Abstract: A multiple vehicle cyber-attack detection system including a vehicle operations center coupled to and monitoring vehicles, where each operations center includes a cyber-attack alert module. A vehicle cyber-attack detection system is in communication with each operations center and includes a first tier security module coupled to an onboard system of each vehicle and receives system log data generated by the onboard system. The first tier security module extracts extracted features from a time series of overlapping windowed system log data generated from the system log data with natural language processing and includes a first cyber-attack anomaly detection module that identifies a first cyber-attack based on system entropy measurements. A second cyber-attack anomaly detection module includes a deep learning component that identifies a second cyber-attack based on classification of the extracted features.

Abstract: Implementations directed to instantiating adapters for communication between a UAP and one or more RPA platforms, and include receiving, by an intelligent adapter service of the UAP, input representing an RPA platform of a plurality of RPA platforms, querying, by the intelligent adapter service, one or more files of the RPA platform to determine one or more identifiers of the RPA platform, selecting, by the intelligent adapter service, an adapter of a plurality of adapters based on the one or more identifiers of the RPA platform, installing, by the intelligent adapter service, the adapter, and configuring, by the intelligent adapter service, the adapter to be specific to the RPA platform, configuring including setting one or more parameters of the RPA platform.

Abstract: A system and method for reducing incident alerts for an enterprise environment are described. In one embodiment, a method of reducing incident alerts for an enterprise environment includes receiving a plurality of historical incident alerts associated with previous incidents associated with nodes within an enterprise environment. The method includes extracting from a first subset of the historical incident alerts a plurality of rules to generate a rule knowledge base and analyzing a second subset of the historical incident alerts against the plurality of rules to identify candidate incidents alerts as potential dead-end tickets. The method also includes providing feedback on the candidate incident alerts to confirm or deny that the alert is a dead-end ticket. Based on the feedback, a prescriptive avoidance rule set is generated to identify an incident alert as a dead-end ticket and eliminate the dead-end tickets from submitted incident alerts.

Abstract: A system for detecting and preventing an imminent failure in a target system includes an interface, a processor in communication with the interface, and non-transitory computer readable media in communication with the processor. The interface receives training data items. Each item corresponds to either a service ticket or a machine-generated log that specifies an issue and a resolution to the issue. The instruction code is executed by the processor and causes the processor to group the training data items according to different categories. For each group, the processor trains a model to match the issue of each item of the group with the corresponding resolution and associates a model configuration of the trained model with the category of the group. The processor receives a sequence of new data items that include service tickets or machine generated logs for which a resolution is unknown. The processor groups the new data items according to one or more categories.

Abstract: A system and method to intelligently formulate automation strategies for technology infrastructure operations are disclosed. The system and method include analyzing infrastructure issue data from support tickets and predicting automation solutions. A cost-benefit analysis is then performed on the automation solutions. Solutions can be ranked and recommended according to the cost-benefit analysis.

Abstract: A method for identifying and projecting recurrent event patterns in an Information Technology (IT) infrastructure is disclosed. The method includes deriving at least one time period based on historical events data; grouping the historical events data comprising a plurality of events based on the at least one time period to create a plurality of data points sets; creating an event corpus comprising each of the plurality of events arranged based on frequency of occurrence across the plurality of data points sets; identifying one or more events that have highest frequency of occurrence within the event corpus; determining one or more data points sets from the plurality of data points sets in which the one or more events have occurred; and computing a projected frequency of occurrence of the one or more events in future time periods.

Abstract: A system and method for reducing incident alerts for an enterprise environment are described. In one embodiment, a method of reducing incident alerts for an enterprise environment includes receiving a plurality of historical incident alerts associated with previous incidents associated with nodes within an enterprise environment. The method includes extracting from a first subset of the historical incident alerts a plurality of rules to generate a rule knowledge base and analyzing a second subset of the historical incident alerts against the plurality of rules to identify candidate incidents alerts as potential dead-end tickets. The method also includes providing feedback on the candidate incident alerts to confirm or deny that the alert is a dead-end ticket. Based on the feedback, a prescriptive avoidance rule set is generated to identify an incident alert as a dead-end ticket and eliminate the dead-end tickets from submitted incident alerts.

