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AssigneeInternational Business Machines Corporation
InventorsRavi Krishnan Muthukrishnan, Jeffrey Robert Hoy, Sreekanth Ramakrishna Iyer, Kaushal Kiran Kapadia, Nataraj Nagaratnam
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A user state tracking and anomaly detector for multi-tenant SaaS applications operates in association with a log management solution, such as a SIEM. A given SaaS application has many user STATES, and the applications often have dependencies on one another that arise, for example, when a particular application makes a request (typically on behalf of a user) to take some action with respect to another application. The detector includes a mapper that maps the large number of user STATES to a reduced number of mapped states (e.g., “red” and “green”), and a dependency module that generates user-resource dependency graphs. Using a dependency graph, a SaaS modeler in the detector checks whether a particular dependency-based request associated with a SaaS application is valid. State and dependency information generated by the mapper and dependency module are reported back to the log management solution to facilitate improved logging and anomaly detection.
A method for improving a log management system in a Software-As-A-Service (SaaS) environment having a plurality of cloud applications, the log management system normally configured to consolidate log source event data to detect anomalies, comprising:
Apparatus, comprising:
A computer program product in a non-transitory computer readable medium for use in a data processing system, the computer program product holding computer program instructions executed by the data processing system to improve a log management system in a Software-As-A-Service (SaaS) environment having a plurality of cloud applications, the log management system normally configured to consolidate log source event data to detect anomalies, the computer program instructions comprising program code operative to:
Dependencies are inferred from the claim text.