A Multifactor Model of Countering Targeted Attacks Within the Framework of an İnfinite Antagonistic Game Scheme
Abstract
A multifactor model for countering targeted attacks is developed. This model considers the parties' financial resources (FRs) in an infinite antagonistic game framework. The model helps to make rational decisions on allocating FRs for cybersecurity under the threat of APT attacks. The proposed model allows for determining the game's value and assessing the degree of risk when using optimal mixed strategies for FRs. Optimal mixed strategies refer to a combination of strategies that maximize the player's expected payoff, taking into account the opponent's strategies. This concept is essential for analyzing the financial aspects of countering APT attacks. The relevance of the research is due to the growing number of targeted attacks on critical infrastructure objects. Computational experiments visualize the game's results, which is helpful for cybersecurity analysts. The solution to such a problem contributes to the analytical search for the game's meaning. It makes it possible to find the characteristics of the degree of risk of the players reaching the target when they apply optimal mixed strategies. The found solution contributes to the analysis of the situation with counteraction to the party attacking various objects, including critical ones, with the help of APT attacks.Additional Files
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