Kd Secure LLC

Securenet Solutions Group LLC

Solarwinds Worldwide, LLC

Dnsstuff, Inc.

John J Donovan

Daniar Hussain

R Scott Perry

Paul D Parisi

Anish Dhanda

Danir Hussain

Charles K Stefanidakis

Gregory Sabatino

Richard Person

One embodiment comprises a non-transitory storage medium storing program code to receive one or more sensory events from a sensory event analytics module that receives sensory data about a physical environment from one or more sensors and processes the sensory data from the one or more sensors to detect the one or more sensory events. The one or more sensors include at least an Internet Protocol (IP) video camera. The one or more sensory events include one of a face detected, a vehicle detected, and a license plate detected. The program code includes code to store the sensory events for later retrieval as stored sensory events; and evaluate one or more historical correlations among the stored sensory events by evaluating the stored sensory events for the one or more historical correlations across at least one of time and space based on at least one weight vector.

Correlation engine for correlating sensory events utilizing weight vector

Monitoring systems and methods for use in security, safety, and business process applications utilizing a correlation engine are disclosed. Sensory data from one or more sensors are captured and analyzed to detect one or more events in the sensory data. The events are correlated by a correlation engine, optionally by weighing the events based on attributes of the sensors that were used to detect the primitive events. The events are then monitored for an occurrence of one or more correlations of interest, or one or more critical events of interest. Finally, one or more actions are triggered based on a detection of one or more correlations of interest, one or more anomalous events, or one or more critical events of interest. A hierarchical storage manager, having access to a hierarchy of two or more data storage devices, is provided to store data from the one or more sensors.

Correlation engine for correlating sensory events

Heirarchical data storage and correlation system for correlating and storing sensory events in a security and safety system

Monitoring systems and methods for use in security, safety, and business process applications utilizing a correlation engine are disclosed. Sensory data from one or more sensors are captured and analyzed to detect one or more events in the sensory data. The events are correlated by a correlation engine, optionally by weighing the events based on attributes of the sensors that were used to detect the primitive events. The events are then monitored for an occurrence of one or more correlations of interest, or one or more critical events of interest. Finally, one or more actions are triggered based on a detection of one or more correlations of interest, one or more anomalous events, or one or more critical events of interest. Events may come from sensory devices, legacy systems, third-party systems, anonymous tips, and other data sources. The present invention may be used to increase business productivity by improving security, safety, and increasing profitability of business processes.

Correlation system for correlating sensory events and legacy system events

Systems and methods for correlating sensory events and legacy system events utilizing a correlation engine for security, safety, and business productivity

Systems and methods for correlating data from IP sensor networks for security, safety, and business productivity applications

The present invention is a correlation engine for use in security, safety, and business monitoring applications. Sensory data from one or more sensors are captured and analyzed to detect one or more events in the sensory data. The events are correlated by the correlation engine by weighing the events based on attributes of the sensors that were used to detect the primitive events. The events are then monitored for an occurrence of one or more correlations of interest. Finally, one or more actions are triggered based on a detection of one or more anomalous events or events of interest. Events may come from sensory devices, legacy systems, third-party systems, anonymous tips, and other data sources. The present invention may be used to increase business productivity by improving security, safety, and increasing profitability of business processes.

Correlation engine for security, safety, and business productivity

This invention is a system, method, and apparatus for detecting compromise of IP devices that make up an IP-based network. One embodiment is a method for detecting and alerting on the following conditions: (1) Denial of Service Attack; (2) Unauthorized Usage Attack (for an IP camera, unauthorized person seeing a camera image); and (3) Spoofing Attack (for an IP camera, unauthorized person seeing substitute images). A survey of services running on the IP device, historical benchmark data, and traceroute information may be used to detect a possible Denial of Service Attack. A detailed log analysis and a passive DNS compromise system may be used to detect a possible unauthorized usage. Finally, a fingerprint (a hash of device configuration data) may be used as a private key to detect a possible spoofing attack. The present invention may be used to help mitigate intrusions and vulnerabilities in IP networks.

Systems, methods, and devices for detecting security vulnerabilities in IP networks

The present invention is a process monitoring method, comprising the steps of capturing sensory data from one or more sensors; storing the sensory data from the one or more sensors in a data storage device; processing the sensory data from the sensors to detect primitive events in the sensory data; correlating two or more primitive events to determine one or more correlated events; and performing one or more actions based on the correlation performed in the correlating step, including sending alerts to recipients in a company's hierarchy. The process monitoring method can be used with a variety of sensors, including temperature, pressure, revolutions per minute, electrical meters, altitude meters, and speedometers, and can accept input from a variety of legacy systems, including financial systems, inventory systems, personnel systems, currency systems, and law enforcement databases. The invention can be used to optimize business processes and ensure safety and security procedures are followed.

Systems, methods, and apparatus for monitoring and alerting on large sensory data sets for improved safety, security, and business productivity

The present invention is a method to ensure business processes are followed, comprising the steps of capturing sensory data from one or more sensors; storing the sensory data from the one or more sensors in a data storage device; processing the sensory data from the sensors to detect primitive events in the sensory data using a computer processor; correlating two or more primitive events, weighted by attribute data representing information about the sensors used to sense the primitive events, to determine one or more correlated events using the computer processor; and performing one or more actions to ensure business processes are followed based on the correlation performed in the correlating step.

Systems and methods for business process monitoring

The present invention is a safety and business productivity system having the following components. One or more cameras capture video data having attribute data, the attribute data representing importance of the cameras. One or more video analytics devices process the video data from one or more of the cameras and detect primitive video events in the video data. A correlation engine correlates two or more primitive video events from the video analytics devices weighted by the attribute data of the cameras used to capture the video data. An alerting engine generates one or more alerts and performs one or more actions based on the correlation performed by the correlation engine.

Systems and methods for safety and business productivity

The present invention is a video surveillance, storage, and alerting system having the following components. One or more surveillance cameras capture video data having attribute data, the attribute data representing importance of the surveillance cameras. One or more video analytics devices process the video data from one or more of the surveillance cameras and detect primitive video events in the video data. A network management module monitors network status of the surveillance cameras, and the video analytics devices, and generates network events reflective of the network status of all subsystems. A correlation engine correlates two or more primitive video events from the video analytics devices weighted by the attribute data of the surveillance cameras used to capture the video data, and network events from the network management module weighted by attribute data of device corresponding to the network event. An alerting engine generates one or more alerts and performs one or more actions based on the correlation performed by the correlation engine.

Hierarchical storage manager (HSM) for intelligent storage of large volumes of data

An audio surveillance, storage, and alerting system, including the following components: One or more audio sensory devices capture audio data having attribute data representing importance of the audio sensory devices. One or more audio analytics devices process the audio data to detect audio events. A network management module monitors network status of the audio sensory devices and generates network events reflective of the network status of all subsystems. A correlation engine correlates two or more events weighted by the attribute data of the device used to capture the data. Finally, an alerting engine generates one or more alerts and performs one or more actions based on the correlation performed by the correlation engine. This invention may be used to help fight crime and help ensure safety procedures are followed.

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Hamilton, MA, United States of America

John J Donovan