Intrusion and Detection Systems for Wired and Wireless Network Application

@article{1710550,
      author = {Oketayo Abimbola, Nriagu C. Ogonna, Oduwole Oluwakemi O.},
      title = {Intrusion and Detection Systems for Wired and Wireless Network Application},
      journal = {Iconic Research And Engineering Journals},
      year = {2025},
      volume = {9},
      number = {3},
      pages = {2317-2324},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1710550.pdf},
      abstract = {The proliferation of wired and wireless networks has increased the risk of cyber threats, making intrusion detection systems (IDS) crucial for network security. This research focuses on designing and developing advanced IDS for both wired and wireless network applications. We explore various machine learning and deep learning techniques to detect and prevent intrusions, including anomaly-based and signature-based detection methods. Our system aims to improve detection accuracy, reduce false positives, and enhance network security. The proposed IDS can be applied to various network environments, including IoT, cloud computing, and industrial control systems. This research contributes to the development of robust and efficient IDS for protecting wired and wireless networks from cyber threats.},
      keywords = {Intrusion Detection Systems, Network Security, Machine Learning, Deep Learning, Wired Networks, Wireless Networks, Cyber Threats.},
      month = {September},
      doi = {https://doi.org/10.64388/IREV9I3-1710550}
  }