A Disinformation Attack Risk Awareness Framework: A Case Study on Incidents Collected by DISARM Foundation
Abstract:
The diversity of disinformation attack strategies highlights the need for a thorough analysis of their impacts and related risks. To deal with them, this paper proposes an ontology-based framework for building knowledge about disinformation incidents, bridging Itemset Mining and Situational Awareness. The framework incorporates a High-Risk Itemset Mining algorithm that combines the frequency and fuzzy utility of attack pattern itemsets, allowing for deeper insights into attack tactics and a better assessment of their associated risks. Experiments conducted using DISARM Foundation dataset demonstrate the framework’s potential to identify the most relevant attack patterns and quantify their associated risks.
AUTHORS
Khoury College of Computer Science, Northeastern University,
Boston, Massachusetts, United States of America
Professor Kenneth Baclawski's research focuses on data semantics, including system interoperability, data integration, inference, and data mining. His contributions extend to formal methods for software engineering, semantic collaboration tools, bioinformatics, situation awareness, information fusion, self-adaptive systems, and wireless communication. He has authored over 360 publications in leading journals and conferences, such as the National Academy of Science, Information Systems, the International Semantic Web Conference, and the Pacific Symposium on Biocomputing. He is also the inventor of 10 patents. Throughout his career, he has served on peer review panels for the National Science Foundation, the National Institutes of Health, and the Association for Computing Machinery. He has been a program committee member for numerous research conferences and has provided consulting services for government agencies and private companies. In addition, he has edited and authored several books and research monographs. Although he retired in June 2017, he remains engaged in research, academic publishing, and professional activities.
Department of Management and Innovation Systems, University of Salerno
Fisciano, Italy
Danilo Cavaliere (Member, IEEE) received both the master’s degree cum laude in computer science and the Ph.D. degree with judgement excellent from the University of Salerno (Italy) in 2014 and 2020, respectively. He now works as a researcher for the same institution. Dr. Cavaliere is on the editorial board of Neurocomputing Journal and was in Program Committees of international conferences, such as IEEE Symposium Series on Computational Intelligence (SSCI) and World Conference on eXplainable Artificial Intelligence (xAI). His research interests include artificial and computational intelligence, knowledge-based systems, soft computing, intelligent agents, data mining, and knowledge discovery, on which he has published many papers.
Department of Management and Innovation Systems, University of Salerno
Fisciano, Italy
Giuseppe Fenza (Senior Member, IEEE) received the Graduate degree and the Ph.D. degree in computer sciences from the University of Salerno, Italy, in 2004 and 2009, respectively. He is currently an Associate Professor in computer science at the University of Salerno. He has over 60 publications in fuzzy decision making, knowledge extraction and management, situation and context awareness, semantic information retrieval, service-oriented architecture, and ontology learning. More recently, he has worked in automating open-source intelligence and big data analytics for counterfeiting extremism and supporting information disorder awareness. His research interests include computational intelligence methods to support semantic-enabled solutions and decision making.
Department of Management and Innovation Systems, University of Salerno
Fisciano, Italy
Domenico Furno (Member, IEEE) received a master’s degree (cum laude) and PhD (with evaluation excellent) from University of Salerno, respectively, in 2007 and 2013. He has publications in situation/context awareness, soft computing, intelligent agents, data mining, semantic web, and knowledge representation. He started his research career by defining and testing hybrid approaches based on Computational Intelligence and Semantic Web methodologies and techniques for distributed Situation and Context Awareness scenarios. He is currently a researcher at the University of Salerno, and his research interests include Information Disorder Awareness.
Department of Management and Innovation Systems, University of Salerno
Fisciano, Italy
Vincenzo Loia (Senior Member, IEEE) received his degree in Computer Science from the University of Salerno, Italy, in 1985, and his Ph.D. in Computer Science from the Université Pierre & Marie Curie Paris VI, France, in 1989. He is currently a Full Professor of Computer Science at the University of Salerno, where he served as a Researcher from 1989 to 2000, and as an Associate Professor from 2000 to 2004. Prof. Loia's research interests include innovative approaches for complex problem-solving through agent and multi-agent systems, approximate reasoning using description logic and fuzzy logic, and knowledge extraction from unstructured data. His work spans various fields, from medicine to law and cyber intelligence. He coordinates the scientific committee of the "Multidisciplinary Observatory for the Fight Against Organised Crime and Terrorism", and contributes to projects on smart manufacturing and cyber-physical systems. Prof. Loia is the co-editor-in-chief of Soft Computing and the editor-in-chief of the Journal of Ambient Intelligence and Humanized Computing and serves as an editor for 14 other international journals.
Published In
Journal of Information Warfare
The definitive publication for the best and latest research and analysis on information warfare, information operations, and cyber crime. Available in traditional hard copy or online.
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