Qomplx, Inc.

Fractal Industries, Inc.

Ian MacLeod

Jason Crabtree

Andrew Sellers

Daniel Fricano

Angad Salaria

John Uchiyama

Nhan Tran

Sethan Arja

Shadrack Antwi

Rajat Gupta

Penelope Brooks

A system for risk-based multi-factor authentication having a multi-dimensional time series data server configured to monitor and record a network's traffic data and to serve the traffic data to other modules and a directed computation graph module configured to receive network traffic data from the multi-dimensional time series data server, determine a network traffic baseline from the network traffic data, and determine a verification score needed before granting access based at least in part by the network traffic baseline. A plurality of verification methods build up a user's verification score to required level to gain access.

Risk-based multi-factor authentication

A system for dynamic predictive analysis of data sets using an actor-driven distributed computational graph, wherein a pipeline orchestrator creates and manages individual data pipelines while providing data caching to enable interactions between specific activity actors within pipelines. Each pipeline then comprises a pipeline manager that creates and manages individual activity actors and directs operations within the pipeline while reporting back to the pipeline orchestrator.

Dynamic predictive analysis of data sets using an actor-driven distributed computational graph

A system for contextual and risk-based multi-factor authentication having a multi-dimensional time series data server configured to monitor and record a network's traffic data and to serve the traffic data to other modules and a directed computation graph module configured to receive network traffic data from the multi-dimensional time series data server, determine a network traffic baseline from the network traffic data, and determine a verification score needed before granting access based at least in part by the network traffic baseline. A plurality of verification methods build up a user's verification score to required level to gain access.

Contextual and risk-based multi-factor authentication

A system for mitigation of cyberattacks employing an advanced cyber decision platform which uses a time series data store, a directed computational graph module, an action outcome simulation module, and observation and state estimation module, wherein the state of a network is monitored and used to produce a cyber-physical graph representing network resources, simulated network events are produced and monitored, and the network events and their effects are analyzed to produce security recommendations.

Application of advanced cybersecurity threat mitigation to rogue devices, privilege escalation, and risk-based vulnerability and patch management

A cybersecurity system that protects against cyber attacks by performing user and device behavioral analysis using an advanced cyber decision platform which creates a map of users and devices attached to a network, develops a baseline of expected interactions and behaviors for each user and device in the map, and monitors deviations from the expected interactions and behaviors.

User and entity behavioral analysis using an advanced cyber decision platform

A system for automated cyber physical threat campaign analysis and attribution, comprising a multi-dimensional time series and graph hybrid data server, an automated planning service module, and a directed computation graph module. A dataset is gathered from a monitored network and aggregated into a cyber-physical systems graph. Cyberattack simulations on the monitored network are made using exogenously collected data as input. Metrics are generated based on the cyber-physical systems graph and results from the cyberattack simulations, and the generated metrics are used to develop a threat profile.

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Arlington, VA, United States of America

Ian MacLeod