Ca, Inc.

Computer Associates Think, Inc.

Debra Jean Danielson

Steven Lloyd Greenspan

James Donald Reno

Prashant Parikh

Eitan Hadar

Carol Piccus

Diane Norris

Donald Joseph Kleinschnitz, Jr

Karen Sleeth

John Patrick Kane

Kenneth William Scott Morrison

Hongrui Gong

Stephen Tyler

Kenneth W S Morrison

Alvin Dale Black

Jack Zito

Maria C Velez-Rojas

Mark Jacob Addleman

Jean-David Dahan

Timothy Gorden Brown

Howard A Abrams

Kouros Hodaee Esfahany

Serge Mankovskii

James Stephen Kress

Walter Schaefer

Miguel A Rivera

Jeffrey C Broberg

Kenneth Blackwell

Navid Rezvani

According to another embodiment of the disclosure, a method includes determining a first original identifier. The original identifier uniquely identifies a first original identity. The method also includes sending a request to a cooperative synthetic identity manager to create a first cooperative synthetic identity case for the first original identity. The method further includes receiving, from the cooperative synthetic identity manager, a first case identifier that uniquely identifies the first cooperative synthetic identity case. The method also includes requesting, from a first data entity, first cooperative synthetic identity information for the first original identity. The first cooperative synthetic identity information request comprises the first case identifier and the first original identifier. The method also includes receiving, from the first data entity, the first cooperative synthetic identity information.

System and method for analyzing cooperative synthetic identities

Systems and methods may include receiving performance data of components in a system. The performance data may include data for parameters for each of the components. The systems and methods may include determining aggregate data for each group of similar components of the components. The aggregate data for each group of similar components may include a group characteristic for each of the parameters. The systems and methods may include, for each group of similar components, determining whether the data for each of the parameters for each component is consistent with the group characteristic for the respective parameter. The systems and methods may include, for each component of the respective group determining that the component is anomalous in response to determining that the data for a parameter for the component is not consistent with the group characteristic for the parameter.

Assessing trust of components in systems

According to one embodiment of the disclosure, a method includes receiving, from a first requestor, a request to create a cooperative synthetic identity case for an original identity. The method includes determining whether a cooperative synthetic identity case has already been created for the original identity. The method also includes generating a case identifier that uniquely identifies the cooperative synthetic identity case. The method further includes associating the case identifier with an expiration period. The method also includes storing the cooperative synthetic identity case, the case identifier, and the expiration period to a memory. The method also includes sending the case identifier to the first requestor.

System and method for managing cooperative synthetic identities for privacy protection through identity obfuscation and synthesis

In an embodiment, a password risk evaluator may receive a request including a user identifier (ID) and a password. The password risk evaluator may retrieve a password preference model associated with the user ID, and may determine a risk score indicating a likelihood that the password is associated with the user ID. For example, the password preference model may be based on previous passwords used by the user, and may identify one or more characteristics, formulas, rules, or other indicia typically employed by the user in creating passwords. If the password supplied in the request matches or is similar to one or more elements of the password preference model, it may be more likely that the password in the request is a password supplied by the user. That is, the risk score may be an authentication of the user, or part of the authentication of the user, in some embodiments.

Authenticating identity for password changes

A method is described for receiving a plurality of node data streams through a data network from a plurality of source nodes, respectively, each of the plurality of node data streams comprising a plurality of node data. The method further comprises determining a respective risk assessment for each of the plurality of node data streams based on a plurality of elements, wherein the respective risk assessment indicates a level of trustworthiness of each of the plurality of node data streams. Moreover, the method comprises determining a plurality of respective actions for each of the plurality of source nodes, based on the respective risk assessment of the plurality of node data streams. The method further comprises instructing each of the plurality of source nodes to perform the respective action.

Automated data risk assessment

Systems and methods may include receiving real-time data about a real component operating in a real-world environment. The systems and methods may further include generating a virtual representation of the real component based on the real-time data about the real component and historical data associated with the real component. In addition, the systems and methods may include receiving injected data from a lab. The injected data may provide data about a lab component operating in the lab. The systems and methods may also include simulating, in a virtual environment, a real-time interaction in the real-world environment between the real component and the lab component using the virtual representation of the real component and the injected data. Moreover, the systems and methods may include determining a real-time performance characteristic of at least one of the lab component and the real component based on the simulated real-time interaction in the real-world environment.

