Abstract: Various techniques for detecting a persistent cross-site scripting vulnerability are described herein. In one example, a method includes detecting, via the processor, a read operation executed on a resource using an instrumentation mechanism and returning, via the processor, a malicious script in response to the read operation. The method also includes detecting, via the processor, a write operation executed on the resource using the instrumentation mechanism and detecting, via the processor, a script operation executed by the malicious script that results in resource data being sent to an external computing device from a client device. Furthermore, the method includes receiving, via the processor, metadata indicating the execution of the read operation, the write operation, and the script operation.

Abstract: The present disclosure relates to system(s) and method(s) for deploying a java agent in runtime. The method creates a .WAR file associated with a java agent. The .WAR file corresponds to a servlet configured to run the java agent. The method further determines an existence of a reference holder class in a bootstrap class loader using the servlet. Based on the determination of the reference holder class, the method connects the servlet to a Java Virtual Machine (JVM). The servlet is connected to the JVM using an open source library. Further, the method deploys the java agent in real-time based on a deployment of a bootstrap class using the servlet. The bootstrap class holds a reference to the java agent. The bootstrap class acts as the reference holder class.

Abstract: The present disclosure discloses system and method for facilitating avoiding of human errors in human error detection environment. At first, a plurality of configurations corresponding to a plurality of machines may be received. Further, a plurality of scripts may be configured corresponding to the plurality of machines based on the plurality of configurations. Further, a script, of the plurality of scripts, may be executed on a machine, of the plurality of machines. Based on the executing of the script, a message and a graphical user interface (GUI) may be displayed on the machines. Further, the message and the GUI may be customized based on the configuration of the machine. Further, the customized message and the GUI guide the user interacting with the machine to avoid the human errors.

Abstract: An embodiment of the invention may include a method, computer program product, and system for detecting email messages sent from an automated mailing system. The embodiment may include analyzing email metadata of a user to detect an indication of automation. The embodiment may include identifying any email messages sent corresponding to the pattern of automation. The embodiment may include performing an action in response to the identified email messages.

Abstract: Disclosed is a system for profiling one or more nodes based on a hybrid Key Performance Indicator (KPI). Initially, a flag indicating an issue with a KPI is received. A set of Performance Management (PM) counters undergoing periodic changes in performance beyond a predefined threshold by using machine learning based statistical techniques is identified. The set of PM counters may comprise a set event based of PM counters and a set of protocol based PM counters. A hybrid KPI is created based on combination of the set event based of PM counters and the set of protocol based PM counters. One or more nodes are profiled by comparing the hybrid KPI associated to the node with hybrid KPI corresponding to each of the one or more nodes.

Abstract: The present disclosure relates to system(s) and method(s) for deploying a data analytics model in a target environment. The system records a set of data pre-processing stages, associated with the data analytics model. The set of data pre-processing stages may comprise receiving raw data, executing a set of ETL functions on the raw data, and executing a set of algorithms on the raw data. Further, the system generates the data analytics model based on the set of algorithms. Furthermore, the system generates a scoring engine workflow, associated with the data analytics model, based on the set of data pre-processing stages. The scoring engine workflow comprises one or more ETL functions and one or more algorithms. Further, the system deploys the data analytics model and the scoring engine workflow in the target environment. The scoring engine workflow enables pre-processing of production data in the target environment.

Abstract: The present disclosure relates to system(s) and method(s) for verifying data loading requirements of an avionics unit. The system receives a request for data loading. The request comprises file data, and data loading requirements associated with the avionics unit. Further, the system obtains target file from a repository based on an analysis of the request. The system further generates valid data set and invalid data set in the target file based on an analysis of the data loading requirements. Upon generation, the system verifies predefined data loading requirements of the avionics unit using the invalid data set from the target file.

Abstract: Disclosed is an antenna for enhancing link coupling efficiency in a power transmission. The antenna may comprise a plurality of coil windings layered across each other. It may be noted that each coil winding may be deployed with a plurality of edges. It may be understood that an edge is separated with another edge at a predetermined distance on each coil winding. It may be noted that the edge and the another edge is a subset of the plurality of edges.

Abstract: Methods, computer program products, and systems are presented. The method computer program products, and systems can include, for instance: generating a first mobile device fingerprint of a mobile device and associating the first mobile device fingerprint to an identifier, and generating a second mobile device fingerprint of the mobile device and associating the second mobile device fingerprint to a MAC address of a mobile device. The methods, computer program products, and systems can include, for instance: receiving a first mobile device fingerprint of a mobile device and an identifier associated to the first mobile device fingerprint; receiving a second mobile device fingerprint of the mobile device and a MAC address associated to the second mobile device fingerprint; and associating received data received from the mobile device to the identifier.

Abstract: Disclosed is a system and method for automatically diagnosing an error by performing failure analysis of functional simulation pertaining to a Design Under Verification (DUV) or System Under Verification (SUV). A prediction unit generates a set of expected output packets upon processing a set of input packets' copy. A comparison unit compares an actual output packet, from the set of actual output packets, with an expected output packet, from the set of expected output packets, corresponding to the actual output packet. When there is a mismatch, the actual output packet is compared with at least one subsequent expected output packet until the match is found. The diagnosing unit automatically diagnoses at least one of a packet drop error, an ordering error, an error in routing, by performing a systematic failure analysis and reports a diagnostic information and/or default diagnostic information associated with the error.

Abstract: Disclosed is a system for performing User Interface (UI) verification of a Device Under Test (DUT). Before performing the UI verification, a set of corner markers is positioned at corners of a display frame associated to the DUT. Once the set of corner markers are positioned, an image receiving module receives a DUT image, captured by an image capturing unit, of the UI pertaining to a DUT. A skew correction module for correcting orientation of the DUT image by determining an orientation correction factor. A file configuration module for storing the orientation correction factor in a pre-configuration file when the DUT image is occupying the content greater than the predefined threshold percentage. In one aspect, the orientation correction factor may be referred while testing a UI of the DUT.

