Abstract: An approach is provided that logs radio frequency (RF) activity detected by a vehicle-based intrusion detection system. The logged activity is ingested at a machine learning system. The approach receives, by a conversational agent with access to the machine learning system, natural language (NL) user queries pertaining to the detected RF activity and presents, by the conversational agent, natural language system responses answering the NL user queries.

Abstract: A method includes: scheduling a job submitted by a user to be executed on at least a portion of a computing infrastructure; determining a level of sanity check to be performed on the job; performing the sanity check on the job while waiting for the job to be executed; when the sanity check shows that the job will not successfully execute, estimating at least one time required to repair the job such that the job will successfully execute; finding whether the estimated time to repair the job exceeds an estimated time remaining before the job is scheduled to be executed; and when the estimated time to repair the job is found to exceed the estimated time remaining before the job is scheduled to be executed, rescheduling the job such that the estimated time remaining before the job is scheduled to be executed exceeds the estimated time to repair the job.

Abstract: An approach is provided that logs radio frequency (RF) activity detected by a vehicle-based intrusion detection system. The logged activity is ingested at a machine learning system. The approach receives, by a conversational agent with access to the machine learning system, natural language (NL) user queries pertaining to the detected RF activity and presents, by the conversational agent, natural language system responses answering the NL user queries.

Abstract: An approach is provided that receives radio frequency (RF) requests at a vehicle. The approach determines that the received request is a possible unauthorized intrusion. The approach then responsively transmits a confirmation request to a mobile device associated with an authorized user of the vehicle and safeguards the vehicle until a positive confirmation is received at the vehicle from the mobile device.

Abstract: A method includes: scheduling a job submitted by a user to be executed on at least a portion of a computing infrastructure; determining a level of sanity check to be performed on the job; performing the sanity check on the job while waiting for the job to be executed; when the sanity check shows that the job will not successfully execute, estimating at least one time required to repair the job such that the job will successfully execute; finding whether the estimated time to repair the job exceeds an estimated time remaining before the job is scheduled to be executed; and when the estimated time to repair the job is found to exceed the estimated time remaining before the job is scheduled to be executed, rescheduling the job such that the estimated time remaining before the job is scheduled to be executed exceeds the estimated time to repair the job.