Abstract
A Decentralized Denial of Service is an attack done by an agent capable to control the spread of a malware. This is a combination of epidemiological and conflictual aspects between several decision makers. There exists in the literature papers that study (non oriented) epidemics and papers that study network attacks regardless the epidemiological aspect. We put together the two aspects and provide a new game theoretical model which is part of the family of partially observable stochastic games (POSG) but with particular features. We prove the consistency of heuristic search value iteration (HSVI) based algorithms. Our framework is applied to optimally design a cyber deception technique based on honeypots in order to control an epidemic cyber-attack of a network by a strategic attacker. Some basic simulations are proposed to illustrate the framework described in this work-in-progress paper.
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Notes
- 1.
Unlike in [6], we consider the use of the world “resistant”: (1) instead of “recovered” to keep in thought the non-vulnerability of the device; (2) instead of “removed” to keep in thought that the device is still in the game scenario.
- 2.
Since the number of infected node cannot exceed \(\left| V\right| \), the probability at each time-slot that all infected nodes become susceptible is greater or equal to \(\left( 1-\alpha \right) ^{\left| V\right| }\). So, at a certain time-slot, there will be no infected node and later all node will be resistant. There is no payoff from this time-slot and consequently the total expected reward converges even with discount factor \(\gamma =1\).
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Tsemogne, O., Hayel, Y., Kamhoua, C., Deugoue, G. (2020). Partially Observable Stochastic Games for Cyber Deception Against Network Epidemic. In: Zhu, Q., Baras, J.S., Poovendran, R., Chen, J. (eds) Decision and Game Theory for Security. GameSec 2020. Lecture Notes in Computer Science(), vol 12513. Springer, Cham. https://doi.org/10.1007/978-3-030-64793-3_17
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