Manimaran Sundaravel

Title: Innovations by Manimaran Sundaravel

Introduction

Manimaran Sundaravel is an accomplished inventor based in Chennai, India. He has made significant contributions to the field of technology, particularly in the areas of software container deployment and network intrusion detection. With a total of 2 patents, his work showcases a blend of innovation and practical application.

Latest Patents

One of his latest patents is titled "Monitor and control toxic configuration in container deployment." This invention discloses systems and processes designed to monitor and control toxic configurations in software container deployment. An AI-based monitor in each node provides an end-to-end fault management system that can detect, diagnose, classify, and suggest remediation actions for non-virtualized cloud-based misconfiguration vulnerabilities. Anomalies are diagnosed using pre-computed fault signatures, and automated remediation is integrated with a cloud management stack. Multiple monitoring layers within nodes secure the container-based virtualization environment. The container-based 'CSTC security framework' virtualization technology provides security and identifies potential toxic configuration threats. CSTC security locates container-based systems at severe risk for DDoS attacks to kernel vulnerability/container breakout and ensures appropriate privilege configuration for user processes. Resource access is limited based on policies and CSTC security profiles, as well as providing AI-based monitoring of container runtime behavior to ensure safety and protection in container-based virtualization.

Another notable patent is the "System and method for network intrusion detection using a neural network implemented by a cloud computing system." This method includes intercepting requests, which are analyzed to identify authenticated and suspicious requests. The suspicious requests are grouped into request groups based on respective geolocation information. A rate of requests is determined for a request group. In response to determining that the rate of requests is less than or equal to a request rate threshold, parameters of a suspicious request of the request group are analyzed to determine values of the parameters. If the values do not match with respective malicious parameter values stored in a block list, the suspicious request is analyzed using a neural network to identify if it is legitimate or malicious. If identified as malicious, a notification is sent, and the values of the parameters are added to the block list.

Career Highlights

Manimaran Sundaravel is currently employed at Bank of America Corporation, where he applies his expertise in technology and innovation. His work focuses on enhancing security measures and improving system efficiencies through his patented technologies.

Collabor