Abstract: Disclosed is a system to perform parallel processing on a distributed dataset. A receiving module, for receiving a dataset along with a set of functions. A partitioning module, for partitioning the dataset into a set of distributed datasets. A distributing module, for distributing the set of distributed datasets amongst a set of computing nodes. A determining module, for determining an applicability of the function on the distributed dataset. An executing module, for executing one or more functions applicable on the distributed dataset. A generating module, for generating processed data for the distributed dataset based upon the executing of the one or more functions.

Abstract: Disclosed is a system for allowing secure access to a microservice. An Application Programming Interface (API) gateway receives a request comprising a Uniform Resource Locator (URL) associated to the microservice. A set of input parameters indicating information about the user device and the microservice is identified from the URL. The system performs validation of input parameters, extraction of request patterns, tracking of IP address, and detection of user credentials to provide output parameters. A decision tree comprising rules is generated by using a supervised machine learning technique on the output parameters. Further, the API gateway creates a stateless identity token to encrypt the request. The stateless identity token is created based on the user credentials and at least one rule applicable to the request. Once the stateless identity token is created, the stateless identity token is verified to allow the secure access to the microservice.

Abstract: The present disclosure relates to system(s) and method(s) for storing sensor data received from a device connected an Internet of Things (IoT) network. The system may store one or more record tables corresponding to one or more devices connected in an Internet of Things (IoT) network, in a database. Further, the system may receive a modification request from a device connected in the Internet of Things (IoT) network, wherein the modification request comprises a unique identification number corresponding to the device and a sensor configuration data. Further, the system may modify a table structure of a record table corresponding to the device to generate a modified table structure, based on the modification request. Further, the system may execute a programmed instruction stored in the memory to store the sensor data received from the device, in the record table, based on the modified table structure.

Abstract: The present disclosure relates to system(s) and method(s) for generating a functional simulation's progress report simultaneously when the simulation is in progress. The system comprises a testbench and a DUV/SUV connected to the testbench. The testbench generates a set of input data/packets in order to simulate and verify the DUV/SUV. The system is configured to identify one or more components, from a set of components in the testbench. Furthermore, the system receives one or more current progress messages from the one or more components and identifies one or more component Lock-Up conditions based on the processing of the one or more current progress messages and one or more previous progress messages. Further, the system executes one or more actions to resolve the one or more component Lock-Up conditions. Furthermore, the system generates a simulation progress report, simultaneously at runtime, during the simulation.

Abstract: Disclosed is a system for profiling one or more nodes based on a hybrid Key Performance Indicator (KPI). Initially, a flag indicating an issue with a KPI is received. A set of Configuration Management (CM) may be changed or identified by SME. Deviation in magnitude of each CM parameters from a predefined CM magnitude is computed to determine a changed CM parameter with deviation magnitude higher than deviation magnitude of remaining CM parameters. A set of Performance Management (PM) counters is identified by comparing magnitude of each PM with a predefined threshold value or using machine learning or statistical techniques. A hybrid KPI is created based on combination of the changed CM parameters and a subset of PM counters. One or more nodes are profiled by comparing the hybrid KPI associated to the node with hybrid KPI corresponding to each of the one or more nodes.

Abstract: Disclosed is a method and system for enabling immersive viewing of a multimedia. The method may comprise receiving multimedia from one or more source devices, a user data associated with a user wearing an eyewear, a display device data associated with a display device, and an alignment data. The eyewear may comprise a regular glass and a smart glass, and the display device data may comprise dimensions of the display device. The method may further comprise dividing the multimedia in to a primary multimedia and a secondary multimedia based on one or more of the user data, the display device data, and the alignment data. The method may furthermore comprise transmitting the primary multimedia to the display device for display on the display device and transmitting the secondary multimedia to the eyewear for display on the smart glass, thereby enabling immersive viewing of a multimedia.

Abstract: Disclosed is a reconfigurable convolution engine for performing a convolution operation on an image. A data receiving module receives image data. A determination module determines a kernel size based on the image data, clock speed associated to the convolution engine and number of available on-chip resources. An allocation module allocates a plurality of instances based on the kernel size. Each instance of the plurality of instances further comprises a set of computing blocks operating concurrently. Each computing block is configured to perform convolution operation on the feature map of the image. An aggregation module aggregates the convolution output of each computing block for each instance of the plurality of instances to produce a convolution result for the image.

Abstract: Disclosed is a convolution operator system for performing a convolution operation concurrently on an image. An input router receives image data. A controller allocates image data to a set of computing blocks based on the size of the image data and number of available computing blocks. Each computing block produces a convolution output corresponding to each row of the image. The controller allocates a plurality of group having one or more computing blocks to generate a set of convolution output. Further, a pipeline adder aggregates the set of convolution output to produce an aggregated convolution output. An output router transmits either the convolution output or the aggregated convolution output for performing subsequent convolution operation to generate a convolution result for the image data.

Abstract: A Convolution Multiply and Accumulate (CMAC) system for performing a convolution operation is disclosed. The CMAC system receives image data pertaining to an image. The image data comprises a set of feature matrix, a kernel size and depth information. Further, the CMAC system generates a convoluted data based on convolution operation for each feature matrix. The CMAC system performs an accumulation of the convoluted data to generate accumulated data, when the convolution operation for each feature matrix is performed. The CMAC system further performs an addition of a predefined value to the accumulated data to generate added data. Further, the CMAC system filters the added data to provide a convolution result for the image, thereby performing the convolution operation of the image.