MUMBAI, India, Sept. 28 -- Intellectual Property India has published a patent application (202611099208 A) filed by Ms. Ramanan Sathiaseelan on August 17, 2026, for Predictive Ai-Based Cloud Security Posture Management And Automated Risk Remediation System.
Inventor includes Ms. Ramanan Sathiaseelan.
The application for the patent was published on September 25, 2026, under issue no. 39/2026.
Abstract: A system and method are disclosed for predictive artificial intelligence based management of cloud security posture together with automated remediation of identified risks. The system collects configuration data, operational telemetry, identity, network traffic, and external threat information from one or more cloud computing platforms. The collected data is normalized into a temporal model that captures the relationships between resources as well as the resource lifecycle common to dynamically allocated and de-allocated cloud infrastructure. The predictive artificial intelligence engine analyzes the normalized data to predict future security posture states for a given time horizon. The engine combines models that learn from historic security events and models that identify anomalous patterns to detect potential configuration weaknesses, exposure, or other issues that could lead to compromised assets or unauthorized information disclosure. The identified risks are then scored and prioritized by a contextual prioritization module based on factors including but not limited to asset criticality, exposure scope, likelihood of exploitation given the current environment and defenses, and the degree to which the risk has been mitigated or compensated. These risk scores are continuously updated as new information becomes available, enabling the system to focus repair efforts on the issues with the largest potential impact. For each prioritized risk that qualifies for automated resolution, an appropriate remediation sequence is retrieved from a policy constrained action library. Each candidate remediation sequence is then validated in a digital twin of the production infrastructure to ensure that it will not have unintended consequences before being applied via the relevant cloud platform management APIs to the production infrastructure. Automated remediation actions are monitored and can be rolled back if unexpected effects are observed. The outcomes of both automated and manually initiated remediation actions are then reflected back into the system to inform future predictions and prioritizations. The system is capable of operating in multi-cloud and hybrid cloud environments by abstracting the implementation details specific to each cloud platform. Complete audit trails are maintained for all predictions, prioritizations, simulations, and remediations, supporting forensic reconstruction of every step taken by the system. The system handles ephemeral and serverless infrastructure by capturing information relevant to their short-lived nature and maintaining appropriate baselines for comparison and analysis. By combining continuous observation, predictive analysis, contextual prioritization, guarded automation, and complete audit trails, the invention enables organizations to reduce the mean time to repair security posture weaknesses while also reducing the operational burden of cloud operations security and control maintenance.
Disclaimer: Curated by HT Syndication.
