Secure and Efficient Data Sharing for Underground Exploration in Space‐Air‐Ground Integrated Networks

Abstract

ABSTRACT Underground surveying and mineral exploration increasingly rely on high‐resolution panoramic imaging for digital‐twin construction and remote operation. Yet transmitting massive visual data from remote mining sites is constrained by limited terrestrial infrastructure, high latency, and strict privacy requirements for sensitive geological assets. This paper proposes a Low‐Latency Privacy‐Preserved Data Sharing Framework (LPP‐DSF) for Space‐Air‐Ground Integrated Networks (SAGINs). We design a hierarchical architecture where UAVs act as mobile edge computing (MEC) relays to provide reliable air–ground connectivity and edge preprocessing for underground gateways. We formulate a joint offloading and resource allocation problem that explicitly includes the UAV‐to‐satellite backhaul delay, so as to minimize end‐to‐end latency and gateway‐side energy under link‐reliability and UAV capacity constraints, and develop a priority‐aware greedy offloading algorithm for real‐time decisions. To ensure sovereignty and auditability, LPP‐DSF integrates CP‐ABE with a consortium blockchain for fine‐grained access control and tamper‐evident provenance. Simulations show up to 25% lower latency than representative greedy baselines and about 65% lower latency than direct satellite transmission, while maintaining high throughput and negligible security overhead.