Abstract
Internet of Things (IoT) is envisioned to expand Internet connectivity of the physical world, and the mobile edge cloud can be leveraged to enhance the resource-constrained IoT devices. The performance of the cloud-enhanced IoT applications depends on various system-wide information, such as the wireless channel states between IoT devices and their corresponding serving edge cloud nodes. However, with the semi-trusted edge resources and the public nature of wireless channels, public sharing of system information should be avoided to better balance the tradeoff between performance and security. In this paper, the benefits of local information exchange is investigated, where the privately-owned physical layer channel information is leveraged to extract lightweight keys. For the point-to-point wireless communications links with multiple passive eavesdroppers, the security metric in terms of conditional min-entropy is evaluated via the proposed Dynamic Bayesian Model. The proposed model can flexibly incorporate various dynamic information flows in the system and quantify the information leakage caused by wireless broadcasting. The rigorously defined and derived security metrics for such a key generation pipeline has been verified via the real-world collected time-varying wireless channel data. The designed model can achieve previously inconceivable security properties.
Highlights
I NTERNET of Things (IoT) is envisioned to expand Internet connectivity and fuse the digital and physical world [1]–[5]
The performance of Internet of Things (IoT) applications depends on the following four categories of system-wide information [11]–[19]: 1) static cloud resource configuration parameters specified by the existing public standardization or protocols; 2) dynamic resource utilization status; 3) status of the data pipeline, including the channel state of the wireless medium and the bandwidth measurement of the wired medium; 4) information of the data flow being transmitted in the pipeline
This paper focuses on the following fundamental question about performance improvement and information leakage caused by information exchange in the cloud enhanced IoT networks
Summary
I NTERNET of Things (IoT) is envisioned to expand Internet connectivity and fuse the digital and physical world [1]–[5]. This is a strong assumption for the cloud-enabled IoT infrastructure because of the public nature of the cloud resources and wireless channels. To theoretically measure the security performance of the generated key with multiple malicious users eavesdropping the broadcasted probing signals, we propose to leverage a probabilistic graphical model named Dynamic Bayesian Network (DBN).
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