Authors: Giorgi Iashvili , Roman Odarchenko , Sergii Gnatyuk, Avtandil Gagnidze
Affiliation: Caucasus University, Tbilisi, Georgia, National Aviation University, Kyiv, Ukraine, East West University, Tbilisi, Georgia


Keywords: machine learning, content-based, vulnerability identification;
ABSTRACT. Machine learning and artificial intelligence are becoming increasingly common today. They are used in a variety of fields, including the energy, medical and financial sectors, to perform a variety of tasks and assist with key choices. Among other applications, machine learning and artificial intelligence are used to build powerful recommendation engines to provide users with relevant recommendations in a variety of areas, such as movie recommendations, friend suggestions on social networks, and much more. The objective of this paper is to identify and understand the vulnerabilities of hardware-based systems and related mechanisms in order to improve appropriate security measures. The aim of this paper is to develop an updated detection system model to detect hardware-based faults and provide users with necessary recommendations.


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