Abstract: ML methods and systems for cataloging and making recommendations based on domain-specific knowledge are disclosed. An example method includes: cataloging, using knowledge engines, data to develop knowledge repositories for respective domains; obtain current domain state data; obtain future domain state data; analyze, using first ML models, one or more of (i) data from the knowledge repositories, (ii) the first domain state data, and (iii) the second domain state data to identify a recommended set of one or more regulations, standards, policies and/or rules for a desired second domain state; analyze, using second ML models, (i) the recommended set and (ii) a current data and architecture state for a current computing environment to generate a summary of one or more cloud deployment options for migrating a current computing environment to a future computing environment for a future domain state; and cause the summary to be displayed on a computing device.

Abstract: Systems and techniques that facilitate automated health-check risk assessment of computing assets are provided that can generate a baseline health-check risk score that corresponds to non-compliance of a computing asset with a stipulated control, and can adjust the baseline health-check risk score based on a weakness factor of the stipulated control, an environmental factor of the computing asset, a criticality factor of the computing asset, and a maturity factor of the computing asset.

Abstract: A computer-implemented system and method are disclosed that monitor and determine vendor compliance with at least some aspects of information and security criteria. At least one computing device is configured by executing code to access information and security criteria respectively associated with a vendor that provides a good and/or service. At least some aspects of the information and security criteria are provided by an organization considering the vendor and, further, the information and security criteria include at least one of cybersecurity criteria, regulatory criteria, intellectual property criteria, data management criteria, and policy criteria.

Abstract: A computer-implemented method for monitoring productivity, health and safety risks posed by activities and objects, and other signals present at industrial sites comprises: receiving data inputs from input devices at an industrial site; selecting a data model that is programmed to detect activities or objects associated with workers or equipment present at the industrial sites; applying the data inputs to the data model to receive output data specifying whether the activities or objects associated with workers or equipment are present at the industrial site; and if they are present: based the output data, determining characteristics of the activities or objects; based on the characteristics, determining whether that the activities or objects cause any productivity, health or safety risks at the industrial site; and if so, generating notifications indicating the health or safety risks at the industrial site.

Abstract: One embodiment of the present invention sets forth a technique for processing unstructured data. The technique includes applying one or more machine learning models to a set of candidate topics extracted from the unstructured data to determine a set of activities of interest included in the set of candidate topics. The technique also includes generating a set of scores for the activities of interest, wherein each score included in the set of scores represents an estimated impact of a corresponding activity of interest on operations within a domain. The technique further includes determining one or more activities included in the set of activities of interest based on a ranking of the activities of interest by the scores, and causing one or more alerts to be outputted in a user interface, wherein each of the alerts is associated with a potential event related to the one or more activities.

Abstract: In some implementations, a system may receive a submission associated with an innovation associated with an entity. The system may analyze, using a first machine learning model, the submission to identify a classification associated with the innovation. The system may analyze, using a second machine learning model in association with the classification, content of the submission to identify a characteristic of the innovation. The system may determine, using a third machine learning model and based on the characteristic, a ranking of the innovation relative to individual innovations in the subset of innovations. The system may determine, using a fourth machine learning model, an impact score associated with the innovation. The system may perform, based on the impact score satisfying a threshold, an action associated with a project involving the innovation.

Abstract: This disclosure relates generally to system and method for assessing insider influence on enterprise assets. Existing work focuses on the detection of insider threat and does not consider the influence of an insider on their peers and subordinates. The present disclosure aggregates and preprocesses the enterprise data specific to the individuals received from various sources, and further creates an enterprise graph between entities. Weights of every edge connected between any two entities in the enterprise graph is then calculated. Community of the individuals are detected wherein, relevant insider(s) are identified, and susceptibility of the individuals for probable influence by relevant insider(s) based on the analysis scenarios(s) is calculated. Paths taken by the relevant insider(s) is calculated for estimating probability of data loss.

Abstract: Methods and systems are presented herein for assessing risk associated with a vendor providing services and/or other products to a financial institution, for preparation of associated risk assessment reports or vendor oversight reports, and for maintenance of a plurality of risk assessment reports or oversight reports associated with a plurality of vendors.

Abstract: A dynamical hierarchical tagging system connected to a user site through a remote communications network. The system may comprise a master controller, a job management server connected to the master controller, one or more scanners in communication with the job management server, wherein the one or more scanners are configured to scan for one or more user assets located at the user site, resulting in scan results, a scan logic processor connected to the master controller, wherein the scan logic processor is configured to store the scan results in a user database, a tagging logic engine connected to the master controller, wherein the tagging logic engine is configured to tag the scan results stored in the user database, and an indexing logic processor connected to the master controller, wherein the indexing logic processor is configured to search and index the tagged scan results stored in the user database.

