Abstract: Identifying root cause of code smells is crucial in enabling proper and efficient software maintenance. Desired are computationally less intensive and easy to implement solutions. Embodiments herein provide a method and system for code analysis to identify causes of code smells. The method provides considerable automation during software maintenance by analyzing detected code smells of two subsequent versions of an application by categorizing the code smells, filtering significant code smells from the detected code smells, mapping the significant code smells between two versions, generating a customized PDG for the mapped functions and performing the isomorphic subgraph mapping for computing a function difference. The computed function difference provides added part of the code or removed part or region of the code of the application, which is cause of the significant added code smells, which can then be provided for manual analysis to identify the root causes for efficient software maintenance.

Abstract: System and method for cheque image data masking are disclosed. In an example, a cheque image and a data file are received, the data file includes data records with values corresponding to sensitive data fields in the cheque image. Further, a template cheque image matching to the cheque image and redacted information associated with the template cheque image are obtained. Furthermore, a blank image snippet is generated for each sensitive data field in the cheque image based on a part of the obtained information about sensitive fields. Moreover, values corresponding to each sensitive field from the input data file are written to the blank image snippet based on the remaining information about sensitive fields. Also, the template cheque image is updated with the image snippet. Data of non-sensitive fields in the cheque image is then copied to the template cheque image, thereby facilitating cheque image data masking.

Abstract: This disclosure relates generally to consent management, and more particularly to a method and system for generating consent recommendation. The system determines a user aspect indicating consent preferences of the user, and identifies/predicts a reference privacy profile as matching the user aspect. The system uses a machine learning model to process the user aspect and to predict the matching reference privacy profile. Further, based on the matching reference privacy profile, the system generates one or more consent recommendations. The system can also be configured to obtain feedback for the generated consent recommendations and re-recommends consents based on the obtained feedback.

Abstract: The disclosure herein describes a method and a system for providing data privacy based on customized cookie consent. The proposed customized cookie consent system enables user's data privacy by facilitating the user to customize a plurality of features for each individual cookie, wherein a cookie is customized for multiple features that includes a consent and expiry customization, a drill down at individual cookie, an online masking unmasking cookie data—an offline masking-unmasking cookie data, a consent lineage and a data subject rights for cookie data that further include data access, data portability, right to erasure based on machine learning techniques. Further the customized cookie consent system also provides recommendation for data privacy and obscured cookies using machine learning techniques.

Abstract: Systems and methods for sensitive audio zone rearrangement are provided that protects confidential and sensitive information such as user identifier during query processing and authentication. The sensitive information rearrangement system generates or permutes the actual user identifier in a privacy preserving manner. The sensitive information is extracted from an input being either a speech or DTMF tones, and a virtual user identifier is generated in real time, that is specific to a transaction to be performed, or a query initiation by a user in real-time. The sensitive information is rearranged which can be either DTMF tone or speech of user to generate the virtual user identifier.

Abstract: Identifying root cause of code smells is crucial in enabling proper and efficient software maintenance. Desired are computationally less intensive and easy to implement solutions. Embodiments herein provide a method and system for code analysis to identify causes of code smells. The method provides considerable automation during software maintenance by analyzing detected code smells of two subsequent versions of an application by categorizing the code smells, filtering significant code smells from the detected code smells, mapping the significant code smells between two versions, generating a customized PDG for the mapped functions and performing the isomorphic subgraph mapping for computing a function difference. The computed function difference provides added part of the code or removed part or region of the code of the application, which is cause of the significant added code smells, which can then be provided for manual analysis to identify the root causes for efficient software maintenance.

Abstract: System and method for text localization in images are disclosed. In an embodiment, a line and graphic eliminated image is received. Further, horizontal projection is performed on rows of the image to obtain a first flag vector, the flag vector indicates whether there is text in each row. Furthermore, a number of run-lengths of consecutive 1's and 0's is computed in the first flag vector. Moreover, text lines is extracted in the image based on the computed number of run-lengths of consecutive 1's and 0's in the first flag vector. Also, vertical projection is performed on the text lines to obtain a second flag vector for the text lines. Further, a number of run-lengths of consecutive 1's and 0's is computed in the second flag vectors. Furthermore, text is localized in the image based on the computed number of run-lengths of consecutive 1's and 0's in the second flag vectors.

