Mobile offloading game against smart attacks
Mobile offloading game against smart attacks
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DOI：
10.1109/access.2016.2565198
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发表时间：
2016-05
期刊：
影响因子：
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通讯作者：
Liang Xiao;Caixia Xie;Tianhua Chen;H. Dai;H. Poor
中科院分区：
文献类型：
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作者：
Liang Xiao;Caixia Xie;Tianhua Chen;H. Dai;H. Poor
移动云计算使智能手机等移动设备能够通过接入点或基站将数据卸载到云端，以减少能耗并改善用户体验。然而，移动卸载很容易受到聪明攻击者的攻击，他们可以根据无线电环境的状态和卸载过程，利用软件定义的无线电执行多种类型的攻击，例如欺骗和干扰。本文研究了一种针对智能攻击的移动卸载博弈，其中移动设备选择其卸载速率，智能攻击者选择其攻击类型，安全代理决定是否启动卸载的全面数据保护。移动设备、智能攻击者和安全代理之间的交互被制定为安全的移动卸载游戏。为静态安全卸载博弈提供了纳什均衡（NE）及其存在条件。针对动态环境，提出了一种基于 Q 学习的移动卸载策略，以应对移动设备不知道系统参数的智能攻击。仿真结果表明，所提出的卸载策略提高了卸载率和安全性能。
Mobile cloud computing enables mobile devices such as smartphones to offload data to clouds via access points or base stations to reduce energy consumption and improve their user experience. However, mobile offloading is vulnerable to smart attackers that can exploit software defined radios to perform multiple types of attacks, such as spoofing and jamming, based on the status of radio environments and the offloading process. In this paper, a mobile offloading game against smart attacks, in which a mobile device chooses its offloading rate, a smart attacker chooses the type of its attack, and a security agent decides whether to initiate full data protection for the offloading, is investigated. The interactions among a mobile device, a smart attacker and a security agent are formulated as a secure mobile offloading game. The Nash equilibrium (NE) and its existence conditions are provided for the static secure offloading game. A Q-learning based mobile offloading strategy is proposed for dynamic environments to address smart attacks, in which the mobile device is unaware of the system parameters. Simulation results show that the proposed offloading strategy improves both the offloading rate and the security performance.