# of Displayed Technologies: 4 / 4


A Cybersecurity Vulnerability Prioritization System Including Identifying "Super-Critical" Vulnerabilities, predicting "Dark Host" Vulnerabilities, and Addressing Economic Costs
TS-066063 — Our cybersecurity vulnerability maintenance system stands as a pillar of modern security strategy, transforming reactive security measures into a preemptive defense mechanism. This integration of technology and economics ensures that your most critical assets are protected efficiently and effectively, making it an invaluable tool for any organization serious about security.
In today’s hyper-connected world, the escalation in cyber threats poses significant risks to organizational data and systems. Vulnerabilities within network infrastructures can lead to massive security breaches, as demonstrated by incidents like the 2017 Equifax hack. Effective vulnerability…
  • College: College of Engineering (COE)
  • Inventors: Allen, Theodore; Liu, Enhao
  • Licensing Officer: Zinn, Ryan

Learning Optimal Empirical Reward iNtelligence (LOERN) with Cyber Maintenance Applications
TS-040341 — A software solution designed to optimize cyber security decision making and reduce maintenance costs.
As the world becomes more and more connected, our systems become more and more vulnerable. If cyber security can become more automated, risk-based decisions can be made more quickly and rationally. Organizations can then leverage this decision-making to improve their security without increasing co…
  • College: College of Engineering (COE)
  • Inventors: Allen, Theodore; Hou, Chengjun
  • Licensing Officer: Zinn, Ryan

TS-037930 — Data-Driven Inspection, Alerts, Maintenance, Observable Network Decision Control System with Cyber Action Taker to Address Less Inspected Hosts Including Cell Phones
Cyber security is an important facet of many major corporations and government entities. The implementation of effective cyber security protocols is an arduous process because the most targeted individuals, C-suite and boardroom level personnel, understand the protocols the least. A lack of adhere…
  • College: College of Engineering (COE)
  • Inventors: Allen, Theodore; RoyChowdhury, Sayak
  • Licensing Officer: Zinn, Ryan

Subject Matter Expert Refined Topic Models
TS-015175 — Human-Assisted Modeling (HAM), Subject Matter Expert Refined Models (SMERM), and Subject Matter Expert Refined Topic (SMERT) Models.
Currently, unstructured data represents up to 80% of the data within an organization. This means the traditional data, such as sales figures or other statistics, are separated into different documents without a meaningful and effective way to aggregate the data. Due to this there is now an opportu…
  • College: College of Engineering (COE)
  • Inventors: Allen, Theodore; Xiong, Hui
  • Licensing Officer: Zinn, Ryan

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