Abstract: Techniques are described for protecting services containing web applications from malicious attacks. A data flow that includes a stack trace and a process is received from a web application. The stack trace is chained with the process to generate a data flow graph. A data lake is then accessed to determine whether the data flow graph is in the data lake. If the data flow graph is not in the data lake, then the data flow can be considered safe. If the data flow graph is not already in the data lake, then a determination is made as to whether the data flow includes a command that accepts user input. If it is determined that the data flow does include a command that accepts user input, then the data flow can be considered to be malicious and the process is terminated to protect the web application from a malicious attack.

Abstract: An example operation may include one or more of detecting, by a blockchain (BC) node, a contract update on a blockchain, determining, by the BC node, at least one charge affected by the contract update, executing, by the BC node, a smart contract to re-generate an invoice based on the at least one charge, and recording the invoice on a ledger of the blockchain.

Abstract: Techniques are disclosed for migrating one or more services from an edge device to a cloud computing environment. In one example, a migration service receives a request to migrate a first set of services from the edge device to the cloud computing environment. The migration service identifies a hardware profile of a computing device (or devices) of the cloud computing environment that matches the edge device, and then configures the computing device to execute a second set of services that corresponds to the first set of services. The migration service establishes a communication channel between the edge device and the computing device, and then executes a set of migration operations such that the second set of services is configured to execute as the first set of services. The computing device may operate in a virtual bootstrap environment or dedicated region of the cloud computing environment.

Abstract: The present invention relates to a system and a method for managing communication between at least one NB-IoT device and an application server. The method comprises continuously receiving, at a mobility management unit, one or more data request from the application server for the at least one NB-IoT device. The mobility management unit transmits a paging request to the at least one NB-IoT device and dynamically monitors a response to the paging request from the at least one NB-IoT device. The mobility management unit continuously buffers the one or more data request based on the dynamic monitoring, and transmits, the one or more buffered data request based on one of an expiry of the paging request and the dynamic monitoring for managing communication between at least one NB-IoT device and the application server.

Abstract: A workflow configuration system for configuring and tracking quality report generation workflows receives via a workflow configuration interface input indicative of selected arrangements of graphical elements within quality report pane(s) of the workflow configuration interface and generates workflow configuration data based on the received input. The workflow configuration data is provided to a quality report generation system, which may be configured to perform report generation operations based on the workflow configuration data. The workflow configuration system presents a workflow status tracking interface and generates status alerts with respect to quality report generation workflows defined in the workflow configuration data based on quality report generation status data (e.g., generated by the quality report generation system) and/or on the quality report workflow configuration data.

Abstract: Provided are systems, methods, and programming for facilitating real-time determination of a process completion likelihood. In some embodiments, data including an update to a system, the update occurring at a first time, wherein updates to the system are permitted until an expiration time may be obtained, a set of fixed descriptors of the system may be retrieved and/or received, and a set of status updates describing the system at prior times may be obtained. Each status update of the set of one or more status updates includes at least (i) an update to the first system and (ii) a time that the respective status update occurred. Based on the data, the fixed descriptors, and the status updates, using a trained machine learning model, a failure/success score indicating a likelihood that, at the expiration time, the system satisfies a threshold condition may be computed and stored in memory.

Abstract: An application programming interface (API) call is received to obtain an access data object that includes a permission of an application provider to access a resource of an entity. A previous permission to access a second resource of the entity is identified. As a result of receiving the API call, an access data object is generated to include the permission and the previous permission.

Abstract: Aspects presented herein may improve an emergency call establishment procedure by enabling a UE to transmit emergency register messages more efficiently. In one aspect, a UE transmits, to a network entity, a request to set up an ePDN. The UE receives, from the network entity, a response to the request comprising a set of multiple P-CSCF addresses. The UE transmits, to the network entity, a registering message to each of the multiple P-CSCF addresses simultaneously. The UE receives, from the network entity, at least one acceptance message from at least one of the set of multiple P-CSCF addresses in response to the registering message. The UE transmits, to the network entity, an invitation message to a P-CSCF address from which an acceptance message is received to establish an emergency call connection.

Abstract: A method can include training a machine learning algorithm to determine a duration of a new work order, based on (a) historical input data for the machine learning algorithm and (b) historical output data for the machine learning algorithm. The method can also include determining one or more work orders for a service provider comprising: determining, by the machine learning algorithm, as trained, one or more durations of the one or more work orders; and determining an optimized service route for the one or more work orders. The method can further include updating a work schedule for the service provider based on the optimized service route. Other embodiments are also provided.

Abstract: A query generation and processing system includes a relational data store, a query generator, and a query processor. The relational data store stores data ingested from data sources in a first and second datasets. The query generator interprets a data expression in a simplified query language to generate a query in a structured query language based on identifying quads corresponding to the first and second datasets in the data expression and determining an implicit join between the quads based on an unambiguous relationship obtainable from a schema of the first and datasets, in which the data expression does not expressly identify a join between the first quad and the second quad. The query processor generates a query pipeline that uses the data of the first and second datasets stored by the relational data store to execute the query generated by the query processor.

