• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>IEEE Wireless Communications and Networking Conference Workshops >Privacy Preserved Secure Offloading in the Multi-access Edge Computing Network
【24h】

Privacy Preserved Secure Offloading in the Multi-access Edge Computing Network

机译：隐私保留在多访问边缘计算网络中的安全卸载

获取原文
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Mobile edge computing (MEC) emerges recently to help process the computation-intensive and delay-sensitive applications of resource limited mobile devices in support of MEC servers. Due to the wireless offloading, MEC faces many security challenges, like eavesdropping and privacy leakage. The anti-eavesdropping offloading or privacy preserving offloading have been studied in existing researches. However, both eavesdropping and privacy leakage may happen in the meantime in practice. In this paper, we propose a privacy preserved secure offloading scheme aiming to minimize the energy consumption, where the location privacy, usage pattern privacy and secure transmission against the eavesdropper are jointly considered. We formulate this problem as a constrained Markov decision process (CMDP) with the constraints of secure offloading rate and pre-specified privacy level, and solve it with reinforcement learning (RL). It can be concluded from the simulation that this scheme can save the energy consumption as well as improve the privacy level and security of the mobile device compared with the benchmark scheme.
机译：最近，移动边缘计算（MEC）出现了帮助处理资源有限移动设备的计算密集型和延迟敏感应用，以支持MEC服务器。由于无线卸载，MEC面临许多安全挑战，如窃听和隐私泄漏。已经研究了现有研究的反窃听卸载或隐私卸载。然而，在实践中可能发生窃听和隐私泄漏。在本文中，我们提出了一种隐私保留的安全卸载方案，其旨在最大限度地减少能耗，其中包括对窃听者的位置隐私，使用模式隐私和安全传输是共同考虑的。我们将此问题作为一个受约束的马尔可夫决策过程（CMDP），其限制安全卸载率和预先指定的隐私级别，并用强化学习（RL）来解决它。可以从模拟中得出结论，该方案可以节省能量消耗，并与基准方案相比，提高移动设备的隐私水平和安全性。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号