Analysis of Approaches to the Implementation of the Knowledge Management Life Cycle in Intelligent Cyber Defense Systems
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Abstract
The article investigates the task of effective knowledge management in intelligent cyber defense systems in order to enhance their ability to detect, interpret and prevent modern cyber threats. It is substantiated that achieving a high level of their adaptability and situational awareness is possible only if full life cycle of knowledge management is implemented, which includes the stages of extraction, integration, organization, application and updating.
A comparative analysis of modern approaches to the implementation of the key phases of knowledge management in intelligent cyber defense systems is carried out. Particular attention is paid to the analysis of approaches to the organization of knowledge, such as ontological modeling, knowledge graphs, production rules, frames, neural network structures and semantic networks. Relevant knowledge representation languages, threat information exchange protocols, and knowledge mining tools are considered. The results obtained show that none of the approaches under consideration fully meets the defined criteria for effective knowledge management, in particular, structuredness, relevance, interpretability, scalability, flexibility, computational efficiency, and transparency of decision-making. In this regard, the expediency of creating a hybrid knowledge management architecture that combines the advantages of different approaches is substantiated.
Functional scheme is proposed that integrates the ontological core with modules for self-learning, automatic rule generation, verification, and feedback. The presented approach ensures end-to-end processing of knowledge from extraction to practical application in the form of informed decisions in real time. This creates the basis for building a new generation of intelligent cyber defense systems capable of self-improvement and sustainable response to threats in a dynamic cyber environment.
