Abstract
This article proposes a mathematical model that helps to track a player’s game actions and present them in a structured form. The gaming process is presented as a set of states that are connected by a player’s actions. Each state is a set of predicates that characterize the player’s knowledge about the game. This mathematical model was developed as a step in achieving the general goal of the research branch, which is to increase the safety of an information system from social engineering attacks by developing a serious game. This serious game is aimed at improving players’ skills in recognition and counteraction to social engineering attacks as well as at raising awareness among employees.
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Notes
- 1.
We use two predicates to describe the player’s knowledge of the NPC’s password because during the game it is possible to learn only some characters in the password by using shoulder surfing mechanic.
- 2.
If the player learns the same information from 2 different actions, the system stores the one that the player performed first.
- 3.
The action extracted from the queue is guaranteed to provide the player some new information. If feff(a) ∈ s, where s is a current state of the game environment, the action a is considered redundant and is not recorded.
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Acknowledgments
The research was carried out in the framework of the project on state assignment SPIIRAN No 0073–2019–0003, with the financial support of the RFBR (project No 20–07–00839 Digital twins and soft computing in social engineering attacks modeling and associated risks assessment; project No 18–01–00626 Methods of representation, synthesis of truth estimates and machine learning in algebraic Bayesian networks and related knowledge models with uncertainty: the logic probability approach and graph systems).
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Krylov, B., Abramov, M., Khlobystova, A. (2021). Automated Player Activity Analysis for a Serious Game About Social Engineering. In: Dolinina, O., et al. Recent Research in Control Engineering and Decision Making. ICIT 2020. Studies in Systems, Decision and Control, vol 337. Springer, Cham. https://doi.org/10.1007/978-3-030-65283-8_48
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