Abstract: Disclosed are methods and systems for determining combinations of system parameters that indicate a root cause of a system level experience deterioration (SLED). Some of the disclosed embodiments generate a decision tree from a first class of operational parameter datasets. Rules are derived from the decision tree. Filtered rule sets for feature parameters included in the system parameters are then determined. Pairs of features within a particular dataset that each satisfy their respective filtered rule sets are indicative of a root cause of the degradation, at least in some embodiments.

Abstract: A system that intercepts and analyzes application program interface (API) traffic, identifies correlations between components of API traffic, and uses those correlations to detect anomalous behaviors. API traffic, including requests and responses, is intercepted and analyzed to identify correlations in the API traffic. The correlations may be based on API traffic and can include a sequence of APIs, parameters passed between earlier and subsequent APIs, user roles within a user session and APIs accessed by the user roles, and other correlations. Correlation data for user sessions is generated and stored, and later compared to subsequent user session traffic. If the subsequent user session traffic does not comply with the correlations detected in earlier user sessions, an anomaly may be triggered.

Abstract: Disclosed are methods and systems for determining combinations of system parameters that indicate a root cause of a system level experience deterioration (SLED). Some of the disclosed embodiments generate a decision tree from a first class of operational parameter datasets. Rules are derived from the decision tree. Filtered rule sets for feature parameters included in the system parameters are then determined. Pairs of features within a particular dataset that each satisfy their respective filtered rule sets are indicative of a root cause of the degradation, at least in some embodiments.

Abstract: A computer-implemented method for creating a deception computing system may include (i) identifying, by a computing device, a dataset of security alert signatures from a set of client devices, (ii) determining, by the computing device, a set of software vulnerabilities based on the dataset of security alert signatures, (iii) clustering, by the computing device, the set of software vulnerabilities to increase a length of at least one potential attack path within a predetermined number of honeypot machines, and (iv) distributing, by the computing device and based on clusters of software vulnerabilities, a set of vulnerable software among a set of honeypot machines within a honeynet. Various other methods, systems, and computer-readable media are also disclosed.

Abstract: Knowledge automation techniques may include generating, for each user of a plurality of users, a user vector associated with the user, and grouping the generated user vectors into clusters based on a clustering distance metric between the user vectors. For each cluster, the techniques may include determining a centroid of the cluster, and associating with the cluster at least some of the knowledge elements that the users associated with the cluster has interacted with. The techniques may further include comparing a target user vector of a target user with the centroids of the clusters to determine a matching cluster for the target user, and providing one or more recommendations of the knowledge elements that are associated with the matching cluster to the target user.

Abstract: A method and computing device are provided for performing virtual camera functions during playback of media content. In the method, the computing device selects a region of interest (RoI) during a playback of media content, and represents the RoI as an ensemble of disparate hypotheses. Then the computing device identifies the RoI in a frame sequence sampled according to the hypotheses, performs a virtual camera action on the identified RoI, and plays the RoI with a virtual camera.

Abstract: Knowledge automation techniques may include generating, for each user of a plurality of users, a user vector associated with the user, and grouping the generated user vectors into clusters based on a clustering distance metric between the user vectors. For each cluster, the techniques may include determining a centroid of the cluster, and associating with the cluster at least some of the knowledge elements that the users associated with the cluster has interacted with. The techniques may further include comparing a target user vector of a target user with the centroids of the clusters to determine a matching cluster for the target user, and providing one or more recommendations of the knowledge elements that are associated with the matching cluster to the target user.

Abstract: A method and a system for detecting and monitoring of at least one object in a multimedia content are provided. The method includes extracting at least one contour from the multimedia content using non-textural information in a segmented region within the multimedia content, computing a histogram for the extracted at least one contour in the segmented region of the selected multimedia content to represent an object shape based on the computed histogram, and determining an orientation change of the represented object shape within the segmented region of the multimedia content.

Abstract: Knowledge automation techniques may include receiving a request for determining a representative image for a knowledge unit and determining a set of one or more images associated with the knowledge unit. The techniques may include providing the set of one or more images to a user on a client device and receiving user input indicative of a selection of a first image from the set of one or more images. Based on the first image, a thumbnail image for the knowledge unit can be generated. The techniques may further include associating the thumbnail image with the knowledge unit and displaying the thumbnail image to the user via the client device. In some embodiments, the techniques include generating a thumbnail image for a knowledge pack, wherein the knowledge pack comprises one or more knowledge units.

