An information security audit method (ISA) for a distributed computer network (DCN) of an informatization object (OBI) has been developed. Proposed method is based on the ISA procedures automation by using Bayesian networks (BN) and artificial neural networks (ANN) to assess the risks. It was shown that such a combination of BN and ANN makes it possible to quickly determine the actual risks for OBI information security (IS). At the same time, data from sensors of various hardware and software information security means (ISM) in the OBI DCS segments are used as the initial information. It was shown that the automation of ISA procedures based on the use of BN and ANN allows the DCN IS administrator to respond dynamically to threats in a real time manner, to promptly select effective countermeasures to protect the DCS.

Additions were proposed to the method of organizing the information security (IS) event management process of companies. Unlike existing solutions, the algorithm of the "Event handling" subprocess was detailed. This detailing is a complex, which includes the IS event processing substage. In addition, the proposed detailing of the "Event Handling" subprocess allows for covering the entire life cycle of an IS event. The performed research allows in practice to fill in potential gaps in information when creating a company's ISMS. An additional advantage of the proposed solution is the possibility of using this sub-process as an independent one. The proposed approach makes it possible to simplify the procedure for managing the information security of a company as a whole, as well as potentially reduce the costs of its construction for small companies and enterprises. Also, this subprocess can be considered as an independent information security management process, for example, for a company's CIS. The proposed solutions and additions, in contrast to similar studies, are characterized by invariance with respect to the methods of implementing the company's IS infrastructure solutions, and in particular its CIS. This ultimately allows, without changing the methodological tools, to scale this approach and adapt it to the ISMS of various companies.