AI-Based Joint Optimization of QoS and Security for 6G Energy Harvesting Internet of Things
AI-Based Joint Optimization of QoS and Security for 6G Energy Harvesting Internet of Things
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DOI：
10.1109/jiot.2020.2982417
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发表时间：
2020-08-01
影响因子：
10.6
通讯作者：
Kato, Nei
中科院分区：
文献类型：
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作者：
Mao, Bomin;Kawamoto, Yuichi;Kato, Nei
物联网（IoT）网络中的数据隐私和机密性已成为最受关注的问题之一，由于威胁的增加。常用的物联网芯片在链路层采用固定的认证和加密方案，即使通常支持多种选项。由于不同的认证和加密操作意味着不同的保护和不同的能量消耗，固定安全策略忽略了剩余能量，动态威胁和不同的服务需求，导致能量效率低。此外，固定的高级别安全保护消耗太多的能量，即使安全要求可能很低，这导致工作时间很短。为了解决这个问题，我们提出了一种基于人工智能（AI）的自适应安全规范方法，用于6G物联网网络，其中物联网设备通过不同的频段连接到蜂窝网络，包括太赫兹（THz）和毫米波（mmWave）。物联网传感设备被认为支持预计将在6G中广泛采用的能量收集技术。在我们的建议中，扩展卡尔曼滤波（EKF）方法，首先采用预测未来的收获功率。然后，在每个能量感知周期中，设计一个数学模型来计算不同安全策略所需的能量，并选择能够满足服务需求且避免能量耗尽的最高级别保护。仿真结果表明，该方案不仅能为不同的业务提供满意的安全保护，而且能通过调整安全保护来避免能量耗尽，从而显著提高了吞吐量和工作时间。
The data privacy and confidentiality in Internet-of-Things (IoT) networks have been one of the most concerned problems due to increasing threats. The commonly utilized IoT chips adopt a fixed authentication and encryption scheme in the link layer even though multiple options are usually supported. As different authentication and encryption operations mean dissimilar protections and various energy consumption, the fixed security strategy neglects the remaining energy, dynamic threats, and diverse service requirements, leading to low energy efficiency. Moreover, fixed high-level security protections consume too much energy even though the security requirement may be low, which results in a short working time. To address this problem, we propose an artificial intelligence (AI)-based adaptive security specification method for 6G IoT networks where the IoT devices are connected to cellular networks via different frequency bands, including terahertz (THz) and millimeter wave (mmWave). The IoT sensing devices are assumed to support the energy harvesting technique which is expected to be widely adopted in 6G. In our proposal, the extended Kalman filtering (EKF) method is first adopted to predict future harvesting power. Then, in each energy-aware cycle, we design a mathematical model to calculate the required energy of different security strategies and choose the supported highest level protection which can meet service requirement and avoid energy exhaustion. The simulation results illustrate that the proposal can not only provide satisfied security protection for different services but also adjust the security protection to avoid the energy exhaustion, leading to a significant improvement of throughput and working time.