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All Journal International Journal of Electrical and Computer Engineering
Islam, A. H. M. Saiful
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Computer Science & IT Electrical & Electronics Engineering

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IDPS: A machine learning framework for real-time intrusion detection and protection system for malicious internet activity Fabiha, Raisa; Reberio, Stein Joachim; Farazi, Zubayer; Nur, Fernaz Narin; Sultana, Shaheena; Islam, A. H. M. Saiful
International Journal of Electrical and Computer Engineering (IJECE) Vol 16, No 1: February 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v16i1.pp437-449

Abstract

With the increasing frequency and complexity of cyber threats, there is a pressing need for effective real-time solutions to detect and prevent malicious activities. This study introduces a novel machine learning-based architecture for real-time cybersecurity to enhance accurate identification and prevention of malicious cyber activities. The proposed framework combines advanced machine learning algorithms with Wireshark network traffic analysis to effectively detect and classify a wide range of cyberattacks, providing timely and actionable insights to cybersecurity professionals. A core component of this system is a prototype blocker, which is seamlessly integrated with Cisco infrastructure, enabling proactive intervention by blocking suspicious IP addresses in real-time. In addition, a user-friendly web application enhances system operability by offering intuitive data visualization and analytical tools, enabling rapid and informed decision-making. This comprehensive approach not only strengthens network security and protects digital assets but also equips defenders with the capability to respond effectively to the dynamic landscape of cyber threats.
Co-Authors Fabiha, Raisa Farazi, Zubayer Nur, Fernaz Narin Reberio, Stein Joachim Sultana, Shaheena