Abstract: This disclosure relates generally to data masking, and more particularly to method and system for dynamic data masking for mainframe application. In one embodiment, the method includes receiving a request to access a mainframe application from a user profile. A role assigned to the user-profile is fetched from a roles-repository. The role defines rights associated with the user-profile to access information from the mainframe application. Corresponding to the request, an access session is initiated based on the role, and a screen is received. The screen includes a multiple fields, where one or more fields includes sensitive data associated with the mainframe application. Contextual information associated with the plurality of fields is identified corresponding to the session. Rules indicative of the fields to be masked, are fetched corresponding to the screen based on the role. The fields are masked based on the rule and the contextual information associated with the fields.

Abstract: A system and method are provided for enforcing user policies on database. In one aspect a user policy and/or enterprise policy is predefined and mapped to the column of the database. Further, the query is run through a query parsing module, the result is sent to a query analyzing module to analyze the sensitivity of each query. A query rewriting module rewrites the query and the rewritten query is sent to the database. A sensitive tree is generated using database metadata, which is used during query analysis and query re-writing. In cases the original query does not contain any set operators the rewritten query is executed on the database and results are displayed as per the user policy. The cases where the original query comprises set operators a function called merger is implemented in the database or at the proxy server and data is displayed as per the user policy.

Abstract: The present disclosure provides systems and methods to estimate Importance Measure (IM) and temporal Importance Measure (IM) for any type of data in a distributed enterprise network by involving direct and indirect stakeholders of the data in the estimation process. Firstly data type of the received data is identified. Data type plugins including pre-defined classes, IM matrix and Temporal IM matrix are loaded for the identified data type. Extracted features from the data are appropriately mapped against pre-defined classes and then the IM is estimated. Temporal IM is estimated taking into account the current time and the rate of change.

Abstract: The disclosure generally relates to transcription of spoken words, and more particularly to a system and method for transcription of spoken words using multilingual mismatched words. The process comprises collection of multi-scripted noisy transcriptions of the spoken word obtained from workers of the multilingual mismatched crowd unfamiliar with the spoken language. The collected words are mapped to a phoneme sequence in the source language using script specific graphemes to phoneme model. Further, it builds a multi-scripted transcription script specific, worker specific and a global insertion-deletion-substitution (IDS) channel. Furthermore, the disclosure also determines reputation of workers to allocate the transcription task. Determination of reputation is based on word belief.

Abstract: Systems and methods for computing data privacy-utility tradeoff is disclosed. Large data hubs like data marketplace are a source of data that may be of utility to data buyers. However, output data provided to data sellers is required to meet the privacy requirements of data sellers and at the same time maintain a level of utility to data buyers. Conventionally known methods of achieving data privacy tend to suppress components of data that may result in reduced utility of the data. Systems and methods of the present disclosure compute this tradeoff to establish need for data transformation, if any, before data is shared with data sellers.

Abstract: A method and system is provided for managing complaint and reputation in a multi-party data marketplace. The system is managed by an independent external entity to monitor the data transactions in an unbiased manner. The system considers the data as commodity or resource, which is perishable and whose worth might decay with time. The system defines new parameters for reputation and liability calculation (based on complaints), for example, consideration of peer and trust network, history of peering and transaction, automatic decay of reputation and liability in case of inactive participants. According to another embodiment, the disclosure also handles any kind of collusion between external or internal entities/parties/participants. Whereas in another embodiment the disclosure also identifies and restrict influencers in a multi-party data marketplace.

Abstract: Method and system for analyzing unstructured data for compliance enforcement is disclosed. The system provides a comprehensive compliance enforcement platform, which enables purpose based data processing in an enterprise to support automatic discovery of purposes and linking between data fields and purposes. The system creates a single view of data associated with the data subject for enforcing the data subject's right for data protection and privacy. The system supports database like transactions for unstructured data over web and ensures Atomicity, Consistency, Isolation and Durability (ACID) properties of these transactions. Thus, the system creates a uniform data layer or a web view for data residing in the unstructured and semi-structured data, spread across the enterprise. The transactions on the unstructured data include READ operation, UPDATE operation, and DELETE operation using hypertext transfer protocol (http) over the unstructured data.

