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Deception Maze: A Stackelberg Game-Theoretic Defense Mechanism for Intranet Threats

机译:欺骗迷宫:用于Intranet威胁的Stackelberg游戏理论防御机制

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The intranets in modern organizations are facing severe data breaches and critical resource misuses. By reusing user credentials from compromised systems, Advanced Persistent Threat (APT) attackers can move laterally within the internal network. A promising new approach called deception technology makes the network administrator (i.e., defender) able to deploy decoys to deceive the attacker in the intranet and trap him into a honeypot. Then the defender ought to reasonably allocate decoys to potentially insecure hosts. Unfortunately, existing APT-related defense resource allocation models are infeasible because of the neglect of many realistic factors.In this paper, we make the decoy deployment strategy feasible by proposing a game-theoretic model called the APT Deception Game to describe interactions between the defender and the attacker. More specifically, we decompose the decoy deployment problem into two subproblems and make the problem solvable. Considering the best response of the attacker who is aware of the defender’s deployment strategy, we provide an elitist reservation genetic algorithm to solve this game. Simulation results demonstrate the effectiveness of our deployment strategy compared with other heuristic strategies.
机译:现代组织中的内联网正面临严重的数据违规和关键资源滥用。通过从受损系统中重复使用用户凭据,高级持久威胁(APT)攻击者可以在内部网络中横向移动。一个有希望的新方法称为欺骗技术使网络管理员(即,后卫)能够部署诱饵来欺骗内联网中的攻击者并将他捕获到蜜罐中。然后,后卫应该合理地将诱饵分配给潜在的不安全的主人。不幸的是,现有的APT相关的防御资源分配模型是不可行的,因为忽视了许多现实因素。在本文中,我们通过提出称为APT欺骗性游戏的游戏理论模型来描述诱饵部署策略来描述后卫之间的相互作用可行和攻击者。更具体地,我们将诱饵部署问题分解为两个子问题,并解决问题。考虑到了解后卫部署策略的攻击者的最佳响应,我们提供了一个精英预订遗传算法来解决这场比赛。仿真结果表明,与其他启发式策略相比,我们的部署策略的有效性。

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