Xenia Mountrouidou
Xenia Mountrouidou

Senior Security Researcher

Xenia Mountrouidou is a Senior Security Researcher at Cyber adAPT with versatile experience in academia and industry. She has over 10 years of research experience in network security, machine learning, and data analytics for computer networks. She enjoys researching novel intrusion detection techniques, finding interesting patterns with machine learning algorithms, and writing Python scripts to automate boring tasks. Her research interests revolve around network security, Internet of Things, intrusion detection, and machine learning.

She has authored scholarly papers in the areas of network security and machine learning. She has presented her work at academic and industry conferences such as USENIX Security, IEEE Big Data, BSides Security, and Interop.

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Interests
  • Machine Learning for Security
  • Intrusion Detection Systems
  • Network Security
  • IoT Security
  • Data Science
Education
  • PhD in Computer Science

    North Carolina State University

  • M.S. in Computer Engineering

    University of Patras

  • B.S. in Computer Science

    University of Crete

đź“š My Research
I am a Security Researcher working in the intersection of Machine Learning and Security. My work focuses on leveraging ML to detect abnormal network behavior and strengthen defenses against evolving threats. I am particularly driven by the challenge of building robust, secure ML models while uncovering and addressing their vulnerabilities. My primary research interests include Network Security, IoT security, and Offensive Machine Learning, where I explore innovative solutions to safeguard modern cyber ecosystems.
Selected Publications
(2021). IoT Metrics and Automation for Security Evaluation. In IEEE CCNC 2021.
(2021). Worth the wait? Time window feature optimization for intrusion detection. In IEEE Cyberhunt 2019.
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