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- W2785187462 abstract "Advanced Persistent Threat (APT) attackers apply multiple sophisticated methods to continuously and stealthily steal information from the targeted cloud storage systems and can even induce the storage system to apply a specific defense strategy and attack it accordingly. In this paper, the interactions between an APT attacker and a defender allocating their Central Processing Units (CPUs) over multiple storage devices in a cloud storage system are formulated as a Colonel Blotto game. The Nash equilibria (NEs) of the CPU allocation game are derived for both symmetric and asymmetric CPUs between the APT attacker and the defender to evaluate how the limited CPU resources, the date storage size and the number of storage devices impact the expected data protection level and the utility of the cloud storage system. A CPU allocation scheme based on hotbooting policy hill-climbing (PHC) that exploits the experiences in similar scenarios to initialize the quality values to accelerate the learning speed is proposed for the defender to achieve the optimal APT defense performance in the dynamic game without being aware of the APT attack model and the data storage model. A hotbooting deep Q-network (DQN)-based CPU allocation scheme further improves the APT detection performance for the case with a large number of CPUs and storage devices. Simulation results show that our proposed reinforcement learning based CPU allocation can improve both the data protection level and the utility of the cloud storage system compared with the Q-learning based CPU allocation against APTs." @default.
- W2785187462 created "2018-02-02" @default.
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- W2785187462 date "2018-01-18" @default.
- W2785187462 modified "2023-10-16" @default.
- W2785187462 title "Defense Against Advanced Persistent Threats in Dynamic Cloud Storage: A Colonel Blotto Game Approach" @default.
- W2785187462 cites W2120713742 @default.
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- W2785187462 doi "https://doi.org/10.48550/arxiv.1801.06270" @default.
- W2785187462 hasPublicationYear "2018" @default.
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