Introducing the CYSAS-S3 Dataset for Operationalizing a Mission-Oriented Cyber Situational Awareness

• Published in: Sensors (Basel, Switzerland) Switzerland), 2022-07, Vol.22 (14), p.5104
• Main Authors: Medenou Choumanof, Roumen Daton, Llopis Sanchez, Salvador, Calzado Mayo, Victor Manuel, Garcia Balufo, Miriam, Páramo Castrillo, Miguel, González Garrido, Francisco José, Luis Martinez, Alvaro, Nevado Catalán, David, Hu, Ao, Rodríguez-Bermejo, David Sandoval, Pasqual de Riquelme, Gerardo Ramis, Sotelo Monge, Marco Antonio, Berardi, Antonio, De Santis, Paolo, Torelli, Francesco, Maestre Vidal, Jorge
• Format: Article
• Language: English
• Subjects: advanced persistent threats; Chains; cyber defence; cyber situational awareness; Cybersecurity; dataset; Datasets; decision-making; Defense; Digital transformation; Military operations; Situational awareness; Software
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s22145104

The digital transformation of the defence sector is not exempt from innovative requirements and challenges, with the lack of availability of reliable, unbiased and consistent data for training automatisms (machine learning algorithms, decision-making, what-if recreation of operational conditions, support the human understanding of the hybrid operational picture, personnel training/education, etc.) being one of the most relevant gaps. In the context of cyber defence, the state-of-the-art provides a plethora of data network collections that tend to lack presenting the information of all communication layers (physical to application). They are synthetically generated in scenarios far from the singularities of cyber defence operations. None of these data network collections took into consideration usage profiles and specific environments directly related to acquiring a cyber situational awareness, typically missing the relationship between incidents registered at the hardware/software level and their impact on the military mission assets and objectives, which consequently bypasses the entire chain of dependencies between strategic, operational, tactical and technical domains. In order to contribute to the mitigation of these gaps, this paper introduces CYSAS-S3, a novel dataset designed and created as a result of a joint research action that explores the principal needs for datasets by cyber defence centres, resulting in the generation of a collection of samples that correlate the impact of selected Advanced Persistent Threats (APT) with each phase of their cyber kill chain, regarding mission-level operations and goals.