Collection
AI Meets Cybersecurity
Cyberspace has completely revolutionized our ways of life, prompting important progress in science and technology. However, the advantages of cyberspace are now threatened by the systemic risk of proliferation of offensive cyber-tools and cyber-operations. Cybersecurity is the practice of securing networks, systems and any other digital infrastructure from malicious attacks. Traditional cybersecurity relies on the static control of security cyberspace monitoring according to pre-specified rules. However, this passive and reactive defense methodology is no longer useful in protecting cyberspace against new cybersecurity threats.
AI technologies, such as deep learning, have been recently introduced into cybersecurity to construct smart models for implementing malware classification, intrusion detection, vulnerability and threat discovery. By the same logic, it is important to consider that AI can be used also by attackers to continually improve their techniques and refine their offensive capabilities. Studying the effectiveness of both Defensive and Offensive AI is thus critical to ensure modern cybersecurity equipped to face the emerging threats allowed by malicious uses of AI.
The focus of this special issue of the Journal of Intelligent Information Systems is to explore the impact of AI on modern cybersecurity, for better and for worse. It aims to showcase new research focusing on how attackers can use AI to augment the attack kill chain, as well as the ways in which defenders are evolving AI-based cybersecurity to respond to these new and unprecedented threats.
Editors
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Giuseppina Andresini
Giuseppina Andresini currently serves as Research Fellow in the Knowledge Discovery & Data Engineering research group within the University of Bari Aldo Moro Department of Computer Science. Her current research interests include Data Mining and Knowledge Discovery, Cybersecurity, Intrusion detection, Big Data Analytics, and Deep learning.
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Annalisa Appice
Annalisa Appice is an Assistant Professor of Computer Science at the University of Bari Aldo Moro. Her current research interests include Clustering, Association Rule Discovery, Associative Classification, (multi)Relational Data Mining, Data Stream Mining, Map Interpretation and Spatial Data Mining, Data Mining Query Language.
Articles (7 in this collection)
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Leveraging siamese networks for one-shot intrusion detection model
Authors (first, second and last of 8)
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Machine learning in industrial control system (ICS) security: current landscape, opportunities and challenges
Authors (first, second and last of 4)
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