Abstract: Disclosed are methods and systems for determining combinations of system parameters that indicate a root cause of a system level experience deterioration (SLED). Some of the disclosed embodiments generate a decision tree from a first class of operational parameter datasets. Rules are derived from the decision tree. Filtered rule sets for feature parameters included in the system parameters are then determined. Pairs of features within a particular dataset that each satisfy their respective filtered rule sets are indicative of a root cause of the degradation, at least in some embodiments.

Abstract: A system, method, and computer-readable medium are disclosed for performing a security operation. The security operation includes: monitoring an entity, the monitoring observing at least one electronically-observable data source; identifying a security related activity of the entity, the security related activity being of analytic utility; accessing an entity behavior catalog based upon the security related activity, the entity behavior catalog providing an inventory of entity behaviors; and performing a security operation via a human-centric risk modeling framework, the security operation using entity behavior catalog data stored within the entity behavior catalog based upon the security related activity.

Abstract: A system, method, and computer-readable medium are disclosed for performing a security operation. The security operation includes: monitoring an entity, the monitoring observing at least one electronically-observable data source; deriving an observable based upon the monitoring of the electronically-observable data source; identifying a security related activity, the security related activity being based upon the observable from the electronic data source; the security related activity comprising a concerning behavior, the security related activity being enacted during an activity session; associating the security related activity enacted during an activity session with a security risk persona; analyzing the security related activity, the analyzing the security related activity using the security risk persona; and, performing a security operation in response to the analyzing the security related activity.

Abstract: A system, method, and computer-readable medium are disclosed for performing a security operation. The security operation includes: monitoring an entity, the monitoring observing at least one electronically-observable data source; identifying an event of analytic utility; analyzing the event of analytic utility, the analyzing the event of analytic utility identifying an entity behavior associated with the event of analytic utility; and, performing the security operation in response to the analyzing the event of analytic utility, where the monitoring, identifying, analyzing and performing are performed via a distributed security analytics framework.

Abstract: Techniques and apparatus for providing peer-based management of user accounts are described. In one embodiment, for example, an apparatus may include at least one memory and logic coupled to the at least one memory. The logic may be configured to determine a total entity risk value representing a risk position of an entity comprising at least one segment, generate a plurality of risk tokens, each of the plurality of risk tokens having a token value that is a portion of the total risk value, determine a total segment risk value for the at least one segment, the total segment risk value representing a portion of the total entity risk value allocated to the at least one segment, and distribute the plurality of risk tokens to the at least one segment of the entity to correspond with the total segment risk value. Other embodiments are described.

Abstract: A risk assessment system is provided and includes a transceiver, an output device, and activity, localization, tracking, and risk assessment modules. The activity module: receives signals from sensors or electrical devices of a supporting structure; and tracks activities in or within a set distance of the supporting structure to generate an activity history log. The localization module relates the activities to aspects of the supporting structure and generates corresponding localization data. The transceiver receives a notification key identifying a network device used by a user exposed to a contaminant. The tracking module, in response to the notification key, tracks contamination states of the aspects of the supporting structure contacted directly or indirectly by the user. The risk assessment module determines and reports an exposure risk level of an occupant of the supporting structure based on the contamination states, the localization data and the activity history log.

Abstract: A system, method, and computer-readable medium are disclosed for performing a security operation. The security operation includes: monitoring an entity, the monitoring observing at least one electronically-observable data source; deriving an observable based upon the monitoring of the electronically-observable data source; identifying a security related activity, the security related activity being based upon the observable from the electronic data source, the security related activity comprising a concerning behavior; generating a contextual modifier relating to the security related activity; analyzing the security related activity, the analyzing the security related activity being based upon the contextual modifier; and, performing a security operation in response to the analyzing the security related activity.

Abstract: There is provided a computer-implemented method of applying a first function to each data element in a first data set, the method comprising (i) determining whether each data element in the first data set satisfies a criterion, wherein the criterion is satisfied only if the result of applying the first function to the data element is equal to the result of applying a second first data set satisfies a criterion function to the data element; (ii) forming a compressed data set comprising the data elements in the first data set that do not satisfy the criterion; (iii) applying the first function to 10 each data element in the compressed data set; and (iv) forming an output based on the results of step (iii); wherein steps (i)-(iv) are performed using multiparty computation, MPC, techniques. A corresponding system and worker node are also provided.

