Abstract: The invention relates to method and system for enhancing computer network security. The method includes receiving a plurality of requests from client devices to avail a plurality of responses from services running on servers; determining a URL pattern for each of the plurality of requests based on URL associated with that request; determining a request data signature for each of the plurality of requests or a response data signature for each of the plurality of responses based on a set of request parameters associated with that request or based on a set of response parameters associated with that response, respectively, using a first machine learning model; and determining an authenticity of each of the plurality of requests based on the URL pattern and the data signature associated with that request, or an authenticity of each of the plurality of responses based on the data signature associated with that response.

Abstract: This disclosure relates to method and system for identifying Personally Identifiable Information (PII) through secret patterns. The method includes receiving user data from at least one data source through a plurality of communication channels. The user data includes PII and non-PII. The user data is associated with a user. The PII includes a plurality of personal identifiers. The method further includes identifying the PII in user data through a predictive model. The method further includes generating a secret pattern based on the PII identified through the predictive model. The secret pattern is an identifiable label. The method further includes adding the secret pattern to each of the plurality of personal identifiers in PII. The method further includes identifying each of the plurality of personal identifiers through the secret pattern in real-time, when user data is transmitted from the at least one data source to at least one data destination.

Abstract: The present disclosure relates to a system and method for controlling data interception in a communication network. One or more requests from a user for accessing one or more microservices are received through an Application Programming Interface (API). Information associated with one or more requests is the detected and requests are classified as secured microservice request and non-secured microservice request. The information is detected through predefined rules. Authentication token is then issued for secured microservice based on the detecting. The authentication token stores information detected by the detector in a geo storage system. The one or more requests are then routed according to the authentication token towards one or more corresponding microservices of the one or more microservices.

Abstract: The invention relates to method and system for enhancing computer network security. The method includes receiving a plurality of requests from client devices to avail a plurality of responses from services running on servers; determining a URL pattern for each of the plurality of requests based on URL associated with that request; determining a request data signature for each of the plurality of requests or a response data signature for each of the plurality of responses based on a set of request parameters associated with that request or based on a set of response parameters associated with that response, respectively, using a first machine learning model; and determining an authenticity of each of the plurality of requests based on the URL pattern and the data signature associated with that request, or an authenticity of each of the plurality of responses based on the data signature associated with that response.

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 a system and method for controlling data interception in a communication network. One or more requests from a user for accessing one or more microservices are received through an Application Programming Interface (API). Information associated with one or more requests is the detected and requests are classified as secured microservice request and non-secured microservice request. The information is detected through predefined rules. Authentication token is then issued for secured microservice based on the detecting. The authentication token stores information detected by the detector in a geo storage system. The one or more requests are then routed according to the authentication token towards one or more corresponding microservices of the one or more microservices.

Abstract: Disclosed is a system for delegating access of sensitive information by a user device to a requestor device through a central server. A receiving module receives a first token Identification (ID) generated by the user device in an offline mode and a request, comprising a second token ID, from the requestor device. A validation module validates the request by comparing the first token ID and the second token ID. An identification module identifies a subset of the sensitive information based on a profile of the requestor, when the first token ID is matched with the second token ID. A watermarking module watermarks the subset of the sensitive information with a set of variables to generate watermarked sensitive information. Upon generating the watermarked sensitive information, the access delegation module delegates the access of the watermarked sensitive information to the requestor device.

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: System and method for generating professional profile of an employee in an organization are disclosed. An organizational ontology may be built for the employee. The organizational ontology may be indicative of interrelationships between the employee, other employees and tasks performed by the employee. Further, email data associated with the employee may be stored for a complete lifecycle of the employee. The email data may be analyzed to identify insights about the employee and the professional profile may be generated based on the identified insights.

Abstract: Disclosed is a system for debugging the network environment under regression testing. Initially, a data receiving module receives data pertaining to the network environment. An extraction module extracts a plurality of features by using a parser. An identification module identifies an error as a Problem Report (PR) or a False Failure (FF) based on classification of a test case execution log and a similarity confidence. The test case execution log may be classified based on comparison of a predefined pattern with an error pattern of the test case execution log. A generation module may generate second test case based on the plurality of features, a predefined set of instructions and the error pattern associated with the test case execution log by using a K-means and a Nearest Neighbour algorithm. A debugging module debugs the network environment based on execution of a test case.

Abstract: The system and method for secure sharing of a source code is disclosed. The method comprises. The method comprises receiving a source code associated with an application, and a defect identification number associated with a defective feature in the application. The method comprises identifying a defective feature of an application and non-defective features of the application based on a defect investigation methodology. The method comprises generating a checkout ID associated with the application and further generates a secured second set of source code based on one of an encryption methodology and an obfuscating methodology. The method further comprises providing a secured source code to a third party for debugging the defective feature in the application.