Abstract: The present disclosure provides systems and methods to optimize data backup in a distributed enterprise system by firstly generating a set of unique files from all the files available in the enterprise. A backup set comprising files to be backed up are then generated from the set of unique files and backup is scheduled in the order in which the files to be backed up are identified. Unique files are generated based on file sharing patterns and communications among users that enable generating a social network graph from which one or more communities can be detected and deduplication can be performed on the files hosted by client systems in these communities thereby conserving resources.

Abstract: The present application provides a method and system for unsupervised word image clustering, comprises capturing one or more image wherein the one or more image comprises at least one word images. Extracting at least one feature vector using an untrained convolution neural network architecture, wherein the convolution filters are initialized by random filter based deep learning techniques using Gaussian random variable with zero mean and unit standard deviation, and wherein the convolution filters are constrained to sum to zero. The extracted feature vectors are used for clustering, wherein clustering is performed in two stages. First stage includes clustering word images which are similar using a graph connected component. Second stage clustering includes clustering a remaining word images which are not clustered during the first stage by evaluating the remaining images against the clusters formed during the first stage and assigning them to clusters based on the evaluation.

Abstract: System and method for text localization in images are disclosed. In an embodiment, a line and graphic eliminated image is received. Further, horizontal projection is performed on rows of the image to obtain a first flag vector, the flag vector indicates whether there is text in each row. Furthermore, a number of run-lengths of consecutive 1's and 0's is computed in the first flag vector. Moreover, text lines is extracted in the image based on the computed number of run-lengths of consecutive 1's and 0's in the first flag vector. Also, vertical projection is performed on the text lines to obtain a second flag vector for the text lines. Further, a number of run-lengths of consecutive 1's and 0's is computed in the second flag vectors. Furthermore, text is localized in the image based on the computed number of run-lengths of consecutive 1's and 0's in the second flag vectors.

Abstract: Systems and methods for masking content of different types are described. The system may implement the method comprising receiving a request to mask input content that includes sensitive and non-sensitive data. The method also comprises parsing the input content to create a content specific structure (CSS) to organize the input content in a structured format. The CSS includes a plurality of CSS nodes. The method analyses each CSS node against a pre-defined privacy policy and identifies sensitivity of the each CSS node. The method also creates a generalized masking structure (GMS) by creating a GMS node corresponding to each CSS node. Each GMS node contains sensitivity information related to corresponding CSS node. Data represented by GMS is masked based upon the sensitivity information stored in it.

Abstract: System and method for cheque image data masking are disclosed. In an example, a cheque image and a data file are received, the data file includes data records with values corresponding to sensitive data fields in the cheque image. Further, a template cheque image matching to the cheque image and redacted information associated with the template cheque image are obtained. Furthermore, a blank image snippet is generated for each sensitive data field in the cheque image based on a part of the obtained information about sensitive fields. Moreover, values corresponding to each sensitive field from the input data file are written to the blank image snippet based on the remaining information about sensitive fields. Also, the template cheque image is updated with the image snippet. Data of non-sensitive fields in the cheque image is then copied to the template cheque image, thereby facilitating cheque image data masking.

Abstract: This disclosure relates generally to malware detection, and more particularly to system and method for detecting and mitigating ransomware threats. For a User Equipment being monitored, the system performs a behavior analysis of corresponding file system to determine whether any anomalous behavior that would amount to a ransomware threat is associated with flies associated with the file system change, if present, then the system virtualizes the file system on the fly. If information pertaining to the identified anomalous behavior is present in any of the reference databases in the system, then all the I/O calls are terminated or the file system is virtualized for rest of the session. If data pertaining to the identified anomalous behavior is not found in any of the associated databases, then new behavioral features and structural patterns of the identified anomalous behavior and the associated processes are extracted, and the reference databases are updated accordingly.