Abstract: A multiple vehicle cyber-attack detection system including a vehicle operations center coupled to and monitoring vehicles, where each operations center includes a cyber-attack alert module. A vehicle cyber-attack detection system is in communication with each operations center and includes a first tier security module coupled to an onboard system of each vehicle and receives system log data generated by the onboard system. The first tier security module extracts extracted features from a time series of overlapping windowed system log data generated from the system log data with natural language processing and includes a first cyber-attack anomaly detection module that identifies a first cyber-attack based on system entropy measurements. A second cyber-attack anomaly detection module includes a deep learning component that identifies a second cyber-attack based on classification of the extracted features.

Abstract: A system for detecting and preventing an imminent failure in a target system includes an interface, a processor in communication with the interface, and non-transitory computer readable media in communication with the processor. The interface receives training data items. Each item corresponds to either a service ticket or a machine-generated log that specifies an issue and a resolution to the issue. The instruction code is executed by the processor and causes the processor to group the training data items according to different categories. For each group, the processor trains a model to match the issue of each item of the group with the corresponding resolution and associates a model configuration of the trained model with the category of the group. The processor receives a sequence of new data items that include service tickets or machine generated logs for which a resolution is unknown. The processor groups the new data items according to one or more categories.

Abstract: Implementations directed to direct messaging between one or more robotic process automation (RPA) platforms, and an autonomic platform (AP), and include actions of receiving, by a platform-specific adapter of the AP, data from a RPA platform of a plurality of RPA platforms the AP interacts with, the data indicating occurrence of a scenario, providing, by an application programming interface (API) of the platform-specific adapter, an occurrence message responsive to the occurrence of the scenario, transmitting, by the API, the message to the AP through a first channel, and transmitting, by the platform-specific adapter, a set of messages to the AP through a second channel that is separate from the first channel, the set of messages communicating tagged data records.

Abstract: A system and method to intelligently formulate automation strategies for technology infrastructure operations are disclosed. The system and method include analyzing infrastructure issue data from support tickets and predicting automation solutions. A cost-benefit analysis is then performed on the automation solutions. Solutions can be ranked and recommended according to the cost-benefit analysis.

Abstract: A vehicle cyber-attack detection system includes at least one first tier security module coupled to at least one onboard system of a respective vehicle and being configured so as to receive system log data generated by the at least one onboard system of the respective vehicle. The first tier security module extracts extracted features from the system log data with natural language processing and includes a first cyber-attack anomaly detection module that identifies a first cyber-attack based on system entropy measurements determined from the extracted features, and a second cyber-attack anomaly detection module that includes a deep learning component that identifies a second cyber-attack based on classification of the extracted features. A cyber-attack alert module is coupled to the first tier security module for generating a notification of one or more of the first cyber-attack and the second cyber-attack to effect cyber-attack diagnostics and remediation by vehicle personnel.

Abstract: Implementations directed to direct messaging between one or more robotic process automation (RPA) platforms, and an autonomic platform (AP), and include actions of receiving, by a platform-specific adapter of the AP, data from a RPA platform of a plurality of RPA platforms the AP interacts with, the data indicating occurrence of a scenario, providing, by an application programming interface (API) of the platform-specific adapter, an occurrence message responsive to the occurrence of the scenario, transmitting, by the API, the message to the AP through a first channel, and transmitting, by the platform-specific adapter, a set of messages to the AP through a second channel that is separate from the first channel, the set of messages communicating tagged data records.

Abstract: Implementations directed to instantiating adapters for communication between a UAP and one or more RPA platforms, and include receiving, by an intelligent adapter service of the UAP, input representing an RPA platform of a plurality of RPA platforms, querying, by the intelligent adapter service, one or more files of the RPA platform to determine one or more identifiers of the RPA platform, selecting, by the intelligent adapter service, an adapter of a plurality of adapters based on the one or more identifiers of the RPA platform, installing, by the intelligent adapter service, the adapter, and configuring, by the intelligent adapter service, the adapter to be specific to the RPA platform, configuring including setting one or more parameters of the RPA platform.