Abstract: The present disclosure relates to system(s) and method(s) for assisting a user in application development lifecycle. The system is configured to receive a new use case from a user device and identify a sub-set of development solutions from a set of development solutions, stored in a historical data repository, that are applicable for developing code corresponding to the new use case. Furthermore, the system is configured to receive a set test cases corresponding to each development solution from the historical data repository. Furthermore, the system is configured to generate a problem report and a false failure report based on analysis of the set of test cases. The system is further configured to rank the sub-set of development solutions based on analysis of the problem report and the false failure report. Further, the system is configured to generate a decision template based on the ranking of the sub-set of development solutions.

Abstract: The present disclosure relates to a record and replay system(s) and method(s) for automating one or more activities with self-learning, the method comprises obtaining data from one or more data source systems and identifying an intent associated with the data based on classification of the data in to one or more domain using a clustering and classification methodology. The method further comprises extracting one or more parameters from the data and a parameters databased based on the intent using a named entity recognition extractor and identifying the activity to be performed based on the one or more parameters and the intent. The method furthermore comprises executing the activity using the one or more parameter, thereby automating execution of one or more activities.

Abstract: Disclosed is a system for delegating access of sensitive information by a user device to a requestor device through a central server. A receiving module receives a first token Identification (ID) generated by the user device in an offline mode and a request, comprising a second token ID, from the requestor device. A validation module validates the request by comparing the first token ID and the second token ID. An identification module identifies a subset of the sensitive information based on a profile of the requestor, when the first token ID is matched with the second token ID. A watermarking module watermarks the subset of the sensitive information with a set of variables to generate watermarked sensitive information. Upon generating the watermarked sensitive information, the access delegation module delegates the access of the watermarked sensitive information to the requestor device.

Abstract: Disclosed is a system for debugging the network environment under regression testing. Initially, a data receiving module receives data pertaining to the network environment. An extraction module extracts a plurality of features by using a parser. An identification module identifies an error as a Problem Report (PR) or a False Failure (FF) based on classification of a test case execution log and a similarity confidence. The test case execution log may be classified based on comparison of a predefined pattern with an error pattern of the test case execution log. A generation module may generate second test case based on the plurality of features, a predefined set of instructions and the error pattern associated with the test case execution log by using a K-means and a Nearest Neighbour algorithm. A debugging module debugs the network environment based on execution of a test case.

Abstract: Disclosed is a system for providing source code suggestion to a user in real-time. A mining module mines source code information, pre-stored in a source code repository, to create a reference model. A code receiving module receives input lines of code from a user, via a User Interface, in real-time. A mapping module maps the one or more parameters with the metadata corresponding to each source code block stored in the reference model. A code suggestion module identifies one or more target source code blocks from the plurality of source code blocks. The code suggestion module suggests at least one target source code block, of the one or more target source code blocks, to be populated in the input lines of code thereby providing the source code suggestion to a user in real-time.

Abstract: Defect classification and association in a software development environment. The embodiments herein relates to a software development environment, and more particularly to managing defects in a software development environment. The defect management engine may use information present in the code repository to create a master list of features and/or sub-features. Using the master list, the defect management engine may scan and parse all reported defects (which may be present in the defect repository). The defect management engine may associate defects with features present in the master list. The defect management engine may then extract the test cases and map the test cases to the defects. The defect management engine may determine the test coverage metric and the test case sufficiency metric. The defect management engine may also label unmapped defects as orphan defects.

Abstract: The present disclosure relates to system(s) and method(s) for assisting a user in application development lifecycle. The system is configured to receive a new use case from a user device and identify a sub-set of development solutions from a set of development solutions, stored in a historical data repository, that are applicable for developing code corresponding to the new use case. Furthermore, the system is configured to receive a set test cases corresponding to each development solution from the historical data repository. Furthermore, the system is configured to generate a problem report and a false failure report based on analysis of the set of test cases. The system is further configured to rank the sub-set of development solutions based on analysis of the problem report and the false failure report. Further, the system is configured to generate a decision template based on the ranking of the sub-set of development solutions.

Abstract: Disclosed is a system for providing semantics based technical support to a user. A keyword extraction module extracts a set of keywords from a plurality of knowledge content and a plurality of bug content. A matrix generation module generates a keyword-content matrix comprising a similarity score computed for each keyword corresponding to each knowledge content. The matrix generation module further decomposes the keyword-content matrix into one or more sub-matrices. A vector coordinates identification module determines a first set of vector coordinates for each knowledge content of the plurality of knowledge content and a second set of vector coordinates for a bug-query received from a user in real-time. A similarity measure module computes a cosine similarity measure of the bug-query with each knowledge content to identify at least one knowledge content relevant to the bug-query. The knowledge identification module further provides the at least one knowledge content to the user.

Abstract: Disclosed is a method and system for classifying test cases. In one implementation, the method comprises creating a test step master list comprising a plurality of test case, one more test step associated with the plurality of test case, and a test step identification number associated with the one more test step. Further, the method comprises generating a sequence diagram for each of the plurality of test cases based on the test step master list. Furthermore, the method comprises classifying, by the processor, each of the plurality of test cases in to an independent test case or an asynchronous test case or a synchronous test case based on the sequence diagram.