Identifying and prioritizing predictive indicators in cyber resilience evaluation

The purpose of this research is to explain how to evaluate the cyber resilience of the Islamic Republic of Iran Army by predicting cyber attacks. The current research was done with a descriptive and integrated method of applied type and research approach. The desired data was collected by studying authentic documents and interviews with 9 experts in the field of research, and a questionnaire was compiled based on them. The face/content validity of the questionnaire and its reliability were confirmed with Cronbach's alpha coefficient of 0.83 and among the sample size of 100 commanders, chiefs and managers and cyber experts of the Islamic Republic of Iran Army and operational officers at executive levels. and staff familiar with the specifics and characteristics of cyber missions, was divided. In this research, after studying sources and interviewing experts, 3 dimensions and 8 components were calculated to evaluate the cyber resilience of the Islamic Republic of Iran Army by predicting cyber attacks, which were analyzed using SPSS software and statistical methods. 73% of the sample community believe that the use of machine learning algorithms to detect unusual patterns, the use of intrusion detection and response systems using artificial intelligence, the use of neural networks to detect unusual patterns and identify cyber threats, cyber directives and regulations, backup The systematic use of data, the existence of a cyber risk management team, the creation of cyber command and control centers and the regular execution of hypothetical attack scenarios can be used in...