Data-Driven Intelligence Can Revolutionize Today’s Cybersecurity World: A Position Paper

Sarker, Iqbal H.; Janicke, Helge; Maglaras, Leandros; Camtepe, Seyit

Abstract

As cyber threats evolve and grow progressively more sophisticated, cyber security is becoming a more significant concern in today’s digital era. Traditional security measures tend to be insufficient to defend against these persistent and dynamic threats because they are mainly intuitional. One of the most promising ways to handle this ongoing problem is utilizing the potential of data-driven intelligence, by leveraging AI and machine learning techniques. It can improve operational efficiency and saves response times by automating repetitive operations, enabling real-time threat detection, and facilitating incident response. In addition, it augments human expertise with insightful information, predictive analytics, and enhanced decision-making, enabling them to better understand and address evolving problems. Thus, data-driven intelligence could significantly improve real-world cybersecurity solutions in a wide range of application areas like critical infrastructure, smart cities, digital twin, industrial control systems and so on. In this position paper, we argue that data-driven intelligence can revolutionize the realm of cybersecurity, offering not only large-scale task automation but also assist human experts for better situation awareness and decision-making in real-world scenarios.

Citation

Sarker, I. H., Janicke, H., Maglaras, L., & Camtepe, S. (2023, October). Data-Driven Intelligence Can Revolutionize Today’s Cybersecurity World: A Position Paper. Presented at Third International Conference, ARTIIS 2023, Madrid, Spain

• Presentation Conference Type: Conference Paper (published)
• Conference Name: Third International Conference, ARTIIS 2023
• Start Date: Oct 18, 2023
• End Date: Oct 20, 2023
• Online Publication Date: Jan 3, 2024
• Publication Date: 2024
• Deposit Date: Jan 16, 2024
• Publisher: Springer
• Pages: 302-316
• Series Title: Communications in Computer and Information Science
• Series Number: 1936
• Series ISSN: 1865-0929
• Book Title: Advanced Research in Technologies, Information, Innovation and Sustainability (ARTIIS 2023), Proceedings, Part II
• ISBN: 978-3-031-48854-2
• DOI: https://doi.org/10.1007/978-3-031-48855-9_23
• Keywords: Cybersecurity, Data-Driven Intelligence, Automation, Human Assistance, Augmenting Experts Knowledge, AI, Machine Learning
• Public URL: http://researchrepository.napier.ac.uk/Output/3446046
• Related Public URLs: https://arxiv.org/pdf/2308.05126.pdf