Abstract: A system, method, and computer-readable medium are disclosed for performing a security operation. The security operation includes: monitoring an entity, the monitoring observing an electronically-observable data source; deriving an observable based upon the monitoring of the electronically-observable data source; identifying a security related activity, the security related activity being based upon the observable from the electronic data source; analyzing the security related activity, the analyzing the security related activity using a security risk persona; and, performing a security operation in response to the analyzing the security related activity.

Abstract: Aspects of the disclosure relate to using synthetic DNA stranding and mutant nucleotide processes to conduct enterprise market volatility predictions. In some embodiments, a computing platform may initiate a set of instructions associated with performing an action on a synthetic DNA market data set associated with a plurality of lines of business across an enterprise organization. Thereafter, the computing platform may convert the set of instructions to a mutant nucleotide sequence, and insert the mutant nucleotide sequence into the synthetic DNA market data set. The computing platform may extract, using the mutant nucleotide sequence, target information from the synthetic DNA market data set, and validate the target information to detect one or more anomalies. The computing platform may remove the one or more data anomalies, and subsequently output a validated synthetic DNA market data set to a synthetic DNA client server.

Abstract: Aspects of the disclosure relate to using synthetic DNA stranding and mutant nucleotide processes to conduct enterprise market volatility predictions. In some embodiments, a computing platform may receive raw market data from a plurality of lines of business of an enterprise organization. Thereafter, the computing platform may preprocess the raw market data to obtain enterprise level market data, execute synthetic DNA stranding of the enterprise level market data to obtain synthetic DNA stranded market data, run the synthetic DNA stranded market data through one or more market volatility models, and compile results from the market volatility models on the synthetic DNA stranded market data. The computing platform may transmit results from the market volatility models on the synthetic DNA stranded market data. The transmitted results may be configured to display a market application interface that includes market volatility forecasting parameters based on results of the market volatility models.

Abstract: A protection system, method, and a security device can protect an operational technology (OT) system having connected hardware equipment, including at least an interface that can receive a control communication and an industrial control device (ICD) for controlling at least one industrial device. They feature tasks/steps that receive control communication from the communication interface, determine whether the received control communication contains an undesirable control command, and either pass or block the received control communication to the ICD depending on whether the received control communication contains an undesirable control command. The security device can be disposed between a source of communication in an OT network and the ICD for protection.

Abstract: In an example embodiment, machine learning is utilized to automatically identify pain points of an entity. More particularly, a random forest search algorithm receives inputs from a number of different outside-in data engines. These inputs are segregated in terms of key performance indexes (KPIs), which is then fed to a random forest decision tree. The random forest search algorithm calculates a p-value for each KPI. This p-value may then be used to identify the most relevant KPIs (such as by ranking the KPIs by their respective p-values). Rules are utilized not to identify the pain points themselves, but instead to define sorting preferences (refine the ranking). Based on a combination of the p-values and the evaluation of the rules, the top-N pain points may be identified.

Abstract: Provided are a cloud platform-based comprehensive line network monitoring method and system. Device state data of each line is acquired, and stored in a monitoring platform and a data platform that are built on a cloud platform. The monitoring platform can only store only the latest device state data, perform data monitoring processing on the device state data to obtain real-time monitoring data, and transmit corresponding real-time monitoring data to a client at an application layer based on a data subscription demand of the client, to allow the client to perform real-time device monitoring processing based on the real-time monitoring data. Also, the data platform can provide, in response to a historical data application request sent by the client, the device state data to the client as historical statistical analysis data, to allow the client to perform historical state monitoring processing based on the historical statistical analysis data.

Abstract: A method in a network node is provided for mitigating disruption during maintenance of an edge gateway node of a communication network. The edge gateway node connects devices to services(s) of the communication network. First device(s) are capable of connecting to a cloud environment in the absence of the edge gateway node, and second device(s) are incapable of connecting to the cloud environment in the absence of the edge gateway node. The method comprises: establishing respective virtual devices for the second device(s), the virtual devices comprising predictive models trained to replicate data output by the respective second device(s); and, during a time interval in which the maintenance of the edge gateway node is performed: configuring the virtual device(s) to connect to a virtual edge gateway node established in the cloud environment; and configuring at least one of the first device(s) to connect to the virtual edge gateway node.

