Modification of the Berlekamp-Massey algorithm for explicable knowledge extraction by SIEM-agents

The article discusses the problems of applying self-explanatory machine learning models in Security Information Event Management systems. We prove the possibility of using information processing methods in finite fields for extracting knowledge from security event repositories by mobile agents. Based on the isomorphism of fuzzy production and fuzzy relational knowledge bases, a constructive method for identifying patterns based on the modified Berlekamp-Massey algorithm is proposed. This allows security agents, while solving their typical cryptanalysis tasks, to use the existing built-in tools to extract knowledge and detect previously unknown anomalies. Experimental characteristics of the application of the proposed algorithm are given.