Inventor

JEYAKUMAR VIMALKUMAR

US38 patents

⚠️ This page may combine multiple inventors who share the name “JEYAKUMAR VIMALKUMAR”. Patents are grouped by organization below to help distinguish them — per-person disambiguation is on the roadmap.

JEYAKUMAR VIMALKUMAR

CISCO TECH INC

MDL-based clustering for dependency mapping

MDL-based clustering for application dependency mapping

Optimizations for application dependency mapping

Augmenting flow data for improved network monitoring and management

Round trip time (RTT) measurement based upon sequence number

Round trip time (RTT) measurement based upon sequence number

Cluster discovery via multi-domain fusion for application dependency mapping

System for monitoring and managing datacenters

MDL-based clustering for dependency mapping

System for monitoring and managing datacenters

System for monitoring and managing datacenters

System and method for network information mapping and displaying

System and method for user optimized application dependency mapping

Synthetic data for determining health of a network security system

Generate a communication graph using an application dependency mapping (ADM) pipeline

Round trip time (RTT) measurement based upon sequence number

Synthetic data for determining health of a network security system

Creating classifiers for servers and clients in a network

System for monitoring and managing datacenters

System and method for user optimized application dependency mapping

Round trip time (RTT) measurement based upon sequence number

Round trip time (RTT) measurement based upon sequence number

Server-client determination

System for monitoring and managing datacenters

LACEWORK INC

Using activity monitored by multiple data sources to identify shadow systems

User-specific data-driven network security

Elastic privileges in a secure access service edge

Generating user-specific polygraphs for network activity

Detecting deviations from typical user behavior

Handling of certificates by intermediate actors

Detecting anomalous behavior of a device

Establishing a location profile for a user device

FORTINET INC

Risk scoring based on entity correlation

Browser-based detection of data exfiltration

Location-based identification of anomalous activity on a user device

Monitoring the usage of an application at an edge device

Determining user risk based on user posture and activity

Distinguishing user-initiated activity from application-initiated activity