agent is configured to receive a platform independent network policy from a network policy system, determine implementation characteristics of the network entity, generate platform specific policies from the platform independent network policy based on the implementation characteristics of the network entity, and implement the platform specific policies on the network entity.

Abstract: The disclosed technology relates to assigning network agents to communication modules. A network policy system is configured to assign network agents to buckets based on an agent identifier of each agent. The network policy system can assign buckets to communication modules. When a failed communication module is detected, the network policy system can reassigning buckets assigned to the failed communication module to operational communication modules.