A Review of Advanced Cyber Threat Detection Techniques in Critical Infrastructure: Evolution, Current State, and Future Directions

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@article{1706103,
      author = {Muritala Aminu, Ayokunle Akinsanya, Oyewale Oyedokun, Oladayo Tosin Akinwande},
      title = {A Review of Advanced Cyber Threat Detection Techniques in Critical Infrastructure: Evolution, Current State, and Future Directions},
      journal = {Iconic Research And Engineering Journals},
      year = {2024},
      volume = {8},
      number = {2},
      pages = {74-87},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1706103.pdf},
      abstract = {Cyber threats pose substantial risks to critical infrastructure, necessitating the development and implementation of advanced detection techniques to protect against possible attacks. This review examines the evolution, current state, and prospects of cyber threat detection techniques in critical infrastructure. Conventional signature-based approaches provided more sophisticated strategies like anomaly detection, machine learning algorithms, and behavior-based analysis in the evolution of cyber threat detection techniques. Although these techniques offer promising abilities in terms of identifying and reducing cyber threats, they also have several drawbacks, such as the speed at which threats are evolving, the complexity of environments involving critical infrastructure, and the vulnerabilities brought about by novel technologies. The future of cyber threat detection in critical infrastructure has the potential to improve resilience and lessen the risks posed by cyber threats in a world that is increasingly becoming digitally connected and interconnected by embracing emerging technologies and implementing proactive security strategies.},
      keywords = {Interconnectivity, Critical Infrastructure, Threat, Network Security, Safety},
      month = {August},
  }