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With current technological advancements, the need for resources in computing systems becomes evident. The general public often finds it difficult to check whether their system or computer is functioning perfectly, and even more challenging to identify if it is under a cyberattack. Therefore, a monitoring tool is necessary to reduce the threats to which a user could be exposed. Based on this premise, we developed a web platform that detects any process that exceeds the parameterizable threshold of fifty percent CPU usage and that could compromise the integrity of the system. In addition to monitoring the system’s active processes, the platform stops those that exceed the established limit, as long as they are not user processes. We use the agile SCRUM methodology to optimize development and Python with Flask for the backend. The platform sends the information to a cloud database like MongoDB Atlas, which uses artificial intelligence to generate a detailed report of the problem, allowing for early decision-making. In this way, we complemented the web interface developed in React with Vite. The results show a functional, easily accessible system optimized for Linux and Windows, with an intuitive and responsive interface to improve the user experience.

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An Implementation of a Web-Based Resource Monitoring Platform to Detect Cyberattacks Based on Massive Process Floods

  • 会议论文

  • 发表日期：

    2026年

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  • Yeshua Chiliquinga,
  • Andrés Espín,
  • José Sanmartín,
  • Walter Fuertes

摘要

With current technological advancements, the need for resources in computing systems becomes evident. The general public often finds it difficult to check whether their system or computer is functioning perfectly, and even more challenging to identify if it is under a cyberattack. Therefore, a monitoring tool is necessary to reduce the threats to which a user could be exposed. Based on this premise, we developed a web platform that detects any process that exceeds the parameterizable threshold of fifty percent CPU usage and that could compromise the integrity of the system. In addition to monitoring the system’s active processes, the platform stops those that exceed the established limit, as long as they are not user processes. We use the agile SCRUM methodology to optimize development and Python with Flask for the backend. The platform sends the information to a cloud database like MongoDB Atlas, which uses artificial intelligence to generate a detailed report of the problem, allowing for early decision-making. In this way, we complemented the web interface developed in React with Vite. The results show a functional, easily accessible system optimized for Linux and Windows, with an intuitive and responsive interface to improve the user experience.