Abstract: Methods, apparatuses, systems, and computer program products are disclosed for outputting a contextually relevant development unit performance insight interface component in a project management and collaboration system. In an example embodiment, an apparatus detects an insight interface component request, accesses past development unit performance metrics data, determines a suggested development unit performance target, determines a selected development unit commitment, determines a visual emphasis element for the selected development unit commitment, wherein the visual emphasis element is configured to visually compare the selected development unit commitment to the suggested development unit performance target, generates a development unit performance summary insight interface component comprising the visual emphasis element, and outputs the development unit performance summary insight interface component for rendering to a project management user interface.

Abstract: A cybersecurity risk management method may include recommending, for each of a plurality of affiliates of an entity, a respective cybersecurity criticality tier selected from a set of cybersecurity criticality tiers; receiving user input adjusting and/or adopting the recommended cybersecurity criticality tier for each of the affiliates; assigning each of the affiliates to the respective adjusted or adopted cybersecurity criticality tier; obtaining respective security scores for the affiliates; and displaying a user interface component configured to show a visualization of a cybersecurity risk management plan of the entity with respect to the plurality of affiliates, wherein the risk management plan partitions the affiliates into a plurality of affiliate sets based on the security scores and the assigned cybersecurity criticality tiers of the affiliates and specifies, for each of the affiliate sets, an action to be taken by the entity with respect to the affiliates in the affiliate set.

Abstract: A cognitive information processing system environment which includes a plurality of data sources; a cognitive inference and learning system coupled to receive a data from the plurality of data sources, the cognitive inference and learning system processing the data from the plurality of data sources to provide cognitively processed insights, the cognitive inference and learning system further comprising performing a learning operation to iteratively improve the cognitively processed insights over time; and, a destination, the destination receiving the cognitively processed insights.

Abstract: A method, apparatus, and computer program product are disclosed for improved machine learning using a statistical model. In the context of an apparatus, some example embodiments include a processor configured to cause retrieval of information regarding a plurality of consumers, and modeling circuitry configured to train a statistical model of the plurality of consumers based on the retrieved information, and predict, using the statistical model, an incremental booking value associated with the promotion for each consumer of the plurality of consumers. The processor is further configured to select a subset of the plurality of consumers for receiving impressions of the promotion. Some example embodiments may further include communications circuitry configured to transmit an impression of the promotion to each consumer in the subset of the plurality of consumers.

Abstract: Mobile device security techniques are described. For a specific computing device, for each of a plurality of distinct security categories, a risk score is determined. The determined risk scores are aggregated to obtain an overall risk score.

Abstract: User behavior data of multiple users is acquired, and multiple user eigenvalues of user behavior data of each user under preset multiple user behavior dimensions are extracted. A user eigenvector of each user is determined based on the multiple eigenvalues of this user. Multiple user classes are obtained by clustering the user eigenvectors of multiple users are clustered through a preset clustering algorithm. A central vector of each user class is determined based on the user eigenvectors included in this user class. A difference eigenvector of each user class is determined, wherein a distance between the difference eigenvector and a central vector of an aggregation class to which the difference eigenvector belongs is not within a preset distance range. A user characterized by the difference eigenvector is determined as an abnormal user.

Abstract: Systems, methods, and products for detection of selective omissions in an open data sharing computing platform comprises monitoring a plurality of events associated with a first digital record stored in a database of digital records, the first digital record uniquely identifying a first entity; associating a first detected event with a first set of words at least partially descriptive of the first detected event; associating a second detected event with a second set of words at least partially descriptive of the second detected event, the first event and the second event being detected, in response to digital records associated with the first event and the second event being shared over an open data sharing computing platform with express authorization provided by the first entity.

Abstract: A computerized process useful for automating Risk Identification, Quantification, Benchmarking and Mitigation in an enterprise computer system, includes the step of integrating an enterprise security, privacy and compliance system in an enterprise computer system. The enterprise security, privacy and compliance system monitors a set of risk sources. The method includes the step of implementing an identification and a weighted scoring of a set of risks associated with each risk source. The method includes the step of, with a specified machine learning technique, matching a set of similar risk inputs with an associated weight. The set of similar risk inputs are similar to the risk sources in the RPPBM practice. The method includes the step of monitoring the relevant enterprise systems for changes in risk levels of each risk source. The method includes the step of generating a risk-score number for each risk source. The risk-score number is used to avoid a subjective assessment of the risk source.