Multi-component and mixed-reality simulation environments

The system and method for diagnosing information technology systems in multiple virtual parallel universes described herein may create virtualized parallel universes that represent a problematic information technology system. The virtualized parallel universes may then be diagnosed to identify potential solutions to a problem experienced in the problematic information technology system (i.e., the parallel universes may be diagnosed without disrupting the live problematic system). For example, the problematic information technology system may be cloned in response to a diagnostic request associated therewith to create various virtualized parallel universes representing the problematic information technology system. The parallel universes may then conduct various problem resolution steps to identify a potential solution to the problem, which may then be applied to the problematic information technology system to resolve the problem associated therewith.

System and method for diagnosing information technology systems in multiple virtual parallel universes

Systems and methods may include receiving data of a physical system. The systems and methods may include determining whether an anomalous event has occurred based on the data. The systems and methods may include, in response to determining that the anomalous event has occurred, capturing data of the physical system and of an environment. The systems and methods may include generating a virtual representation of the physical system and the environment based on the captured data. The systems and methods may include repeatedly simulating data of the virtual representation by varying parameters of the captured data. The systems and methods may include determining which parameters are a root cause of the anomalous event based on the simulated performance data. The systems and methods may include determining particular values of the parameters that are likely the root cause of the anomalous event to use as a trigger for a proactive process.

Self-learning simulation environments

The disclosed embodiments included a system, apparatus, method, and computer program product for optimizing the placement of data utilizing cloud-based IT services. The apparatus comprises a processor that executes computer-readable program code embodied on a computer program product. By executing that computer-readable program code, the processor extracts content from data and determines the context in which that data was generated, modified, and/or accessed. The processor also classifies the data based on its content and context, determines the cost of storing the data at each a plurality of locations, and specifies which of those locations the data is to be stored based on the classification of that data and the cost of storing that data at each of the plurality of locations.

Optimized placement of data

A method includes receiving product data relating to a first computer software product, selecting from the product data a set of epics that describe functional aspects of the first computer software product, and generating a product description ontology of the first computer software product from the selected set of epics. Product description ontologies of a plurality of second computer software products are compared to the product description ontology of the first computer software product, and in response, a list of product functions that are missing from the first computer software product but that are relevant to the first computer software product is generated. The list of product functions that are omitted from the first computer software product but that are relevant to the first computer software product is weighted and output as a weighted list. The weighted list may be used as an input to a software development management platform on which the first computer software product is developed.

System and method for synthetic ideation

The disclosed embodiments included a system, apparatus, method, and computer program product for optimizing the storage of data based at least in part on cost and service levels utilizing a cloud-based virtual storage fabric. Those embodiments are configured to compile operational information for service offerings that provide data storage at different storage locations, determine the costs of migrating that data to and storing that data at each of those storage locations utilizing the operational information, designate at which storage location each datum is to be stored based in part on those costs, and designate at least one datum for migration from one of the storage locations to another if the cost of storing that datum at that storage location is determined to be greater than the costs of migrating and storing that datum at the other storage location.

Optimized virtual storage fabric

Data privacy is provided in a computer network using a security inference control processor of a network device in the computer network which receives a query from a user device through a network interface circuit. In response to the query, a query result data set is generated based on information in a database stored in a non-volatile data storage device. Personally Identifiable Information (PII) exposure risk associated with the query result data set is determined based on an evaluation of combining the query result data set with an exposure storage log that includes result data sets from past queries associated with the user. Based on the PII exposure risk, the query result data set is provided to the user, so as to refrain from providing the query result data set if the PII exposure risk is greater than a risk threshold. Related methods, devices, and computer program products are provided.

Providing data privacy in computer networks using personally identifiable information by inference control

A current task flow path of a user is identified based on task flow nodes of the current task flow path, and a data context of the task flow nodes. The task flow nodes may include actions performed by the user with one or more software applications. A suggestion point of the current task flow path is detected. The suggestion point may be detected based upon a user action indicating that the user needs assistance to proceed with the current task flow path. A candidate task flow node is selected responsive to a comparison of the current task flow path to historical task flows. A suggestion is displayed to the user based on the candidate task flow node.

Methods, systems and computer program products for guiding users through task flow paths

A method includes receiving respective statistics for a plurality of infrastructure implementations. Each infrastructure implementation includes a respective organization and a respective deployment architecture. The method also includes determining a selected infrastructure implementation of the plurality of infrastructure implementations. The method further includes determining, using a processor, first particular implementations comparable to the selected infrastructure implementations from the plurality of infrastructure implementations, based on characteristics of the respective organization of the selected infrastructure implementation. The method additionally includes determining comparison metrics. The determining comparison metrics includes anonymizing the respective organization of each of the first particular implementations, and aggregating the respective statistics of each of the anonymized first particular implementations into comparison statistics. The comparison metrics include the comparison statistics, each respective deployment architecture of each of the first particular implementations, and the selected infrastructure implementation.

Growing community of inventors

Somerset, NJ, United States of America

Debra Jean Danielson