SYSTEM ENGINEERING APPROACHES TO SECURING THE SAFETY OF ARTIFICIAL INTELLIGENCE SYSTEMS, TAKING INTO ACCOUNT THE QUALITY OF DATA FOR MACHINE LEARNING
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Annotation: The article discusses some of the challenges of ensuring the security of artificial intelligence systems related to the quality of data for machine learning. It provides a brief analysis of the current standard that defines processes at all stages of the data lifecycle. The article also offers some recommendations for ensuring the security of artificial intelligence systems (AIS) during the implementation of data lifecycle processes.
Keywords: information security, comprehensive security, functional security, artificial intelligence systems, technical information protection
Page numbers: 5-10.
For citation: Zatsarinny A. A., Gavrilov V. E. System engineering approaches to securing the safety of artificial intelligence systems, taking into account the quality of data for machine learning // Electronic Scientific Journal IT-Standard. – 2026. – No. 1. – pp. 5-10.