Geosynchronous (GEO) satellite links provide IP backhaul to remote critical infrastructure for utilities, telecom, government, military, and commercial users. To date, academic studies of GEO infrastructure have focused on a handful of satellites and specific use cases. We perform the first broad scan of IP traffic on 39 GEO satellites across 25 distinct longitudes with 411 transponders using consumer-grade equipment. We overcome the poor signal quality plaguing prior work and build the first general parser that can handle the diverse protocols in use by heterogeneous endpoints. We found 50% of GEO links contained cleartext IP traffic; while link-layer encryption has been standard practice in satellite TV for decades, IP links typically lacked encryption at both the link and network layers. This gives us a unique view into the internal network security practices of these organizations. We observed unencrypted cellular backhaul traffic from several providers including cleartext call and text contents, job scheduling and industrial control systems for utility infrastructure, military asset tracking, inventory management for global retail stores, and in-flight wifi.

Immersive videos, also known as 360$^{\circ }$videos, have gained significant attention in recent years due to their ability to provide an interactive and engaging experience. However, the development of immersive video streaming faces several challenges, including privacy concerns, the need for accurate viewport prediction, and efficient bandwidth allocation. In this paper, we propose a comprehensive system that integrates three specialized modules: the Privacy Protection module, the Viewport Prediction module, and the Bitrate Allocation module. The Privacy Protection module introduces a novel approach to differential privacy tailored for immersive video environments, considering the spatial and temporal correlations in viewport and gaze motion data. The Viewport Prediction module leverages a crossmodal attention mechanism based on the transformer to predict user viewport movements by analyzing the complex interactions between historical data, video content, and gaze patterns. The Bitrate Allocation module employs an adaptive tile-based bitrate allocation strategy using an exponential decay function to optimize video quality and maximize user quality of experience. Experimental results demonstrate that our proposed framework outperforms three state-of-the-art integrated frameworks, achieving an average QoE improvement of 21.61%. This paper offers substantial novelty in addressing privacy concerns, leveraging gaze information for viewport prediction, and utilizing underlying correlations between different features.