2020
DOI: 10.1109/access.2020.3019278
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Reversely Discovering and Modifying Properties Based on Active Deep Q-Learning

Abstract: Many researchers studied DQN (Deep Q-Networks) to train a game AI to beat human players, while we trained an improved AI to reversely modify properties of 3D video games. Our ultimate objective is to improve automatic debug for software and cloud services. However, the problem that reversely discovers properties in online 3D Video Games in an automatic way has not been studied yet. Therefore, related special difficulties are first discussed in the paper. RMDQN (a Reverse Method based on our active Deep Q-Netwo… Show more

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“…Attackers have enough theoretical knowledge about software reverse engineering for nonobfuscated original binary source codes. We assume they at least have basic theories as the paper [2] presented.…”
Section: Introductionmentioning
confidence: 99%
“…Attackers have enough theoretical knowledge about software reverse engineering for nonobfuscated original binary source codes. We assume they at least have basic theories as the paper [2] presented.…”
Section: Introductionmentioning
confidence: 99%