Abstract: Data is an asset to any organization and any breach to the data during task allocation to agents may lead to serious damage to organizations including loss of consumer confidence, trust, reputation, financial penalties and the like. Conventional methods mainly focus on the allocating task to agents based on user satisfaction, overall throughput and maximize revenue and less focus is given to data privacy. The present subject matter overcomes the limitations of the conventional methods for task allocation by utilizing a dynamic data exposure analysis method, which enables seamless upgrading of the data access policy and or control. Here, a data exposure is monitored based on a data exposure score, dynamic identification of conflicting tasks and a dynamic privacy budget. The data exposure score is calculated in two execution points. Finally all the values are updated in the system for utilization in the further privacy enabled task allocation.

Abstract: Data is an asset to any organization and any breach to the data during task allocation to agents may lead to serious damage to organizations including loss of consumer confidence, trust, reputation, financial penalties and the like. Conventional methods mainly focus on the allocating task to agents based on user satisfaction, overall throughput and maximize revenue and less focus is given to data privacy. The present subject matter overcomes the limitations of the conventional methods for task allocation by utilizing a dynamic data exposure analysis method, which enables seamless upgrading of the data access policy and or control. Here, a data exposure is monitored based on a data exposure score, dynamic identification of conflicting tasks and a dynamic privacy budget. The data exposure score is calculated in two execution points. Finally all the values are updated in the system for utilization in the further privacy enabled task allocation.

Abstract: Described herein is a method for rendering specification creation, including identifying, within one or more contents, labels as sensitive labels when data associated with the label are determined sensitive based on one or more user-defined policy rules, wherein the identifying considers structural locations of labels determined as sensitive and the data associated with the sensitive label; configuring rendering specifications for data associated with the identified sensitive labels; and associating the configured rendering specifications with the sensitive labels of the data determined as sensitive, for execution in real time.

Abstract: A system and method enabling information access control of the sensitive information, based on a trust computing platform is provided. The trustworthiness of the information seekers is computed and accordingly the information owner is capacitated to decide upon sharing the information completely or sharing with some perturbation. The objective is to provide the information owner with the ability to decide on sharing its private data with respect to a parameter so that the decision is less subjective. This invention allows minimum leakage of sensitive data and makes information owner aware of the risk of privacy breach when private data is shared.

Abstract: A system and method enabling information access control of the sensitive information, based on a trust computing platform is provided. The trustworthiness of the information seekers is computed and accordingly the information owner is capacitated to decide upon sharing the information completely or sharing with some perturbation. The objective is to provide the information owner with the ability to decide on sharing its private data with respect to a parameter so that the decision is less subjective. This invention allows minimum leakage of sensitive data and makes information owner aware of the risk of privacy breach when private data is shared.

Abstract: Described is a method for dynamic data masking (DDM) of sensitive data. The method for DDM comprises receiving a response output comprising sensitive data, based on a client request, from an application, and identifying a main masking specification, based on the response output, for masking of the sensitive data in the response output. Further, the response output is parsed for creating a Document Object Model (DOM) tree for the response output. Status of a masking approach indication field of the main masking specification is checked, and masking is performed on nodes in the DOM tree comprising the sensitive data, based on the status of the masking approach indication field of the main masking specification.

Abstract: The present subject matter relates to systems and methods for database sampling. The method comprises identifying at least one query table and one or more associated tables amongst a plurality of tables in a production database, based on filtering criteria. Further, the method comprises generating a key value list for the at least one query table and each of the one or more associated tables based on an order indicated by an order list. Based on the generated key value list, the sample data is extracted in a reverse order indicated by the order list, from the at least one query table and each of the one or more associated tables.

Abstract: Described is a method for dynamic data masking (DDM) of sensitive data. The method for DDM comprises receiving a response output comprising sensitive data, based on a client request, from an application, and identifying a main masking specification, based on the response output, for masking of the sensitive data in the response output. Further, the response output is parsed for creating a Document Object Model (DOM) tree for the response output. Status of a masking approach indication field of the main masking specification is checked, and masking is performed on nodes in the DOM tree comprising the sensitive data, based on the status of the masking approach indication field of the main masking specification.

Abstract: Described herein is a method for rendering specification creation, including identifying, within one or more contents, labels as sensitive labels when data associated with the label are determined sensitive based on one or more user-defined policy rules, wherein the identifying considers structural locations of labels determined as sensitive and the data associated with the sensitive label; configuring rendering specifications for data associated with the identified sensitive labels; and associating the configured rendering specifications with the sensitive labels of the data determined as sensitive, for execution in real time.

Abstract: The present subject matter relates to systems and methods for database sampling. The method comprises identifying at least one query table and one or more associated tables amongst a plurality of tables in a production database, based on filtering criteria. Further, the method comprises generating a key value list for the at least one query table and each of the one or more associated tables based on an order indicated by an order list. Based on the generated key value list, the sample data is extracted in a reverse order indicated by the order list, from the at least one query table and each of the one or more associated tables.

Abstract: A system for identifying rail weights applicable to worn railroad rails measured along a railroad track system includes at least one track measurement device for recording at least a portion of a profile shape of the worn rails, and, a data processor running a software implement for accepting recorded data as input data from the at least one track measurement device and for processing the input data against known unworn railroad rail data to facilitate selection and application of the appropriate rail weights equated thereto to the worn railroad rails.

Abstract: In a system using digital identities, such as a public key cryptosystem using public key certificates, each certificate is part of a data revocation structure of tokens maintained by a certification authority (CA). Certificates may then share tokens with other certificates. By updating certain of these tokens periodically to indicate valid (unrevoked and unexpired) certificates, the number of updated records is reduced. Moreover, in response to a status query, a single token is transmitted in response. This results in a more efficient overall use of both computing and communications network resources. In one version of the invention, the data revocation structure is a binary tree. Each certificate includes each zero token for each node in its path from leaf to root of the tree. The tree is updated periodically to indicate valid and revoked certificates.