Abstract: Systems and methods for valuating automation are described. The system computes plurality of parameters associated with process. The plurality of parameters comprises time related parameters and cost related parameters. Further, the system determines a total actual cost saved when an automation is applied on the process based on the time related parameters and the cost related parameters. The system further normalizes the total actual cost saved based on the cost related parameters and a cost of automation maintenance. Further, the system determines a value of the automation based on the total actual cost saved after normalization, qualitative parameters associated with the process and the cost of automation maintenance. The value is categorized into at least one of an automate category, a neutral category and a non-automate category. Based on the categorization, the system selects only relevant automations in order to reduce overload of running unnecessary automations, thereby improving system's performance.

Abstract: A vehicle cyber-attack detection system includes at least one first tier security module coupled to at least one onboard system of a respective vehicle and being configured so as to receive system log data generated by the at least one onboard system of the respective vehicle. The first tier security module extracts extracted features from the system log data with natural language processing and includes a first cyber-attack anomaly detection module that identifies a first cyber-attack based on system entropy measurements determined from the extracted features, and a second cyber-attack anomaly detection module that includes a deep learning component that identifies a second cyber-attack based on classification of the extracted features. A cyber-attack alert module is coupled to the first tier security module for generating a notification of one or more of the first cyber-attack and the second cyber-attack to effect cyber-attack diagnostics and remediation by vehicle personnel.

Abstract: System and method for optimizing event alerts in an information technology (IT) infrastructure management system are disclosed. In one embodiment, the method comprises tracking one or more event alerts triggered by monitoring tools. The method further comprises determining a probable usage for at least one configuration item associated with the one or more event alerts. The method further comprises determining a probable threshold value for each of the at least one configuration item based on the probable usage and capacity data. The method further comprises computing a final threshold value for each of the at least one configuration item based on the probable threshold value, seasonality data, or semantic context data. The method further comprises optimizing the event alerts by filtering at least one unwanted event alert from the one or more event alerts based on at least one of the final threshold value and filtering rules.

Abstract: In one embodiment, an access management system for dynamically managing access to one or more devices for resolution of an incident ticket associated with the one or more devices is disclosed. The access management system comprises a processor and a memory communicatively coupled to the processor. The memory stores processor instructions, which, on execution, causes the processor to identify an incident ticket type by analyzing data associated with the incident ticket. The processor is caused to determine one or more access parameters based on the incident ticket type. The one or more access parameters comprises a device type, an application software run on a device, a system software run on a device, a security privilege to access the device, and time duration to access the device. Further, the processor is caused to provide the access to the one or more devices based on the one or more access parameters.

Abstract: A system and method for classifying and resolving software production incident tickets includes receiving an incident ticket, extracting a plurality of keywords from the incident ticket, and deriving a query vector corresponding to the incident ticket based on the plurality of keywords. The system and method further comprises classifying the incident ticket into at least one of a positive mechanization incident ticket and a negative mechanization incident ticket based on a comparison of the query vector and a plurality of vectors derived from a plurality of past incident tickets. The plurality of vectors are derived based on a plurality of keywords and their corresponding occurrences in the plurality of past incident tickets.

Abstract: A method for identifying and projecting recurrent event patterns in an Information Technology (IT) infrastructure is disclosed. The method includes deriving at least one time period based on historical events data; grouping the historical events data comprising a plurality of events based on the at least one time period to create a plurality of data points sets; creating an event corpus comprising each of the plurality of events arranged based on frequency of occurrence across the plurality of data points sets; identifying one or more events that have highest frequency of occurrence within the event corpus; determining one or more data points sets from the plurality of data points sets in which the one or more events have occurred; and computing a projected frequency of occurrence of the one or more events in future time periods.