Abstract: Machine data is collected from multiple sources of an operating environment such as an information technology system, factory floor, or the like, into a data intake and query system, in one embodiment. Metrics representative of the environment are included in or derived from the data. Users may interact with an interface to depict a representation of various metrics and interdependencies and that depiction is reflected in a computer storage model. Changes to the computer storage model based on the user interaction may also result in training of a machine learning model according to the user interaction, the machine learning model configured to determine a prediction, classification or clustering of a result of a first search query by utilizing a result of at least a second search query as input to the machine learning model.

Abstract: Methods and systems are presented herein for assessing risk associated with a vendor providing services and/or other products to a financial institution, for preparation of associated risk assessment reports or vendor oversight reports, and for maintenance of a plurality of risk assessment reports or oversight reports associated with a plurality of vendors.

Abstract: Hardware trust boundaries in a data confidence fabric are provided. Nodes in a data confidence fabric are provisioned with identifies and confidence scores. Hardware-based trust insertion technologies are applied to data in the data confidence fabric. Protocols allow nodes to join the data confidence fabric and be aware of other nodes. Paths of data can be graphed and audited.

Abstract: A device may receive historical risk data identifying historical risks associated with entities, and historical compliance data identifying historical compliance actions performed by the entities. The device may train a machine learning model with the historical risk data and the historical compliance data to generate a structured semantic model, and may receive entity risk data identifying new and existing risks associated with an entity. The device may receive entity compliance data identifying new and existing compliance actions performed by the entity, and may process the entity risk data and the entity compliance data, with the structured semantic model, to determine risk and compliance insights for the entity. The risk and compliance insights may include insights associated with a key performance indicator, a compliance issue, a regulatory issue, an operational risk, a compliance risk, or a qualification of controls. The device may perform actions based on the risk and compliance insights.

Abstract: Systems and methods are provided for evaluating workplace risk by associating sensors with individual members of a workforce to measure conditions affecting the individual. Data is obtained from the sensors for reoccurring work periods for each individual so that a risk analysis may be performed to derive a risk score. Probability of injury is calculated aggregating risk scores for multiple reoccurring work periods. The calculated probability of injury is used to quantify workplace risk for the at least one individual and an enterprise risk assessment is provided by combining the quantified risks for each individual.

Abstract: An automated parameterized modeling and scoring intelligence system includes a parameterized score estimation software tool and a parameterized score optimization software tool. The parameterized score estimation software tool processes design metrics associated with a current project according to historical project data selected based on a similarity with at least some of the design metrics to determine a score estimation for the current project. The parameterized score optimization software tool processes the score estimation based on external application data retrieved from an external application to determine an expected yield for the current project. A user of the system may iterate against the score estimation or the expected yield by changing one or more of the parameters used to determine same. The iteration may result in a score estimation or expected yield different from the initial versions thereof, such as to identify an optimal design for the current project.

Abstract: In general, various aspects of the present disclosure provide methods, apparatuses, systems, computing devices, computing entities, and/or the like for addressing a modified risk rating identifying a risk to an entity of having computer-implemented functionality provided by a vendor integrated with a computing system of the entity.

Abstract: An apparatus and method for system safety analysis evaluation is provided, the apparatus including processing circuitry configured for generating a calculation matrix for a system, generating a plurality of models based on the calculation matrix, performing a benchmarking or convolution analysis of the plurality of models, identifying a design envelope based on the benchmarking or convolution analysis, deriving uncertainty models from the benchmarking or convolution analysis, deriving an assessment judgment based on the uncertainty models and acceptance criteria, defining one or more limiting scenarios based on the design envelope, and determining a safety margin in at least one figure-of-merit for the system based on the design envelope and the acceptance criteria.

Abstract: The invention relates to a system for monitoring wind turbine components including an independent data processing environment adapted to: receive a first category of data input related to operation of the wind turbine, process the received data input by one or more component specific monitoring algorithms adapted to establish an estimated component value related to a component to be monitored based on received first category data input having at least indirectly impact on the component, wherein the component specific monitoring algorithm is adapted to establish a component residual as the difference between the estimated component value and received first category of data input of the component to be monitored, and wherein the component specific monitoring algorithm furthermore is adapted to establish a component specific health value of the component to be monitored based on the established residual and put the health value at disposal for data processors outside the environment.

Abstract: There is provided a research framework system. For example, in some implementations there is provided a sleep prediction system for pilots including a first data structure storing collected research data related to pilot sleep patterns, a second data structure storing data related to a flight schedule associated with a pilot, and a sleep prediction module configured to access the data stored in the first and second data structures and calculate, by one or more processors using the data stored in the first data structure, a likelihood that the pilot associated with the flight schedule stored in the second data structure is sleeping at a given time.