Abstract: Techniques and architecture are described for detecting a compromised mailbox as an email account compromise (EAC) involved in lateral phishing, lateral scam, lateral BEC, outbound scam, lateral and inbound fraudulent money transfer requests. For example, the techniques and architecture provide a method that comprises scanning, by a pre-filter, electronic mail messages (emails) within an organization, wherein the emails originate within the organization. The pre-filter analyzes the emails with respect to known fraudulent email practices and determines that an email is a questionable email. A retrospective behavior engine analyzes the questionable email with respect to one or more historical traits to provide a feature set. Based at least in part on the feature set, the verdict correlation engine determines that the questionable email belongs in a class of emails from multiple classes of emails. Based at least in part on the class, the verdict correlation engine performs a responsive action.

Abstract: In order to predict an optimized send time for one or more end users in an email campaign, one or more times in a day are identified for sending the email campaign to the one or more end users. The email campaign may then be transmitted at one of the one or more times identified to the one or more end users.

Abstract: Certain aspects and features of this disclosure relate to semantically-aware image extrapolation. In one example, an input image is segmented to produce an input segmentation map of object instances in the input image. An object generation network is used to generate an extrapolated semantic label map for an extrapolated image. The extrapolated semantic label map includes instances in the original image and instances that will appear in an outpainted region of the extrapolated image. A panoptic label map is derived from coordinates of output instances in the extrapolated image and used to identify partial instances and boundaries. Instance-aware context normalization is used to apply one or more characteristics from the input image to the outpainted region to maintain semantic continuity. The extrapolated image includes the original image and the outpainted region and can be rendered or stored for future use.

Abstract: The present invention relates to new immunogenic compositions comprising conjugated Streptococcus pneumoniae capsular saccharide antigens (glycoconjugates), kits comprising said immunogenic compositions and uses thereof. Immunogenic compositions of the present invention will typically comprise at least one glycoconjugate from a S. pneumoniae serotype not found in PREVNAR®, SYNFLORIX® and/or PREVNAR 13®. The invention also relates to vaccination of human subjects, in particular infants and elderly, against pneumococcal infections using said novel immunogenic compositions.

Abstract: An example system may include a first endpoint executing a remote collector and a second endpoint in communication with the first endpoint. The remote collector may monitor the second endpoint. The remote collector may include an agent installation unit to install a monitoring agent with configuration data on the second endpoint. The configuration data may specify a configuration for the monitoring agent to monitor a first program executing in the second endpoint. Further, the second endpoint may include a buffer limit configuration unit to execute the monitoring agent in a test mode to determine a first number of metrics to be collected in one cycle based on the configuration data. Furthermore, the buffer limit configuration unit may configure a buffer limit of the monitoring agent based on the first number of metrics and, upon configuring the buffer limit, enable the monitoring agent to monitor the first program.

Abstract: An example system may include a first endpoint and a second endpoint executing a remote collector to monitor the first endpoint. The remote collector may include a buffer limit configuration unit to receive a request to install a monitoring agent on the first endpoint. The request may include an operating system type. Further, the buffer limit configuration unit may determine a first predefined buffer limit corresponding to the operating system type. Furthermore, the remote collector may include an installation unit to install the monitoring agent with configuration data on the first endpoint. The configuration data may specify a configuration for the monitoring agent to monitor an operating system executing in the first endpoint and the first predefined buffer limit as a buffer limit for the monitoring agent. Furthermore, the installation unit may enable the monitoring agent to monitor the operating system based on the configuration data with the buffer limit.

Abstract: A system and method for performing tactical segmentation including a supply chain network having a tactical segmentation planner, an inventory system, a transportation network, supply chain entities and a computer.

Abstract: A method, system, and computer program product are configured to create a tuned data record matching model by adjusting values of one or more parameters in a data record matching model based on a second training data set labeled at a data record level, wherein the data record matching model is initially trained using a first training data set labeled at an attribute level.

Abstract: A cellular repeater system is provided. The cellular repeater system includes an outdoor antenna communicatively coupled to a repeater. The outdoor antenna is configured to relay communications from the repeater to a cellular base station. The outdoor antenna includes a plurality of log-periodic antennas rotated relative to one another such that each of the plurality of log-periodic antennas is pointed in a different direction. The cellular repeater system includes a switching device configured to selectively couple one or more of the plurality of log-periodic antennas to a RF transceiver of the repeater in order to configure the outdoor antenna in a plurality of antenna modes. Each of the plurality of antenna modes have a distinct radiation pattern.

Abstract: The present disclosure provides systems and methods for animal health monitoring. Load data can be obtained from an animal monitoring device including three or more load sensors associated with a platform carrying contained litter thereabove, wherein individual load sensors of the three or more load sensors are separated from one another and receive pressure input from the platform independent of one another, wherein the three or more load sensors individually sample loads at from 2.5 Hz to 110 Hz. An animal behavior property associated with the animal can be recognized if it is determined based on load data that the interaction with the contained litter was due to the animal interaction with the contained litter. The animal behavior property can be classified into an animal classified event using a machine learning classifier.