Marie Louise Uwibambe

Researcher

University of Arkansas at Fayetteville

unknown

2 h-index 5 pubs 9 cited

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Biography and Research Information

OverviewAI-generated summary

Marie Louise Uwibambe's research focuses on enhancing the security of industrial control systems, particularly within operational technology environments. Her work investigates methods for optimizing vulnerability remediation and detecting silent crashes in power grid control devices. Uwibambe has developed a fuzzing framework specifically designed for Programmable Logic Controller (PLC) control logic, aiming to safeguard industrial automation systems. She has also explored the application of reinforcement learning to improve input mutation techniques in fuzzing processes.

Her recent publications address the intersection of artificial intelligence tools like ChatGPT with vulnerability management, highlighting both benefits and drawbacks. Collaborations with Kylie McClanahan and Yanjun Pan at the University of Arkansas at Fayetteville have contributed to shared publications in these areas. Uwibambe's scholarly output includes 5 publications with an h-index of 2 and 9 total citations.

Metrics

  • h-index: 2
  • Publications: 5
  • Citations: 9

Selected Publications

  • Optimizing the Selection of Vulnerability Remediation Actions in Operational Technology Environments (2025) DOI
  • A Reinforcement Learning Approach to Multi-Parametric Input Mutation for Fuzzing (2025) DOI
  • Safeguarding Industrial Automation: A Fuzzing Framework for PLC Control Logic (2025) DOI
  • When ChatGPT Meets Vulnerability Management: The Good, the Bad, and the Ugly (2024) DOI
  • Fuzzing for Power Grids: A Comparative Study of Existing Frameworks and a New Method for Detecting Silent Crashes in Control Devices (2023) DOI

Collaborators

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