Abstract: There is provided a system for enabling user control of a live video stream, the system including: a processing module for obtaining offset data for each of a plurality of encoded video segments having a number of different resolutions of the live video stream, the offset data indicative of offsets of video elements in the encoded video segment; a storage medium for storing the encoded video segments and the corresponding offset data; a segment management module for receiving messages from the processing module relating to the availability of the encoded video segments and facilitating streaming of the encoded video segments to the user based on said offset data; and a user interface module for receiving a user request from a user with respect to the live video stream and communicating with the segment management module for streaming the encoded video segments to the user based on the user request.

Abstract: A method and a system for detecting and monitoring of at least one object in a multimedia content are provided. The method includes extracting at least one contour from the multimedia content using non-textural information in a segmented region within the multimedia content, computing a histogram for the extracted at least one contour in the segmented region of the selected multimedia content to represent an object shape based on the computed histogram, and determining an orientation change of the represented object shape within the segmented region of the multimedia content.

Abstract: A method and an electronic device for rendering a selected portion in a video displayed in a higher resolution in a pull-based streaming are provided. The electronic device, when a user selects a portion of the video at a first resolution, identifies display coordinates associated with the video played at the first resolution. The identified display coordinates associated with the video are scaled to a second resolution of a frame of the video. Once the display coordinates are scaled in accordance to the second resolution of the video, the electronic device identifies at least one tile associated with the selected portion in the second resolution. After identifying the tile associated with the selected portion, the electronic device receives a video stream of the selected portion of the video and renders the selected portion on the electronic device.

Abstract: The embodiments described herein provide a method, program and computing network for processing a content request received via a computing network. The method comprises the steps of receiving an incoming request for content from a remote computing device, determining the content type requested by the incoming request and delivering the request to one of a plurality of servers according to the determined content request type.

Abstract: Methods and apparatus are provided for reliably transmitting data. A method comprises identifying a metric for a first frame of a plurality of frames, wherein the metric is indicative of decoding significance for the first frame among the plurality of frames. When the metric corresponds to a relatively high decoding significance, the method further comprises transmitting the first frame in accordance with an enhanced transmission scheme. When the metric corresponds to a relatively low decoding significance, the method further comprises transmitting the first frame in accordance with a default transmission scheme. The reliability of the enhanced transmission scheme is greater than the reliability of the default transmission scheme.

Abstract: A method provides for differentiating usage permissions between different categories of communication traffic within a given network. The method includes ensuring one or more categories of traffic never transits communication radios, link, and/or spectrums dedicated to a different category of traffic. A combined routing metric is calculated using a scaling factor for discouraging usage of restricted communication links and encouraging usage of non-restricted communication links.

Abstract: A method and computing device are provided for performing virtual camera functions during playback of media content. In the method, the computing device selects a region of interest (RoI) during a playback of media content, and represents the RoI as an ensemble of disparate hypotheses. Then the computing device identifies the RoI in a frame sequence sampled according to the hypotheses, performs a virtual camera action on the identified RoI, and plays the RoI with a virtual camera.

Abstract: Data-type-based spanning tree reconfiguration includes determining volumes for one or more types of data transmitted in information flows in an existing spanning tree in a network. The spanning tree is reconfigured based on one or more of the volumes and the types of data transmitted in the flows.

Abstract: A technique for identifying RTP based traffic in routers and switches is disclosed. In one embodiment, a method of identifying RTP based traffic in routers and switches, includes receiving IP packets including a UDP header and a second header located substantially after the UDP header, generating statistical parameters by inspecting predetermined sequence of bits at predetermined offsets in the second header of each received IP packet for a predetermined number of IP packets, and determining whether the IP packet is an RTP based IP packet by comparing the generated statistical parameters to predetermined characteristics. The method also includes pre-filtering the received IP packets to allow only the IP packets comprising the UDP header and the second header to reach an RTP detection engine.

Abstract: A system and method for multicast video streaming over a wireless local area network (WLAN) improves scalability and reliability. The method includes configuring the WLAN access point with a reserved video bandwidth (step 1005). A multicast video stream including data packets marked with differentiated services code points (DSCPs) is then received (step 1010). The multicast video stream is then converted to a plurality of “n” unicast streams (step 1015). Data packets in the unicast streams are then streamed from the WLAN access point to a plurality of “n” mobile units using a selective packet discard algorithm that employs the DSCPs (step 1020).

Abstract: A method provides for differentiating usage permissions between different categories of communication traffic within a given network. The method includes ensuring one or more categories of traffic never transits communication radios, link, and/or spectrums dedicated to a different category of traffic. A combined routing metric is calculated using a scaling factor for discouraging usage of restricted communication links and encouraging usage of non-restricted communication links.