论文标题
部分可观测时空混沌系统的无模型预测
Technical Report-IoT Devices Proximity Authentication In Ad Hoc Network Environment
论文作者
论文摘要
储层计算是预测湍流的有力工具，其简单的架构具有处理大型系统的计算效率。然而，其实现通常需要完整的状态向量测量和系统非线性知识。我们使用非线性投影函数将系统测量扩展到高维空间，然后将其输入到储层中以获得预测。我们展示了这种储层计算网络在时空混沌系统上的应用，该系统模拟了湍流的若干特征。我们表明，使用径向基函数作为非线性投影器，即使只有部分观测并且不知道控制方程，也能稳健地捕捉复杂的系统非线性。最后，我们表明，当测量稀疏、不完整且带有噪声，甚至控制方程变得不准确时，我们的网络仍然可以产生相当准确的预测，从而为实际湍流系统的无模型预测铺平了道路。
Internet of Things (IoT) is a distributed communication technology system that offers the possibility for physical devices (e.g. vehicles home appliances sensors actuators etc.) known as Things to connect and exchange data more importantly without human interaction. Since IoT plays a significant role in our daily lives we must secure the IoT environment to work effectively. Among the various security requirements authentication to the IoT devices is essential as it is the first step in preventing any negative impact of possible attackers. Using the current IEEE 802.11 infrastructure this paper implements an IoT devices authentication scheme based on something that is in the IoT devices environment (i.e. ambient access points). Data from the broadcast messages (i.e. beacon frame characteristics) are utilized to implement the authentication factor that confirms proximity between two devices in an ad hoc IoT network.