Abstract: A method includes obtaining data associated with operation of a model-based industrial process controller. The method also includes identifying at least one estimated impact of at least one operational problem of the industrial process controller, where each estimated impact is expressed in terms of a lost opportunity associated with operation of the industrial process controller. The method further includes presenting the at least one estimated impact to a user. The at least one estimated impact could include impacts associated with noise or variance in process variables used by the industrial process controller, misconfiguration of an optimizer in the industrial process controller, one or more limits on one or more process variables, a quality of at least one model used by the industrial process controller, a quality of one or more inferred properties used by the industrial process controller, or one or more process variables being dropped from use by the industrial process controller.

Abstract: An apparatus comprises a processing device configured to receive, at a user interface of a trust platform configured to manage cloud assets operating in clouds of two or more cloud service providers, a request to view multi-cloud relative risk information for at least a subset of the cloud assets on which workloads of a given entity run. The processing device is also configured to obtain, utilizing application programming interfaces of the trust platform, first and second sets of cloud asset risk data generated by first and second pluralities of monitoring tools operating in tenant and management environments of the clouds of the two or more cloud service providers. The processing device is further configured to generate and provide, at the user interface of the trust platform, a unified view of the multi-cloud relative risk information utilizing the first and second sets of cloud asset risk data.

Abstract: A system to provide an automated data driven risk relationship review tool via a back-end application computer server of an enterprise. A resource allocation data store may contain electronic records representing requested resource allocations between the enterprise and a plurality of entities. The server may receive an indication of a selected requested resource allocation and retrieve, from the resource allocation data store, the electronic record associated with the selected requested resource allocation. The server may automatically calculate a first and second review date for the selected requested resource allocation and automatically establish a communication link based on the first review date for the selected requested resource allocation. The system may then support a graphical interactive user interface display via a distributed communication network, the interactive user interface display providing resource allocation data in connection with the second review date.

Abstract: Techniques are described for enabling a software modernization assessment service of a cloud provider network to maintain a modernization knowledge base and to use the knowledge base to generate modernization recommendations for users' software applications. A modernization knowledge base comprises one or more modernization ontologies, where a modernization ontology defines concepts and relationships used to describe modernization tool capabilities and limitations, modernization strategies, etc. The modernization assessment service uses the modernization knowledge base to automate various software modernization processes including, for example, providing modernization recommendations for software applications (e.g., applications identified by users as candidates for modernization) and generating modernization assessment reports.

Abstract: Systems and methods for automatically creating and managing electronic data tables are disclosed. The method includes receiving a metric request descriptor from a client device, the metric request descriptor including at least information for creating a metric query and an identifier of an electronic data table; automatically generating a custom metric query based on the information for creating the metric query and one or more predefined metric templates; creating the electronic data table based on the identifier of the electronic data table received in the metric request descriptor; applying the custom metric query to a data store storing a plurality of event records; extracting metric data from the data store based on the custom metric query; and storing the metric data in the electronic data table.

Abstract: A data management system predicts whether users will continue using the data management system. The data management system includes an analysis model that generates user retention prediction data based on time dependent user data and static user data. The analysis model also generates recommended actions to be taken by the data management system to increase the probability of retaining the user.

Abstract: A system, a method, and a computer program for remediating a vulnerability on a computing resource asset located in a computer network that has a plurality of other computing resource assets each having at last one vulnerability, where a Common Vulnerability Scoring System (CVSS) score is determined for the vulnerability. Vulnerability scanning results data corresponding to the computing resource asset can be analyzed and an environmental factor weighting score value determined for each of a plurality of environmentally-dependent factors. The environmental factor weighting score values and CVSS score can be aggregated and an adjusted environmental factor weighting score aggregate value generated. A prioritization score value for the vulnerability on the computing resource asset can be determined based on the adjusted environmental factor weighting score aggregate value and the vulnerability remediated on each of the computing resource assets according to the prioritization score value.

Abstract: Systems are provided for logging transactions in heterogeneous networks that include a combination of one or more instrumented components and one or more non-instrumented components. The instrumented components are configured to generate impersonated log records for the non-instrumented components involved in the transaction processing hand-offs with the instrumented components. The impersonated log records are persisted with other log records that are generated by the instrumented components in a transaction log that is maintained by a central logging system to reflect a complete flow of the transaction processing performed on the object, including the flow through the non-instrumented component(s).